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Sustainable material selection for additive manufacturing technologies: A critical analysis of rank reversal approachThe world is moving towards a situation where resource scarcity leads to increased material cost, and the government is bound to dispose of heavy wastes generated by the growing population. Additive Manufacturing (AM) has bought a significant revolution in the current manufacturing processes. AM can fabricate complex and intricate shapes with ease. Material selection is an essential aspect in AM as a wide range of compatible materials available for AM. Appropriate material selection is necessary for cleaner production and sustainable development. Sustainable material selection considering various material properties and varied criteria can be effectively managed by Multi-Criteria Decision Making (MCDM) approach. However, several MCDM methods have a rank reversal problem, in which the rank of alternatives got changed when an alternative is added or removed from all considered alternatives. In this regard, this work presents a sustainable material selection of AM technologies. Sustainable material selection has been made for 3 a.m. technologies, namely Fused Deposition Modelling (FDM), Selective Laser Sintering (SLS), and Stereolithography (SLA). Four MCDM techniques have been used to analyze and compare AM materials, namely SAW (Simple Additive Weighting), MOORA (Multi-Objective Optimization based on Ratio Analysis), TOPSIS (Technique for order performance by similarity to ideal solution), and VIKOR (Vlsekriterijumska Optimizacija I Kompromisno Resenje). Rank reversal problems associated with MCDM methods are also highlighted in the material selection stage. The results reveal that ‘TPU Elastomer’, ‘Accura HPC′, and ‘Duraform EX′ are identified as the best material for FDM, SLA, and SLS based AM technologies. Further, practical and research implications have been derived based on the study to help industrial practitioners, researchers, and decision-makers for the selection of the best materials in the product development stage to support cleaner production.Advanced technology like AM can help manufacturing firms enhance their capabilities and become more competitive (). Globally 54% of energy is consumed by the industrial sector (), a major concern for society and needed massive transformation in technologies to make it more sustainable. The forecasting study on resource consumption done by the UN reveals that by 2030, the existing resources need to be double to deal with increasing resource consumption due to the vast population growth rate (). Nowadays, AM is gaining vital growth because it is a widely used technique for producing a complex structure with ease and multi-material (). More industries are adopting AM technologies as they are becoming familiar with the benefits of adopting AM technologies, which accelerate the product development phase and with cost-effectiveness (). AM can fabricate complex structures and geometry with lesser cost and time with multi-material properties (). AM can provide an immediate customized product, complex and intricate shapes, innovative product design to the customer, increasing competition in the market (). Apart from its advantages and opportunities, AM provides several sustainable benefits () and can act as a critical technology to sustain the future (). Recently, several studies have been done to evaluate the sustainable performance of AM processes (). It is found that the common method adopted in assessing sustainability is the LCA study and SDM approach (). As the demand for new product development increases, Additive Manufacturing (AM) is gaining vital importance in the new product development process. Various additive manufacturing technologies available are Fused Deposition Modelling (FDM), Selective Laser Sintering (SLS), Stereolithography (SLA), and so on …A report on plastic economy presented by Ellen MacArthur Foundation (EMF) shows that by 2050, plastic wastes will be more by weight compared to fish in the ocean because of current waste generation and resource consumption (). Sustainable material selection plays a vital role in minimizing resource consumption. Sustainable material selection ensures the recycling of material for further use. Several benefits associated with the recycling of material are reduced weight, resource conservation, and cleaner production. Sustainable material selection enables triple-bottom-line sustainability benefits, namely, social, economic, and environmental benefits (Materials play an essential role throughout the life span of a product. Current developments and industrial globalization reach the planetary threshold, where a small increment in carbon emissions will significantly increase global warming (). It generates many environmental problems such as degradation of fresh water, biodiversity loss, land degradation, and an increase in greenhouse gas emissions. The existence of various researches in material selection () shows the importance of material selection for sustainable development. Appropriate material selection is essential in the product development stage. Each material has different properties, so proper criteria must be selected based on the application to analyze alternate materials. For sustainable material selection, not only mechanical properties but environmental properties are also important.The selection of material can be effectively managed by a multi-criteria decision making (MCDM) approach. Many MCDM methods are available to solve such problems (). Like AHP (Analytic Hierarchical Process), VIKOR (Vlsekriterijumska Optimizacija I Kompromisno Resenje), SAW (Simple Additive Weighting), MOORA (Multi-Objective Optimization based on Ratio Analysis), IEM (Information Entropy Method), TOPSIS (a technique for order performance by similarity to ideal solution), COPRAS (complex proportional assessment) and BWM (Best Worst Method). However, several MCDM methods have a rank reversal problem, in which the rank of alternatives got changed when an alternative is added or removed from all considered alternatives (). To deal with growing demand and resource consumption, sustainable material selection for AM is essential. In this context, this work addressed three research questions;RQ1: What are the potential materials available for AM applications?RQ2: What are the critical material selection criteria for different AM technologies?RQ3: How materials can be analyzed to identify the priority order using MCDM methods?As per developed research questions, the objectives of this work is as follows:To identify potential materials available for AM applications.To identify critical material selection criteria for different AM technologies.To analyze materials using different MCDM applicationsTo propose materials priority order for different AM technologies for cleaner production.To achieve these objectives, this work starts with the identification of potential materials for different AM technologies through a literature review. Several criteria have been considered both from traditional and sustainable perspective to compare AM materials. Sustainable material selection has been made for widely used AM technologies, namely FDM, SLS, and SLA. The mentioned 3 a.m. technologies are commonly used in various applications (). Previous studies on AM process selection show that FDM, SLS, and SLA are considered the best AM technologies (). So, this work finds FDM, SLS, and SLA based AM technologies for analyzing sustainable materials. This work uses widely used MCDM methods, namely SAW, MOORA, VIKOR, and TOPSIS.Further, the rank reversal problem associated with considered MCDM methods is also included in this study. The main contribution of the study is the prioritization of materials for FDM, SLS, and SLA based AM technologies by considering both traditional and sustainable criteria. Practical and research implications have been derived based on the study to help industrial practitioners, researchers, and decision-makers for the selection of the best materials in the product development stage to support cleaner production.This paper is organized in the following manner. A summary of the previous literature on materials of AM is presented in section . Description of considered methodology for material selection is discussed in Section includes an analysis of materials of different AM technologies. Section contains results and discussions on findings. Section contains discussions and implications of the study. Section presents conclusions, limitations, and future works.This section includes a review of previous articles to support this work. This section is further divided into three subsections, a literature review on AM materials, a literature review on sustainable material selection, and a research gap.A wide range of materials is available in the field of AM manufacturing. Various researchers have discussed and analyzed materials available for AM ( discussed several materials of AM technologies. The study analyses different properties of AM materials for the proper selection of materials to minimize defects related to AM processes. Further, discussed the abilities of FDM-based 3D printers and analyzed their materials. The study considered twelve material suitable for FDM printer and analyzed based on biocompatibility and solvent compatibility. The adoption of the circular economy in the AM process was discussed by through a case study of the Netherlands. The study suggested searching for local materials that can be recycled and act as input material for AM part fabrication. This will leads to cleaner production and enhance sustainable development.A review on AM process, materials, and their applications in different sectors was presented by . The study discusses materials development in the field of AM, including metals, polymer, ceramics, and concretes. Further, the study presents a survey on the benefits and limitations of AM processes. aimed to fabricate the 3D printed composite material part. The study uses ABS, PLA, and HIPS material to fabricate composite parts and investigate the thermal and mechanical properties of printed parts. The study also analyzed the microstructure of the composite structure produced pieces to confirm the result. Later, developed a metal matrix composite for FDM feedstock by reinforcing ceramic material to low-density polyethylene (LDPE). The study highlights different process parameters on the fabricated part with Taguchi’s L9 orthogonal array.A study to fabricate high-strength punches using AM processes was presented by . The study considered three material and fabricated holes using powder bed fusion based AM process. Different mechanical properties were tested, and Energy Dispersive Spectra (EDS) and Scanning Electron Microscopic (SEM) imaging were also studied to analyze the microstructure of fabricated parts. studied the environmental impact of AM products by considering electricity, fluid, and material consumption. For evaluating ecological implications, the study focused not only on the processing stage but also considers preprocessing and post-processing steps as well.A mathematical algorithm to optimize the material selection of AM processes was proposed by . The study considers three materials: ABS, silicon carbide, and aluminum, and analyzed using AHP methodology. The considered criteria were material cost, manufacturability, and recyclability and the result showed that aluminum has the highest cost-effectiveness value compared to other considered material. Further, in 2020, discussed various AM processes for their applications. The study presents material selection for energy storage devices printed using AM technology. Later, presented a review on biodegradable polymer material used by AM processes for biomedical applications. The study also discussed various biodegradable classes of polymer material used in the AM process by considering their extraction and physical and chemical properties. presented a review of available polymer materials related to AM technologies. The study discusses various AM technologies along with their development. A recent development in AM materials, along with their application areas, is also highlighted. reviewed the current literature on polymer chemistry to achieve sustainability in the field of AM through a proper focus on biodegradable polymer. presented a review on commercially available materials along with high-performance polymer composites that are used in AM applications. Materials pertaining to four technologies of AM, namely, FDM, SLS, Multijet fusion, and SLA was discussed by authors.Sustainable material selection is an essential aspect of sustainable development. Many researches discussed the importance of material selection for new product development under a sustainable environment ( analyzed sustainable material selection for construction materials using the fuzzy AHP method. The study considered six criteria based on the triple bottom line approach to sustainability. A model based on the AHP approach to analyze fiber-reinforced composites material was presented by . The study used an expert choice software tool for analysis and found propylene as the best material. This study helps automotive firms to enable green technology by the sustainable selection of materials. Further, presented challenges associated with sustainable material selection and suggested using LCA packages for effective decision making in sustainable material selection. analyzed the construction material by considering sustainable indicators and uses the hybrid MCDM method for analysis. The indicators were collected from the literature review and proposed a model to analyze the construction material. Further, the developed model was validated through a construction company in the UAE. Further, in 2017, aimed to develop automotive parts remanufacture by properly selecting material in the design stage. A list of criteria was shortlisted for analyzing materials related to automotive parts and used a fuzzy TOPSIS approach to analyze alternative materials. Further, the developed concept was validated by presenting two case studies in the automotive sector.An analysis of sustainable material selection for automobile door panels was presented by . The study integrated LCA, TOPSIS, and IEM method to analyze alternative materials. LCA was used to identify potential categories, IEM was used to calculate weights of criteria, and TOPSIS was used to prioritize alternatives based on selected criteria. Further, presented the rank reversal problem associated with MCDM methods. The study showed several material selection problems by using TOPSIS, VIKOR, and COPRAS based MCDM methods to analyze rank reversal associated with MCDM methods. Later, a hybrid MCDM approach for sustainable material selection for construction was proposed by . Sustainability criteria were considered in the study based on TBL. The study uses DEMATEL to analyze the weights of criteria for analyzing materials and uses fuzzy ANP to prioritize construction materials.A material selection tool based on software support that helps the designer select a suitable composite configuration for aircraft structures was developed by . The study uses LCA and Life Cycle Costing (LCC) to analyze the economic and environmental performance of the material. Further, results reveal that the developed tool helps in significant weight reduction and enhance sustainable development. analyzed materials for construction work by considering sustainable aspects. The study used the LCA module to analyze the environmental impact of construction materials and uses the ANP method for sustainable material selection.Further, in 2020, Maghsoodi et al. show the importance of material selection for sustainable development. The study highlights BWM, Combined Compromise Solution (CoCoSo), and multi MOORA method for optimum selection phase change material used in construction sectors. Later, presented an approach for material selection based on environmental and durability indicators. Further, a case study was presented for polymer material selection based on developed indicators to show developed indicators’ applicability.AM is rapidly growing from the last decade and shows a higher potential for reducing material consumption and enabling cleaner production. AM can fabricate complex and intricate shapes with ease. Material selection is an essential aspect in AM as a wide range of compatible materials available for AM. Sustainable material selection is necessary for cleaner production and sustainable development. Sustainable material selection enables triple-bottom-line benefits of sustainability, namely, social, economic, and environmental benefits. From the existing literature survey, it is found that many studies are available pertaining to the selection of AM materials (). Various authors have discussed polymer-based materials (), and many have studied ceramic, metal, composites-based materials (). But, Specific studies pertaining to different AM technologies are rare. Some studies are available on materials analysis based on their properties, but very few studies are available on AM materials’ ranking. Studies on AM material selection considering sustainability criteria are rare, and rank reversal problems in AM material selection using MCDM methods have not been reported.In this regard, this study attempts to fulfill all research gaps. Sustainable material selection has been made for widely used AM technologies, namely FDM, SLS, and SLA. The mentioned 3 a.m. technologies are commonly used in various applications (). Previous studies on AM process selection show that FDM, SLS, and SLA are considered the best AM technologies (). So, this work finds FDM, SLS, and SLA based AM technologies for analyzing sustainable materials. Four MCDM techniques have been used to analyze and compare AM materials, namely SAW, MOORA, TOPSIS, and VIKOR. Also, the rank reversal problem associated with MCDM applications is discussed. The main contribution of the study is the prioritization of materials for FDM, SLS, and SLA based AM technologies by considering both traditional and sustainable criteria.In this section, the different methodologies used in this work have been demonstrated. IEM was used to analyze the weights of other criteria used in sustainable material selection for AM. For the sustainable material selection of AM technologies, this work considers four MCDM methodology, namely SAW, MOORA, TOPSIS, and VIKOR. MCDM method starts with developing the decision matrix, where selected alternatives are compared with all criteria. The decision matrix is presented in the model (X=[C1C2…CnA1X11X12…X1nA2X21X22…X2n⋮⋮⋮⋱⋮AmXm1Xm2⋯Xmn]Xij presents a rating of ith alternative with respect to jth criteria. A (1,2, ….m) are m alternatives and C(1,2, ….n) are n criteria.Based on this decision matrix, the decision-maker provides the best alternative among all considered alternatives. For analysis, criteria are divided into two categories; beneficial criteria and non-beneficial criteria.The first step of any MCDM method is to identify the weights of criteria. There are many available methods to calculate weights of criteria: IEM, Digital logic, BWM, and AHP (). IEM is used in this study to calculate the weights of criteria because of its broad applicability in real-time data.The next step in the MCDM method is normalization. Different normalization steps are followed in other MCDM methods. After identifying the weights of criteria and normalization of the decision matrix, the final step is to calculate the performance of each alternative based on the criteria. As MCDM methods have different normalization steps and different ways of calculating the performance of alternatives, the ranking achieved by other MCDM methods may vary. The spearman rank correlation method is used to analyze the similarity between MCDM methods (). A detailed description of methodologies are described in further subsections.IEM is mainly used to analyze the criteria and to calculate the weights of criteria in MCDM problems. Steps of IEM are as follows (Step1: Normalize the criteria values using equations Where, Xij′ is normalized value and Xij is the original value.Step 2: Calculate the entropy of each criterion.The entropy of each criterion can be calculated using equation m is the number of the object under each criterion.Step 3: Calculate the redundancy of entropy of each criteria using equation Step 4: Final step is to calculate weight of criteria using equation Step1: Normalize the decision matrix (1) using equations Xij′ is normalized performance value of ith alternative with respect to jth criteria.Xj+ is the maximum value of Xij for criteria j.Xj− is the minimum value of Xij for criteria j.Step 2: Assign weights to each criterion.Step 3: Calculate the performance score of each alternative.In this step of the SAW method, the normalized value of all criteria are multiplied with their criteria weight and added for each alternative. The performance score for each alternative can be calculated using equation Yi is the performance score of ith alternative with respect to all criteria.The ranking of alternatives is given based on values ofYi. The alternative with the highest Yi value is given as ranked first.Step1: Normalize the decision matrix (1) using equation Xij′ is normalized performance value of ith alternative with respect to jth criteria.Step 2: Assign weights to each criterion.Step 3: Calculate the performance score of each alternative.In this step of the MOORA method, the normalized value of all beneficial or maximizing criteria are added, and non-beneficial or minimizing criteria are subtracted for each alternative. The performance score for each alternative can be calculated using equation g is the number of beneficial or maximizing criteria, and (n-g) is the number of non-beneficial or minimizing criteria.Yi is the performance score of ith alternative with respect to all criteria.The ranking of alternatives is given based on values ofYi. The alternative with the highest Yi value is given as ranked first.Step1: Normalize the decision matrix (1) using equation Xij′ is normalized performance value of ith alternative with respect to jth criteria.Xj+ is the maximum value of Xij for criteria j.Xj− is the minimum value of Xij for criteria j.Step 2: Assign weights to each criterion.Step 3: Next step is to develop a weighted normalized decision matrix using equation D=[D11D12…D1nD21D22…D2n⋮⋮⋱⋮Dm1Dm2⋯Dmn]Where,Dij=Xij′×WjStep 4: Next step is to identify the ideal solutions of TOPSIS. I+ represents positive Ideal Solution (PIS), and Negative Ideal Solution (NIS) is represented by I−. PIS and NIS can be calculated using equation Ij+=(maxDi1, maxDi2,maxDi3…maxDin)(1≤i≤m)Ij−=(minDi1,minDi2,minDi3…minDin)(1≤i≤m)Step 5: Calculate the distance of all alternatives with PIS and NIS using equation Step 5: Calculate the closeness rating of all alternatives with respect to PIS. The closeness rating of alternatives can be calculated using equation Step 6: The final stage of TOPSIS is assigning a rank to alternatives. The ranking of alternatives is based on closeness value. The alternative with the highest closeness value is given as ranked first.Step 1: Calculation of best and worst values of all criteria using equation Where f∗j and f−j are the PIS and NIS for criteria j.Step 2: Calculation of utility value (Si) and regret value (Ri)The utility value can be calculated using equation Regret value can be calculated using equation Step 3: Calculation for VIKOR index value (Qi) using equation Qi=vj(Si−S∗)(S−−S∗)+(1−vj)(Ri−R∗)(R−−R∗)S∗=min(Si),S−=max(Si),R∗=min(Ri),andR−=max(Ri)Step 4: The final stage of VIKOR is assigning a rank to alternatives. Ranking of alternatives is based on VIKOR index value (Qi). The alternative with the lowest Qi value is given as ranked first.There are various reasons for selecting SAW, MOORA, TOPSIS, and VIKOR method over other MCDM methods. discussed that for a particular problem, an MCDM method could not be considered at the start of a decision-making process. The first decision-maker should understand the problem by considering alternatives, varied outcomes, and conflicting solutions. Further, presented a review of the material selection problem and found that TOPSIS is the most suitable method for the material selection problem. Further, SAW and MOORA are the most general and straightforward method used for material selection problem (). Similarly, VIKOR is an important MCDM method that provides compromising solutions to decision-making problems (). So, these MCDM methods are found to be very useful, reliable, and widely used in decision making problem. In this regard, this work uses SAW, MOORA, TOPSIS, and VIKOR methods for the sustainable material selection of AM materials.In this section, we illustrate real case studies on sustainable material selection for different AM technologies. The flow of the study is presented in . Four MCDM techniques have been used to analyze and compare AM materials, namely SAW, MOORA, TOPSIS, and VIKOR. Also, the rank reversal problem associated with MCDM applications is discussed in material selection studies. This study presents material selection for 3 a.m. technologies, namely FDM, SLA, and SLS. The mentioned 3 a.m. technologies are widely used in various applications (). Three case studies have been demonstrated in further sub-sections.This case study presents sustainable material selection for FDM based AM technology. For FDM technology, 15 critical criteria considered for sustainable material selection are as follows:Among these 15 criteria, Cost of material, GWP, and Energy consumption are the non-beneficial criteria, and the remaining all are beneficial criteria.Also, the six most widely used FDM printing materials are considered for analysis. The considered materials are Acrylonitrile Butadiene Styrene (ABS), Poly Lactic Acid (PLA), Polycarbonate (PC), Acrylonitrile Styrene Acrylate (ASA), Synthetic Polyamide (Nylon), Thermoplastic Polyurethane Elastomer (TPU Elastomer). The materials data are presented in . The weights of criteria are calculated using the IEM method and are as follows:wa = 0.037, wb= 0.046, wc=0.283, wd=0.037, we=0.061, wf=0.058, wg = 0.054, wh=0.05, wi = 0.083, wj = 0.051, wk = 0.045, wl = 0.056, wm = 0.054, wn = 0.039, wo=0.045.First, this case study is solved by the SAW method. The ranking of materials of FDM using the SAW method is generated as 2-1-6-4-3-5. Material 2 (PLA) is the best option, whereas material 5 (nylon) is the worst option for FDM printers. To analyze rank reversal in the SAW method, the worst material (material 5) is removed from the study. Again, the new ranking of material using the SAW method is 2-1-6-4-3. Therefore, it can be said that the SAW method is not having a rank reversal problem for this case study.Now, this case study is solved by the MOORA method. The ranking of materials is generated as 6-2-3-1-4-5. Material 6 (TPU Elastomer) is the best option, whereas material 5 (Nylon) is the worst option. To analyze rank reversal in the MOORA method, the worst material (material 5) is removed from the study. Again, the new ranking of material using the MOORA method is 6-2-3-1-4. Therefore, it can be said that the MOORA method is not having a rank reversal problem for this case study.Similarly, by using the TOPSIS method, the rank is generated as 6-3-5-2-4-1. Material 6 (TPU Elastomer) is the best option, whereas material 1 (ABS) is the worst option for FDM printers. To analyze rank reversal in the TOPSIS method, the worst material (material 1) is removed from the study. Again, the new ranking of material using the SAW method is 6-3-5-2-4. Therefore, it can be said that the TOPSIS method is not having a rank reversal problem for this case study.Similarly, by using the VIKOR method, the rank is generated as 6-2-3-1-4-5. Material 6 (TPU Elastomer) is the best option, whereas material 5 (Nylon) is the worst option for FDM printers. To analyze rank reversal in the VIKOR method, the worst material (material 5) is removed from the study. Again, the new ranking of material using the VIKOR method is 6-2-3-1-4. Therefore, it can be said that the VIKOR method is not having a rank reversal problem for this case study. compares the ranking of FDM materials using different MCDM methods.This case study presents sustainable material selection for SLA based AM technology. For SLA printer, ten critical criteria considered for sustainable material selection are as follows:Also, the five most widely used SLA printing materials are considered for analysis. The considered materials are Accura Polypropylene (Accura PP), Accura Acrylonitrile Butadiene Styrene (Accura ABS), Accura High Temperature (Accura 48 HTR), Accura High-Performance Composite (Accura HPC), Accura polycarbonate (Accura PC 60). The materials data are presented in . The weights of criteria are calculated using the IEM method and are as follows:wa = 0.092, wb= 0.083, wc=0.142, wd=0.153, we=0.059, wf=0.151, wg = 0.137, wh=0.043, wi = 0.097, wj = 0.043.First, the SAW method is used to solve this case study. The ranking of materials of SLA using the SAW method is generated as 4-3-2-1-5. It means material 4 (Accura HPC) is the best option, whereas material 5 (Accura PC 60) is the worst option for SLA printers. To analyze rank reversal in the SAW method, the worst material (material 5) is removed from the study. Again, the new ranking of material using the SAW method is 4-3-2-1. Therefore, it can be said that the SAW method did not generate the rank reversal problem for this case study.Now, this case study is solved by the MOORA method. The ranking of materials is generated as 4-3-2-1-5. It means material 4 (Accura HPC) is the best option, whereas material 5 (Accura PC 60) is the worst option for SLA printers. To analyze rank reversal in the MOORA method, the worst material (material 5) is removed from the study. Again, the new ranking of material using the MOORA method is 4-3-2-1. Therefore, it can be said that the MOORA method is not having a rank reversal problem for this case study.Similarly, by using the TOPSIS method, the rank is generated as 4-3-1-2-5. It means material 4 (Accura HPC) is the best option, whereas material 5 (Accura PC 60) is the worst option for SLA printers. To analyze rank reversal in the TOPSIS method, the worst material (material 5) is removed from the study. Again, the new ranking of material using the TOPSIS method is 4-3-1-2. Therefore, it can be said that the TOPSIS method is not having a rank reversal problem for this case study.Finally, by using the VIKOR method, the ranking of materials is generated as 4-3-2-1-5. It means material 4 (Accura HPC) is the best option, whereas material 5 (Accura PC 60) is the worst option for SLA printers. To analyze rank reversal in the VIKOR method, the worst material (material 5) is removed from the study. Again, the new ranking of material using the VIKOR method is 4-3-2-1. Therefore, it can be said that the VIKOR method is not having a rank reversal problem for this case study. compares the ranking of SLA materials using different MCDM methods.This case study presents sustainable material selection for SLS based AM technology. For SLS printer, seven critical criteria considered for sustainable material selection are as follows:Also, the six most widely used SLS printing materials are considered for analysis. The considered materials are Castform Polystyrene (Castform PS), Duraform Thermoplastic Elastomer (Duraform FLEX), Duraform Thermoplastic Polyurethane (Duraform TPU), Duraform Flame Retardent (Duraform FR1200), Duraform Polypropylene (Duraform EX), Duraform Glass Filled (Duraform GF). The materials data are presented in . The weights of criteria are calculated using the IEM method and are as follows:wa = 0.091, wb= 0.189, wc=0.098, wd=0.173, we=0.147, wf=0.163, wg = 0.139.First, this case study is solved by the SAW method. The ranking of materials of SLS using the SAW method is generated as 5-6-4-3-1-2. It means material 5 (Duraform EX) is the best option, whereas material 2 (Duraform FLEX) is the worst option for SLS printers. To analyze rank reversal in the SAW method, the worst material (material 2) is removed from the study. Again, the new ranking of material using the SAW method is 5-6-4-3-1. Therefore, it can be said that the SAW method is not having a rank reversal problem for this case study.Now, this case study is solved by the MOORA method. The ranking of materials is generated as 5-6-4-3-2-1. It means material 5 (Duraform EX) is the best option, whereas material 1 (Castform PS) is the worst option. To analyze rank reversal in the MOORA method, the worst material (material 1) is removed from the study. Again, the new ranking of material using the MOORA method is 6-5-4-3-2. It can be seen that the ranking of ‘material 5′ and ‘material 6′ got changes. Therefore, the MOORA method shows the rank reversal problem for this case study.Similarly, by using the TOPSIS method, the rank is generated as 3-5-6-4-2-1. Material 3 (Duraform TPU) is the best option, whereas material 1 (Castform PS) is the worst option for SLS printers. To analyze rank reversal in the TOPSIS method, the worst material (material 1) is removed from the study. Again, the new ranking of material using the TOPSIS method is 3-6-5-4-2. The ranking between ‘material 5′ and ‘material 6′ got changed. Therefore, it can be said that TOPSIS shows a rank reversal problem for this case study.Finally, by using the VIKOR method, the rank is generated as 5-4-6-3-1-2. It means material 5 (Duraform EX) is the best option, whereas material 2 (Duraform FLEX) is the worst option for SLS printers. To analyze rank reversal in the VIKOR method, the worst material (material 2) is removed from the study. Again, the new ranking of material using the VIKOR method is 5-4-6-3-1. Therefore, it can be said that the VIKOR method is not having a rank reversal problem for this case study. compares the ranking of SLS materials using different MCDM methods.In this work, a sustainable material selection of AM technologies has been made using different MCDM applications. Three a.m. technologies have been considered case studies in this work, namely, FDM, SLA, and SLS. IEM based MCDM method is used to calculate weights of all considered criteria. Further, four MCDM methods have been used for the sustainable selection of AM materials, namely, SAW, MOORA, TOPSIS, and VIKOR. Rank reversal problems associated with MCDM methods are also highlighted in the material selection stage. Based on the three case studies, the following observations have been summarized:Out of four MCDM methods, three methods shows ‘TPU Elastomer’ as the best material for FDM based AM technology.Accura HPC is identified as the best material for SLA based AM technology.Out of four MCDM methods, three methods shows ‘Duraform EX′ as the best material for SLS based AM technology.Rank reversal problem has occurred in MOORA and TOPSISSAW and VIKOR method did not show any rank reversal problem in all presented case studies.MOORA shows a rank reversal in one case study out of three.TOPSIS also shows a rank reversal in one case study out of three.The result shows that the SAW and VIKOR method did not show any rank reversal problem (). So, it is clear that the simplest MCDM method, i.e., the SAW method performs best under the rank reversal problem.The result shows that ‘TPU Elastomer’ is the best material for FDM based AM technology. In the literature, several materials have been used in FDM based AM technologies. However, some researchers have mentioned the practical application and advantages of using TPU Elastomer over other FDM materials (). TPU elastomer has the highest flexibility and rubber-like structure () with a high degree of elongation, which makes it advantageous over other FDM materials.For SLA based AM technology, Accura HPC is evaluated as the best material over other SLA materials. The studies by show that Accura HPC is a nanocomposite material used for different manufacturing applications. The essential properties of Accura HPC, which makes it advantageous over other SLA materials are, it has the highest accuracy and flexural strength () as compared to other considered SLA materials.For SLS based AM technology, Duraform EX is identified as the best material over other considered SLS material. Several literatures show the application of Duraform EX (). It has several benefits over other SLA materials, such as it provides the highest surface finish and has the highest tensile strength () as compared to other considered SLS materials.The result shows that the TOPSIS and MOORA method suffers from the rank reversal problem reported that TOPSIS shows a severe rank reversal problem. showed that the rank reversal problem associated with the TOPSIS method is due to the vector normalization method. present a new normalization method that avoids the rank reversal problem in TOPSIS.In the present study, the SAW and VIKOR methods did not show any rank reversal problem in the presented case studies. also reported that the SAW method is ideal and shows the least rank reversal problem. show the least rank reversal problem in the SAW method, whereas the VIKOR method shows the rank reversal problem in material selection studies.From the presented study, it can be seen that the selection of the MCDM method for material analysis is a challenging area. And so, it is recommended to use multiple MCDM techniques to analyze the same problem. Moreover, in some cases, different MCDM gives different results, and it is difficult to analyze the correctness of MCDM methods. So, it is recommended to compare the ranking of alternatives based on other MCDM methods through the Spearman rank correlation method. Equation is used for Spearman rank correlation analysisWhere, Diis the difference in ranking between alternatives obtain using two different MCDM methods, and m is the number of alternatives. shows the ranking of alternative materials for first, second, and third case studies using different MCDM methods. The spearman correlation among other MCDM methods can be analyzed using rank data from The rank correlation obtained between different MCDM methods using . It can be seen that the highest rank correlation is obtained between SAW and MOORA (RS= 1), SAW and VIKOR (RS= 1), and MOORA and VIKOR (RS= 1).The present study aims at selecting sustainable materials for additive manufacturing technologies. The material selection had been made considering 3 a.m. technologies, namely FDM, SLS, and SLA, using various MCDM techniques. Material selection is one of the critical factors for managers to take advantage of sustainability. Also, for any manufacturing organization, the cost incurred by materials will be half of the total operating cost. Thus it becomes difficult for key decision-makers or managers to select sustainable material for the manufacturing process.In this study, an attempt to select sustainable material would help managers to take benefits of sustainability and cleaner production. Improper material selection may impact the design of the product making it more vulnerable to failure. Thus the present study allows decision-makers to select material that enhances additively manufactured product design performance, durability, and output. Moreover, sustainable material selection plays a significant role in the entire design manufacturing process, which provides guaranteed product performance and reduce harmful environmental impacts throughout its life cycle. The present study can be beneficial for the researchers to understand the methodology for the sustainable material selection for additive manufacturing and design a better sustainable design assessment system.AM is gaining vital growth because it is a widely used technique for producing a complex structure with ease. More industries are adopting AM technologies to accelerate the product development phase with cost-effectiveness. Appropriate material selection is necessary for cleaner production and sustainable development. Sustainable material selection plays a vital role in minimizing resource consumption. Existing literature shows that there is a gap in reliable methodologies for AM material selection. Studies on AM material selection considering sustainability criteria are rare, and rank reversal problems in AM material selection using MCDM methods have not been reported.This paper focused on the sustainable material selection of AM technologies. Sustainable material selection has been made for 3 a.m. technologies, namely FDM, SLS, and SLA. The considered 3 a.m. technologies are widely used in a variety of applications. Four MCDM techniques have been used to analyze and compare AM materials, namely SAW, MOORA, TOPSIS, and VIKOR. Further, the rank reversal problem associated with considered MCDM methods is also included in this study. The main contribution of the study is the prioritization of materials for FDM, SLS, and SLA based AM technologies by considering both traditional and sustainable criteria. The study showed that ‘TPU Elastomer’, ‘Accura HPC′, and ‘Duraform EX′ are identified as the best materials for FDM, SLA, and SLS based AM technologies by considering both traditional and environmental criteria. This article helps industrial practitioners, decision-makers, and AM experts with the selection of the best AM materials in the product development stage to support cleaner production.The significant contributions of the study are:This work has filled the current literature gap; very few studies were available on AM material selection considering sustainability criteria, and rank reversal problem in AM material selection using MCDM methods has not been reported.This study provides a priority order of material for three important AM technologies: FDM, SLA, and SLS.This work considers four MCDM methods for prioritization of AM materials considering both traditional and sustainable criteria. Also, the rank reversal problem associated with MCDM applications is discussed.The study has certain limitations in terms of materials, selection criteria, and methodology used. The present study considers some important, widely used materials pertaining to AM technologies. Future studies can be performed by considering more AM materials. Three a.m. technologies, namely FDM, SLS, and SLA, have been considered in the present study. In the future, sustainable material selection studies can be done on other AM technologies. In the present study, the TOPSIS and MOORA methods show the problem of rank reversal. So, in the future other MCDM methods could be used to mitigate the rank reversal problem.Rohit Agrawal: Conceptualization, Methodology, Data curation, Writing – review & editing.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.Novel polyurethane produced from canola oil based poly(ether ester) polyols: Synthesis, characterization and properties► Novel bio-based poly(ether ester) polyols were synthesized from canola oil. ► The synthesized polyols had high functionality and low viscosity. ► The utilization of these polyols for polyurethanes production was demonstrated. ► Canola oil derived polyurethanes had high glass transition temperatures. ► These polyurethanes had improved hydrolytic stability and alkali resistance.Two novel bio-based poly(ether ester) polyols (Liprol™ 270 and Liprol™ 320) with high functionality and low viscosity were synthesized from canola oil. A simple, two-step reaction sequence of epoxidation followed by hydroxylation and transesterification with 1,3-propanediol or 1,2-propanediol was used resulting in a versatile, low cost process. The chemical structures of the low molecular weight compounds in the polyols produced were identified by liquid chromatography–mass spectrometry (LC–MS) while the distribution of oligomers was elucidated by size exclusion chromatography (SEC). The feasibility of utilizing these polyols for the production of polyurethanes (PUs) was demonstrated by reacting them with commercial petrochemical derived diisocyanate. The physical properties of the PUs prepared were characterized by FTIR, dynamic mechanical analysis (DMA), modulated differential scanning calorimetry (MDSC), and thermo gravimetric analysis (TGA). It was found that Liprol derived PUs had high glass transition temperatures, good hydrolytic stability and alkali resistance, and formed highly cross-linked networks. This work is the first that establishes the production of polyols and their corresponding PUs from vegetable oil starting materials whose glycerol backbone was removed explicitly during the polyol synthesis reaction.Polyurethanes (PUs) are used by a wide range of industries including the construction, automotive and consumers goods industries, and in many diverse applications ranging from medical devices to coatings, etc. Polyols normally used in PU synthesis are made from chemical intermediates derived from petroleum or natural gas. Recently, with the increasing emphasis on issues concerning waste disposal and depletion of non-renewable resources, the importance of using renewable resources in industrial processes has become very clear from a standpoint of sustainability. In the quest for sustainable chemistry, there are in particular, increasing demands for replacing or complementing the traditional petrochemical raw materials with renewable raw materials in the production of polymers In this work, bio-based poly(ether ester) polyols were synthesized through epoxidation followed by hydroxylation (esterification) reactions, starting from canola oil and other renewable content (i.e. 1,3-propanediol and 1,2-propanediol) and using a cheap and efficient procedure, and a strong acid catalyst. An important consideration in selecting 1,3-propanediol and 1,2-propanediol is that both of these diols derived from renewable resources are currently commercially available The canola oil (Safeway® or Canola Harvest® brand or equivalent) used in this study was purchased from a local grocery store. Unrefined crude castor oil was obtained from CasChem Company, USA. Hydrogen peroxide (35%), formic acid (85%), sodium sulfate anhydrous, sodium bicarbonate and 1,2-propanediol (propylene glycol, technical grade) were obtained from Univar, Canada. Ethyl acetate (ACS grade), sodium hydroxide (ACS grade), sodium chloride (ACS grade) and sulfuric acid (ACS grade) were obtained from Fisher Scientific, USA. 1,3-propanediol was obtained from DuPont Tate and Lyle, USA. Tritricosanoin (Mw = 1,101.88 g/mol), distearin (Mw = 625.00 g/mol) and monostearin (Mw = 358.56 g/mol) with purity ⩾99% were obtained from Nu-Chek Prep. Inc. (USA) and used as calibration standards for size-exclusion chromatography (SEC). The polymeric aromatic diphenylmethylene diisocyanate (pMDI, Mondur MRS) was sourced from Bayer Corporation, Pittsburgh, PA, USA. The NCO content of pMDI was 31.5 wt% and its functionality was 2.6 as provided by the supplier.Canola oil was epoxidized by performic acid generated in situ by reaction of hydrogen peroxide with formic acid, as described elsewhere A suitable amount of polyol and pMDI based on an NCO/OH ratio of 1.1/1.0, were weighed into a plastic container, mixed thoroughly for 5 min, poured in a plastic mold previously greased with silicone release agent, and placed in a vacuum oven at 50 °C for 10–20 min to remove bubbles. Air was then introduced to the oven to avoid the deformation of the sample under vacuum and the sample was cured for about 24 h at 50 °C then post-cured for 24 h at 100 °C to complete the reaction. The sample was then cooled to room temperature and demolded. Based on the different types of polyols used, the PUs prepared were coded as Liprol™ 270-MDI and Liprol™ 320-MDI, respectively.The structures of the main compounds in the polyols that are amenable to analysis by electrospray ionization mass spectrometry were identified by LC–MS analysis using normal phase chromatography. A 1200 Agilent high performance liquid chromatography (HPLC) system (Agilent Technologies; CA, USA) was coupled to an Applied Biosystems/MDS Sciex QSTAR Elite mass spectrometer with an electrospray ion source. The injected samples were dissolved in dichloromethane to concentrations of 0.1% (w/v). The samples were separated using an Ascentis silica column (15 × 0.21 cm, 3 μm) and using a binary gradient where mobile phase A was composed of hexane and mobile phase B was isopropanol. The gradient program was as follows: 0.1 min, 2% B; 0.1–20 min, 18% B; 20–25 min: 40% B; 25.1 min, 2% B. The re-equilibrium time was 6 min. The injection volume was 2 μl and flow rate was 200 μl/min. 40 mM ammonium acetate in methanol/isopropanol (3:1, v:v) was added post-column using an isocratic Agilent 1100 pump (Agilent Technologies; CA, USA) at a flow rate of 20 μl/min.MS analysis of the analytes was performed using positive electrospray ionization. Analyst QS 2.0 software was used for data acquisition and analysis. Nitrogen was used as curtain gas, nebulizing gas, and drying gas. The mass range recorded was from m/z 50–1300. The other instrumental conditions were as follows: ionspray voltage 5500 V; curtain gas setting 25; gas 1 setting 25 and gas 2 setting 55; declustering potential (DP), 80 V; focusing potential (FP), 300; second declustering potential (DP2), 15 V; and ion source temperature: 400 °C.The hydroxyl numbers of the polyols were determined according to ASTM D1957-86 and their acid values were determined according to the ASTM D4662-98. The average values and standard deviations of triplicate measurements are reported in . The viscosity of the polyols was measured in shearing mode with the TA advanced rheometer AR 2000 (TA Instruments, DE, USA) using a constant shearing rate of 51.6 s−1 at 25 °C. The viscosity results are listed in The molecular weight distributions of the epoxides and polyols were determined by SEC. The chromatograms were acquired using an isocratic Agilent 1100 pump (Agilent Technologies; CA, USA) equipped with an evaporative light scattering detector (Alltech ELSD 2000, Mandel Scientific Company Inc, Canada). A gel permeation chromatography (GPC) column (300 × 7.8 mm i.d.) with particle size of 5 μm (Styragel HR1, Waters Corporation, USA) was used under the following conditions: tetrahydrofuran as the mobile phase; flow rate of 1 mL/min; sample concentrations of 0.5% (w/v) and injection volumes of 10 μL. Lipids standards with known molecular weight were used to generate a calibration curve.The FTIR spectra were recorded on a Nicolet Magna 750 FTIR (Thermo Nicolet, WI, USA), equipped with an MCT-A detector and a Nicolet Nic-Plan IR microscope by ATR. The spectra were recorded in the range 650–4000 cm−1 with a nominal resolution of 4 cm−1. A background spectrum was first collected before each absorbance spectrum. A total of 128 interferograms were summed before Fourier transformation using the Nicolet Omnic software. To record the polyurethane spectra, a tiny piece of solid specimen was cut off from the bulk sample and placed on the top of the ATR crystal, whereas for polyols, a tiny drop of liquid specimen was placed on the sample holder directly.The gel time of the polyurethane was measured using an AR2000 Advanced Rheometer equipped with the Environmental Test Chamber (ETC). Due to the thermosetting nature of the material, 25 mm disposable plates were used as the test geometry. Isothermal time sweeps were run at a constant temperature of 50 °C to investigate the storage modulus and loss modulus change. The point at which the two curves intersect is typically taken as the gel point of the system and is the point at which the system begins cross-linking ASTM D543 was followed to measure swelling ratio of PUs by immersing them in toluene at 23 °C. Specimens were taken out and both surfaces were dried with paper before weighting every 24 h until constant weight. The swelling ratio was calculated from the difference in equilibrium weights of the swollen and dry sample.ASTM D570 was followed to measure water absorption of PUs by immersing them in water at 23 °C for 24 h. Specimens were taken out and both surfaces were dried with paper before weighting every 24 h until constant weight. Water absorption was calculated from the difference in equilibrium weights of the swollen and dry sample.Dynamic mechanical analysis (DMA) measurements were carried out on a DMA Q800 (TA Instruments, DE, USA), equipped with a liquid-nitrogen cooling apparatus, in the single cantilever mode with a constant heating rate of 2 °C/min from −40 to +180 °C. The size of the samples was 18 × 7 × 2 mm. The measurements were performed under dry nitrogen gas with 2 L/min flow following ASTM E1640-99 standard at a fixed frequency of 1 Hz and a fixed oscillation displacement of 0.015 mm.Modulated differential scanning calorimetry (MDSC) measurements were carried out on a DSC Q100 (TA Instruments, DE, USA), equipped with a refrigerated cooling system. The samples were heated at a rate of 10 °C/min from 25 to 160 °C to erase thermal history, then cooled down to −20 °C at a cooling rate of 5 °C/min. MDSC measurements were performed with a modulation amplitude of 1 °C/min and a modulation period of 60 s at a heating rate of 2 °C/min to 200 °C. The second heating stage was selected for the analysis of heating data. All the DSC measurements were performed following the ASTM E1356-03 standard procedure under a dry nitrogen gas atmosphere.Thermo gravimetric analysis (TGA) was carried out on a TGA Q50 (TA Instruments, DE, USA) following the ASTM D3850-94 standard. The sample was ground to a powder after chilling with liquid nitrogen, and approximately 10 mg of the specimen was loaded in the open platinum pan. The samples were heated from 25 to 600 °C under dry nitrogen with 100 mL/min purging flow at constant heating rates of 10 °C/min.Mechanical properties were tested using an Instron (MA, USA) tensile testing machine (model 4202) equipped with a 500 Kgf load cell and activated grips that prevented slippage of the sample before break. Specimens were cut out from the PU sheets using an ASTM D638 Type V cutter. For hydrolytic stability test, the cut specimens were fully immersed into water at 80 °C for 7 days, whereas for alkali resistance measurement, the specimens were submerged in 3.3% NaOH solution at 80 °C for 7 days. All the samples were dried the tensile test was performed. The measurements were carried out at room temperature with cross-head speed of 100 mm/min, as suggested by the above-mentioned ASTM standard. The data presented are an average of five different measurements. The reported errors are the associated standard deviations.ECO was synthesized using in situ generated performic acid (formic acid reacting with hydrogen peroxide) in the reaction medium. The performic acid adds oxygen to the double bonds of the fatty acid components of the oil to yield an epoxide group and thereby regenerating formic acid for the further reaction. Therefore, a low amount of formic acid is required which also reduces the production of di-hydroxy and hydroxy carboxylate byproducts formed due to an acid catalyzed ring-opening reaction. This conversion of the double bonds into the epoxides was monitored and quantified by LC–MS as described elsewhere C double bonds were converted into epoxides, based on uncorrected peak areas for unsaturated triglycerides and their epoxide products. ECO was then further reacted with diols in the present of sulphuric acid as a catalyst through acid catalyzed ring-opening hydroxylation of the epoxide groups and transesterification of the glycerides to produce polyols. The resultant polyols were characterized by LC–MS analysis, as shown in (a) and (b). This indicates that the molecular weight of the main component in these polyols is at m/z 433, consistent with the structures proposed in . This is much lower than the molecular weight (around 1000) of the main component of the polyols prepared when tetrafluoroboric acid was used as the catalyst ). In addition, these reactions also result in the addition of extra hydroxyl groups (). As a result, the hydroxyl number of such polyols is about 270 and 320 mg KOH/g, which is higher than the traditional vegetable oil-derived polyols produced via the epoxidation reaction (around 200 mg KOH/g) However, it is known that during the ring opening reaction some of the newly formed hydroxyl groups react with existing epoxy groups on other molecules resulting in oligomerization of the polyol (i.e. the formation of dimers, trimers, tetramers, and higher order oligomers) . By comparing the two chromatograms, it was found that the amount of multiple oligomers of Liprol 320 polyol opened by 1,2-propanediol was considerably less than that of Liprol 270 polyol opened by 1,3-propanediol. This is because the polyols produced with 1,2-propanediol have one secondary hydroxyl group which is significantly less reactive compared to a primary hydroxyl group. Hence, Liprol 320 polyols form oligomers less readily than Liprol 270 polyol, and in turn, a lower percentage of the available hydroxyl groups in Liprol 320 are consumed in forming oligomers. As a result, the hydroxyl value of Liprol 320 polyol is higher than that of Liprol 270 polyol formed under similar reaction conditions, as listed in . It was also expected that the viscosity of Liprol 320 polyol should be high due to its high hydroxyl value. However, the viscosity of Liprol 320 was found to be very close to that of Liprol 270 polyol, as shown in . Again, this can be explained by the low amount of oligomerization in Liprol 320 polyol, the predominance of lower molecular weight compounds resulting in lower viscosity. The high hydroxyl number as along with the low viscosity of such polyols will be beneficial in the preparation of polyurethane materials.The thermal properties of Liprol 270 and Liprol 320 polyols were investigated by MDSC measurements (data not shown). Unlike most of the current commercial available bio-based polyols The presence of free functional hydroxyl groups in Liprol 270 and Liprol 320 polyols and the expected structure of the PUs were confirmed qualitatively by FTIR spectroscopy as shown in . For both polyols, a strong stretching band at 3440 cm−1 (O–H group), a stretching band at 1740 cm−1 (CO group), an antisymmetrical stretching band at 1180 cm−1 (C–O–C group) and a stretching band at 1100 cm−1 (secondary O–H group) are present in both FTIR spectra ((a) and (b)). After the polyols are cross-linked with pMDI, the characteristic urethane N–H stretching bands at 3340 cm−1 are evident. In addition, the characteristic broadness of the CO vibration band at 1740 cm−1, attributed to the hydrogen bonding between CO groups and N–H groups, is observed. These changes indicate the formation of urethane linkages in both PU samples ((c) and (d)). Furthermore, the presence of an –NO band centered at 2270 cm−1 indicates that both PU samples still contain unreacted –NO groups. However, a 10% excess of diisocyanate was deliberately used in both PU preparations in order to ensure complete conversion of polyols to urethanes, given the occurrence of the unavoidable isocyanate-consuming side reactions such as the formation of allophanates, ureas or biurets. For the same NCO/OH molar ratio, the relative intensity of the –NO band was higher in Liprol 320-MDI PU than in Liprol 270-MDI PU sample. In addition, there was a shoulder at even higher wavenumbers (3400 cm−1) around N-H vibration region for Liprol 320-MDI PU, which might be attributed to unreacted –OH groups. These clear differences, even if precise quantitative analyses of the FTIR results are lacking, show that both –OH and –NCO amounts left after the reaction was higher in the case of Liprol 320-MDI PU. They are evidence of the strong effect of the steric hindrance of secondary hydroxyl group in cross-linking, resulting in less complete reactions with isocyanates than is the case with Liprol 270 polyol. It can be seen in that for the monomer structures, Liprol 320 contains three secondary hydroxyl groups whereas Liprol 270 contains only one. Of course, with the addition of a suitable catalyst to the polyurethane preparation, as well as the adjustment of the NCO/OH molar ratio, full consumption of the NCO groups during curing of Liprol 320 polyol could likely be achieved, but this is not the purpose of the present study.The gelation time for both Liprol 270-MDI and Liprol 320-MDI polyurethane was measured by monitoring the evolution of storage modulus (G′) and loss modulus (G″) with time at 50 °C. The point at which the two curves intersect is taken as the gel point of the system and is the point at which the system begins cross-linking. Usually, the magnitude of the modulus at the gel point is several thousand Pascal’s. The gel time is 20 min for Liprol 270-MDI and 100 min for Liprol 320-MDI PU, indicating that the former sample reacts faster than the latter one. This was attributed to the difference between the polyols’ structure as illustrated in . Thus, Liprol 270 polyol contains both primary and secondary hydroxyl groups, whereas Liprol 320 polyol contain only secondary functional hydroxyl groups and it is known that isocyanate generally reacts faster with primary hydroxyl groups than with secondary hydroxyl groups Sol fractions, amounting to <0.5% for both Liprol 270-MDI and Liprol 320-MDI PU, were obtained by multiple extractions with toluene. Hence, the extraction experiments showed clearly that the major fraction in both networks is the gel fraction. compares the SEC traces for the sol fractions of Liprol 270-MDI and Liprol 320-MDI PU with that of the starting Liprol 270 polyol. It can be seen that the molecular weight range of the three traces is similar, spanning from approximately 102 to greater than 104 Daltons. Thus, when comparing the PU SEC traces with those of the pure polyol, it was found that no peaks of higher molecular weight than those of the polyols were observed. This suggests that Liprol polyols have a very low mono-hydroxyl content, resulting in a low abundance of the sol fraction, at <0.5% of the weight of the PU.An attempt to evaluate the cross-linking density values through the swelling experiment was made using Flory–Rehner theory. It involves the determination of the polymer–solvent interaction parameter and the solubility parameter of the network; see Eq. . According to the Flory–Rehner theory for equilibrium swollen networks, the average molecular weight of the portion of the chain between cross-links, Mc and cross-linking density, νe can be calculated:1/νe=Mc/ρ2=[-V1(Aϕ21/3-2Bϕ2/f)][ln(1-ϕ2)+ϕ2+χ12ϕ22]where ρ2 is the density of the dry polymer, V1 is the molar volume of the solvent, ϕ2 is the volume fraction of the polymer in the swollen sample, f is the functionality of the network branch points, and χ12 is the polymer–solvent interaction parameter. A and B within the junction-fluctuation theory of Flory (JFF theory) The polymer–solvent interaction parameter, χ12, was calculated from the solubility parameters of the solvent, δ1, and the polymer network, δ2.The solubility parameter of toluene, δ1 |
= 18.2 (J/cm3)1/2, was obtained from the Polymer Handbook The swelling of Liprol 270-MDI PU in toluene, measured at room temperature is 32%, whereas that of Liprol 320-MDI PU is 35%. Surprisingly, Mc calculated from Eq is only around 200 g/mol for both PU networks when applying the affine model. By comparison with conventional PU networks, these values are unrealistically low. This could be due to the assumptions inherent in the network model, as well as to the irregular chemical structures that both polyols possess. In an affine network, the cross-links are fixed and consequently their positions deform affinely with macroscopic strain. In other words, the junction points are pinned to an elastic background and do not fluctuate during deformation. Consequently, this model neglects the defects that normally occur in a real network, such as dangling chain ends and temporary or permanent chain entanglements. Thus, deviations from the ideal molecular structure could result in an unrealistic value of Mc. In addition, it is of note that some of the reactive hydroxyl groups in both Liprol polyols are in the middle of the chain. These hydroxyl groups may not all be completely reacted with isocyanate, due to steric hindrance effects. A consequence of this would likely be the formation of networks with a large distribution of molecular weights between cross-links. In the case of a polyol monomer originating from linolenic acid, the most unsaturated fatty acid present in canola oil, the hydroxyl groups could be located at C9, C10, C12, C13, C15 and C16 positions on the fatty acyl chain. Therefore, the possibility of several distinct Mc values exists. For instance, Mc could be as low as 26 g/mol, in the event that two adjacent hydroxyls in the same chain react with isocyanate. In another example, an Mc value of 292 g/mol could occur if the primary hydroxyl groups (in the case of Liprol 270-MDI PU) at C9 from each of two fatty acyl chains were reacted to isocyanate. Hence, due to the irregular network, the possible number of Mc values is large, so the calculated value may not be accurate. A similar result was reported by Ryan et al. The Tg for both PUs was determined from the temperature dependence of tan δ (the temperature at the maximum tan δ) in DMA measurements (see ). Tg of Liprol 320-MDI PU is 100 °C, whereas that of Liprol 270-MDI PU is 86 °C. Both values are higher than the Tg values generally reported for PUs made with other vegetable oil polyols, such as those made by the hydroformylation of soybean oil (48 °C) or by the ozonolysis of canola oil (41 °C) ), which showed the same trend: the Tg of Liprol 320-MDI PU is about 15 °C higher than that of Liprol 270-MDI PU.The glass transition of a polymer network is affected by cross-linking density as well as chemical structure. The increase of Tg (∼15 °C) indicated that the flexibility of the polymer chains was reduced for Liprol 320-MDI PU networks shifting the rubbery state to higher temperatures. This could be explained by the higher hydroxyl value of Liprol 320 polyol (), which yields a more highly cross-linked network upon reaction with isocyanate. In addition, the lower oligomer content of Liprol 320 would lead to an increase in the rigidity of the resulting PU and hence, a polymer network with a higher value of Tg. The highly cross-linked network of Liprol 320-MDI PU also gives rise to higher Young’s modulus than Liprol 270-MDI PU, as listed in Plots from TGA and its derivative (DTGA) for Liprol 270-MDI and Liprol 320-MDI PU plastic sheets are shown in (a) and (b), respectively. For both samples, decomposition started at approximately 200 °C and ended at 500 °C. DTGA curves revealed three main degradation processes with noticeable differences in the whole temperature range. For Liprol 320-MDI, the temperatures of 5% mass loss was observed at 273 °C and the fastest mass loss in the first stage was observed at 315 °C. In contrast, Liprol 270-MDI showed higher thermal stability at this stage, with its 5% mass loss and fastest mass loss at 290 and 350 °C, respectively. However, Liprol 320-MDI showed better thermal stability in the second step, with the observation of 50% mass loss at 390 °C versus at 370 °C for Liprol 270-MDI.The thermal stabilities of PUs are dependent on the reactants, additives and conditions in which they are used. It is known that the first stage of degradation is related to urethane bond decomposition , Liprol 270-MDI PU displayed a tensile strength, a Young’s modulus and an elongation at break of 61 ± 1, 1430 ± 8 MPa and 5.9 ± 0.7%, respectively. Liprol 320-MDI PU displayed a tensile strength, a Young’s modulus and an elongation at break of 67 ± 2, 1700 ± 10 MPa and 4.6 ± 0.4%, respectively. The results are compared with that of PU made from castor oil, a widely available natural vegetable oil polyol. In all of these experiments, the isocyanate selected, as well as the NCO/OH molar ratio, were kept constant. As expected, castor oil based PU which has an intact glycerol backbone, displayed lower initial tensile strength (9.3 ± 0.3 MPa), Young’s modulus (8.3 ± 0.2 MPa) and longer elongation at break (62.3 ± 0.6%), compared to both Liprol PU samples. In addition, the tensile strengths of both Liprol PU were of higher values but lower elongation at break than of rhodium catalyzed hydroformylated soybean oil based PUs (38 MPa of tensile strength, 17% of elongation at break), and epoxidized soybean oil based PUs (46 MPa of tensile strength, 7% of elongation at break) Vegetable oils have three ester bonds that are susceptible to hydrolysis, particularly under alkali conditions. Most of the commercially produced vegetable oil derived polyols retain these ester bonds and would therefore, also be susceptible to hydrolysis. In addition, in the corresponding PUs, urethane bonds may hydrolyze when exposed to high humidity to give an amine and carbon dioxide in which the chemical stability of PU made using the test Liprol polyols from this study are compared with that of PU made from castor oil. As expected, castor oil based PU which has an intact glycerol backbone, displayed lower initial tensile strength and poor retention of strength and elongation on exposure to hot water and alkali, compared to both Liprol PU samples. In addition, the water absorption of castor oil PU was about 3% vs. 0.5% for the two Liprols. This is because diffusion of water through polymers is faster in the rubbery state castor oil based PUs, than in the glassy state Liprol based PUs. Higher water absorption leads to the observed greater decrease in strength and elongation in castor oil based PUs. This deficiency was partially overcome by removing the glycerol backbone from the polyol molecules and introducing ether groups during the ring opening reaction. As a result, both Liprol 270-MDI and Liprol 320-MDI PUs displayed an improved retention of strength and elongation after exposure to hot water and alkali solution at 80 °C for 7 days (). Overall, the results indicate that both Liprol polyols can be used in making tough, hard and rigid polyurethanes.Bio-based poly(ether ester) polyols (Liprol 270 and Liprol 320) with high hydroxyl numbers and low viscosity were synthesized from canola oil by epoxidation followed by acid catalyzed ring opening and transesterification reactions with 1,3-propanediol or 1,2-propanediol. The optimized procedure Experimental study on the seismic performance of steel–concrete beam–column connections for prefabricated concrete framesA novel type of prefabricated steel–concrete beam–column connection with different configurations for moment-resisting frames was developed for better constructability. Five beam–column connections, four prefabricated steel–concrete specimens, and one reference monolithic joint were tested under reversed cyclic load–displacement controlled conditions. The main variables were the steel form in beams and columns, fabrication method, and use of steel fiber reinforced concrete (SFRC) in the joint and connection parts. The cracking patterns and load–displacement hysteresis curves were recorded during the test. The efficiency of the developed connection was compared based on bearing capacity, energy dissipation, ductility, and stiffness. The results revealed that the prefabricated specimens with welded reinforcement connection exhibited flexural failure at the prefabricated beam, whereas the specimens with bolted end plates or weld-bolted H-steel beam connecting method failed through joint shear failure. The proposed prefabricated H-steel concrete connection with bolted end plates and SFRC had higher strengths and stiffnesses, more stable load–displacement cycles, and better energy dissipation capabilities. Moreover, the concrete spalling in the joint was adequately controlled, and shear deformation was also reduced. The H-steel beam connector in the proposed connection could effectively transfer loads under earthquakes.Prefabricated concrete members that are created in a factory exhibit better quality control and higher production efficiency than cast-in-place ones []. After being prefabricated, the members are transported to a construction site and fabricated into monolithic structures using different connection methods, resulting in a shorter construction period and better economic profits []. Thus, prefabricated structures have predictable significance in promoting the development of building industrialization and have been widely used in many countries []. The connection has an important function in transferring loads between one prefabricated component and another and is considered the vital part. The type of beam–column connection significantly influences the strength, stability, integrity, and constructability of a prefabricated concrete structure. If the prefabricated beam–column connections are reliable and stable, the fabricated concrete frame can achieve considerable seismic behavior, which has been demonstrated by many research studies. However, the behavior of prefabricated connections does not fully satisfy the requirements under earthquake action, resulting in beam–column connection failures []. Therefore, a reasonable and practical connection with adequate energy dissipation, stiffness, and strength has become a challenge for fabricated concrete moment-resisting frame structures.Currently, many studies have been conducted to evaluate the performance of different types of beam–column connections, including monolithic, welded, bolted, pretensioned, and hybrid joints []. Generally, the continuity of reinforcements between beams and columns is frequently achieved by anchoring or splicing steel bars, grouting sleeves, and cast-in-place concrete [] designed connections with U-shaped beam shells and experimentally revealed good deformation capacities but decreased hysteretic energy dissipation. Yan et al. [] experimented on five beam–column connections using grout sleeves under low-reversed cyclic loading. They reported that the specimens using grout sleeves had a slightly lower energy dissipation capacity than the monolithic connection. Moreover, the use of materials such as steel strands, steel angles, externally embedded rods, and shaped steel was proposed to connect the prefabricated members []. Moreover, experimental studies were performed and the results demonstrated that prefabricated specimens with adequate seismic capacity behave as monolithic connections. In addition, the connection measures were confirmed to be effective and reliable. However, anchoring or splicing reinforcements, and cast-in-place concrete might result in construction difficulty during the on-site assembly process. Additionally, the use of high-performance fiber-reinforced materials, instead of normal concrete, in the joint region is an attractive solution to delay crack propagation []. Recently, high-performance fiber-reinforced materials have been used in prefabricated beam–column connections []. These studies indicated that the deformation performance of connections improved.When a prefabricated beam–column connection is connected by a steel connector, welded or bolted connections are considered feasible methods [] studied the effect and seismic performance of reinforced concrete (RC) slabs, weld connection, and bolt connection for a new precast steel RC beam–column joint with steel beam brackets. They observed that the joint with a slab exhibited better seismic performance, but peak strength decreased owing to the bolt slip. Bahramia et al. analyzed the seismic performance of two new beams to precast column connections connected by welding or bolting with a corbel using nonlinear finite element analysis []. The analytical results revealed that the prefabricated connections exhibited a similar seismic behavior to a corresponding monolithic connection. Ghayeb et al. [] proposed a new type of hybrid beam–column connection and experimentally proved the steel angles significantly improved the seismic performance of precast concrete connections.Steel–RC connections make fabricated concrete frame structures a promising option, but studies of the seismic performance of connections with steel connectors are limited. Their fabrication and post-poured concrete in joint regions have been studied. However, the performance of specimens with steel connections outside the joint region that are reliable and compatible for construction is on high demand. Thus, this study developed a new hybrid prefabricated concrete beam–column connection characterized by H-steel beams, end plates, and steel fiber reinforced concrete (SFRC), which have advantages of easy construction, continuity of column longitudinal reinforcements, and improved seismic behavior. The continuity of the longitudinal reinforcements of the column may improve the integrity of beam–column connections. The H-steel beams and end plates used in the prefabricated beams and columns of the developed specimens have sufficient strength to ensure the continuity of the beam longitudinal reinforcements, and they can be easily assembled through bolting on site. Five specimens including monolithic and prefabricated connections were created and reverse cyclic loading was applied. The efficiency of the developed connection was evaluated in terms of failure mode, hysteretic curves, strength, stiffness, energy dissipation, strains, and shear deformation. The test results indicated that the proposed hybrid beam–column connections can be used in seismic zones.The configurations of the newly proposed prefabricated connection, which consisted of a prefabricated beam, prefabricated column, and connecting segment are shown in . The prefabricated beam and prefabricated column were connected using an H-steel beam, H-steel beam with end plates, or H-steel beam with web connecting plates. These steel connectors can reliably transfer stress from the beam ends to the column to elevate the strength and improve the constructability. Moreover, SFRC was poured into the joint core segment and the connecting segment to enhance the tensile strength.(d)). Four types of configurations used in the prefabricated beam were suggested: partly embedded H-steel beam with grooves inside the beam ((a)), partly embedded connecting plate and protruding longitudinal reinforcements of the beam ((c)), protruding longitudinal reinforcements of the beam ((b)), and partly embedded H-steel beam with a welded end plate ((d)). For the prefabricated column, two types of configurations were developed: an H-steel beam embedded partly in the prefabricated column ((a–c)) and an H-steel beam embedded partly and an end plate welded to the H-steel beam (The developed prefabricated beam–column connection employed steel connectors and welded/bolted connection methods used in steel structures to connect beams and columns that were fabricated in a factory for concrete moment-resisting frames, which have the advantages of rapid construction speed and high assembly efficiency. The connection position was located at a certain distance from the column face; thus, the plastic damage might be moved outward, and the damage of the joint could be avoided. The use of cantilevered H-steel beams through the column avoided the discontinuity of column longitudinal reinforcements and congestion of reinforcement bars in the joint area; thus, it improved the integrity of the joint and effectively transferred the load. The assembly process of the proposed beam–column connection was as follows. After the prefabricated column was installed on site, the prefabricated beams were lifted to the required position. Subsequently, the beam and column were connected through bolting or welding to form the H-steel beam concrete beam–column connections with variable configurations. Finally, the concrete was poured on site for the connecting segment.To understand the seismic performance of the proposed prefabricated beam–column connections visually and clearly, we designed one monolithic connection specimen (denoted as ZJ1) and four prefabricated connection specimens (ZHJ1, ZHJ2, ZHJ3, and ZHJ4) for comparative study. All connections in the test were designed as full-scale specimens based on a prototype moment-resisting frame with a story height of 2.8 m and a beam span length of 3.4 m. The reinforcement configuration of specimens conformed to the requirements of Chinese specifications GB 50011-2010 []. Moreover, to analyze the enhancement effect of different configurations on the proposed connections, we constructed the monolithic connection to initiate failure in the joint for comparison by increasing the interval of the transverse reinforcements. The sectional dimensions of the beam and columns in the test were 400 mm × 250 mm and 350 mm × 350 mm, respectively. The column height was 2800 mm and the beam length was 3550 mm.The dimensions and reinforcement details of each specimen are shown in . The main aim of this study was to compare the prefabricated connections with different connection configurations with the monolithic connection. Therefore, the same reinforcement details were used for the beams and columns of all specimens except for the connection configurations. Eight HRB600 bars with a diameter of 18 mm were placed in the beams as longitudinal bars, and 10 bars of the same grade with a diameter of 20 mm were arranged in the columns as the longitudinal bars through the joint area. The transverse reinforcements were HRB400, of which the intervals were 100 mm in beams and columns. The transverse reinforcement intervals were reduced to 55 and 50 mm for the beam and column ends, respectively, to prevent the premature damage of the beam and column ends from adversely affecting the test results. The yield strength standard value of the H-steel, end plate, connecting plate, and stiffener was Q235.The test variables were the connecting method, SFRC usage, steel skeleton in the beam, steel skeleton in the column, and fabrication method (). Normal concrete was poured into the prefabricated beams and columns of specimens ZJ1 and ZHJ1. For specimens ZHJ2, ZHJ3, and ZHJ4, SFRC was poured into the joint core segment and connecting segment, and normal concrete was poured into the other segments. Cantilevered H-steel beam with cross-sectional dimensions of 354 mm × 200 mm × 6 mm × 12 mm were embedded in the prefabricated columns. The lengths of the cantilever H-steel beams of ZHJ1, ZHJ2, ZHJ3, and ZHJ4 were 750, 950, 750, 710 mm.A 1.0% volume fraction of steel fiber with a diameter of 0.5 mm and length of 30 mm was used to provide resistance against shear stress []. The tensile strength of steel fiber was 1100 MPa, and the density was 7850 kg/m3. The proportion of normal concrete and SFRC is shown in . When the prefabricated beams and columns were poured, 150 mm cubic blocks were fabricated. After the curing period, the test blocks were tested under compression based on GB/T 50152-2012 [], the material properties of the steel bars and steel plates configured in the specimens were tested subjected to tensile tests. The test results are shown in The schematic and photograph of the test setup used in this test are depicted in , respectively. The bottom of the column was connected to the strong floor using a spherical hinge and the top of the column was connected using roller supports. The stability of the column during loading was ensured by lateral bracings at both ends of the column. All the constraints were designed to simulate the practical boundary conditions of the members. First, a constant axial load of 460 kN was applied at the top of the column using a hydraulic jack with a capacity of 1000 kN. The axial compressive ratio of the column was 0.15, which was equal to the ratio of the column axial compression force to the cross-sectional area and the concrete compressive strength. Second, the cyclic load was applied using actuators with a loading range from −500 to 500 kN and a displacement of 500 mm at the left and right beam ends. The left and right actuators applied the load in opposite directions., the loading history was divided into two stages according to JGJ/T101-2015 []: the load-controlled and displacement-controlled stages. Each loading cycle was repeated once at loads of 0.4Py, 0.8Py, and 1.0Py during the load-controlled stage before the specimen yielded, where Py is the yield load, which was obtained by observing the strains of the longitudinal bars in the beam. After the specimen yielded, displacement control was used. The displacement amplitudes of each loading cycle were integral multiples of the yield displacement. Each loading cycle was repeated three times. Finally, loading was stopped when the maximum load value at a certain loading cycle was less than 80% of the peak load. The loading rate was 1 mm/s.During the loading process, the joint shear deformation and rotation were measured using 14 linear variable differential transformers (LVDTs) (). Strain gauges were attached at the corresponding locations for measurement to understand the distribution of strain in the reinforcement, H-steel beam, and steel plate under cyclic loading (The crack patterns and failure modes of the monolithic and prefabricated specimens are shown in . The connections experienced four stages of cracking and failure: the appearance of flexural and diagonal cracks, yielding of reinforcements and steel plates, development of cracks and formation of the plastic hinge, and final failure.For the monolithic specimen ZJ1, four flexural cracks first appeared at the top and bottom of the beams near the column surface at a load of 50.7 kN. When the load increased to 90.8 kN, the first diagonal crack formed in the joint core. Moreover, flexural cracks propagated towards the beam axis. When the specimen yielded, the quantity and width of the cracks on the beam and in the joint continuously propagated, followed by several splitting cracks. As the displacement increased to 69.8 mm, the initial crushed concrete occurred at the joint region owing to a higher shear force. Finally, extensive concrete crushing and spalling caused the final shear failure of the joint owing to increased displacement.For prefabricated connections ZHJ1 and ZHJ4, the crack propagations were similar to those of the monolithic ZJ1 specimen at the initial loading stage. The initial flexural crack of ZHJ1 appeared at the right beam near the column face at a load of 60.5 kN. When the load increased to 90.4 kN, the initial flexural crack of ZHJ4 appeared at the beams away from the embedded H-steel on the beam. Meanwhile, diagonal shear cracks occurred in the joint core area. Compared with specimen ZJ1, fewer flexural cracks occurred on the beam of specimens ZHJ1 and ZHJ4 as the embedded H-steel enhanced the flexural resistance. However, the diagonal cracks rapidly propagated, followed by several splitting cracks resulting from the opening and closing of cracks caused by increased cyclic displacement. With further cyclic loading, concrete spalling occurred in the joint zone along with the diagonal directions and then was fully restrained by the H-steel, which resisted the joint shear force. Finally, both ZHJ1 and ZHJ4 failed through joint shear failure, and the longitudinal reinforcements in the prefabricated beams and columns did not yield. Additionally, there were few minor cracks in the connecting section of specimen ZHJ4 because of the slip caused by the fully bolted connection.Compared with specimens ZHJ1 and ZHJ4, similar crack patterns occurred in specimens ZHJ2 and ZHJ3 under initial cyclic loading. However, significantly more flexural cracks concentrated on the prefabricated beams without the strengthening of the H-steel after the displacement reached 69.5 mm. These cracks at the longitudinal reinforcement–H-steel interface were significantly wider than those at other locations. Subsequently, splitting cracks occurred in the prefabricated beam near the connecting segment, followed by the formation of plastic hinges. With increasing displacement, significant concrete crushing occurred in the plastic hinge region, accompanied by the fracturing of longitudinal reinforcements due to repeated tensile–compression buckling, resulting in the final bending failure of specimens ZHJ2 and ZHJ3.Monolithic specimen ZJ1 and prefabricated specimens ZHJ1 and ZHJ4 suffered from shear failure due to concrete crushing in the core of joints. However, ZHJ1 and ZHJ4 had less damaged concrete in the joint core area than ZJ1 did. This was primarily because of the embedded cantilevered H-steel beam in the columns, which resulted in enhanced shear resistance of the joints. Compared with ZJ1 and ZHJ1, the appearance of initial cracks in ZHJ4 delayed. Moreover, the diagonal cracks of connection ZHJ4 were significantly smaller in width than those of the monolithic connection ZJ1 and prefabricated connection ZHJ1 owing to the steel fibers restraining against the development of cracks. Thus, adding steel fibers in the joint region decreases the width and restrains the propagation of cracks. SFRC is necessary to control the cracks in the proposed connection core region. Therefore, specimen ZHJ4 experienced slight damage in the joint region, resulting from the combination of H-steel beams and steel fibers.The plastic hinges of ZHJ2 and ZHJ3 were located within a certain range around the connection on the beam. The main reason was that the longitudinal bars of ZHJ2 and ZHJ3 were welded to the cantilevered H-steel beam, which produced an abrupt change in stiffness at the connection, resulting in a higher stress of the longitudinal bars. Furthermore, crushed concrete was observed in the prefabricated beams of specimens ZHJ2 and ZHJ3, which was caused by longitudinal reinforcement fracture owing to the increased moment capacity. If the stirrup spacing of the steel–concrete transition section was decreased, the influence of shear force decreased and the specimens suffered a large deformation.The load–displacement curves are depicted in , which also shows the envelope lines of the specimens in blue. shows the comparison of skeleton curves for all connections. As shown in , the yield displacement was obtained using Park's method and defined as the intersection between the horizontal line at peak load and the line that passes through the origin and 75% of the peak load []. The ultimate displacement is equal to the load point in the post peak displacement stage when it corresponds to 80% of the peak load [In prefabricated connections ZHJ1–ZHJ4, the hysteretic loops were fuller, and the pinching phenomenon was less than that of the monolithic specimen. This was because the cantilever H-steel beam enhanced the elastic range, thereby dissipating more energy. Moreover, the average peak load was higher by over 30% than the monolithic connection ZJ1, indicating that the H-steel beam significantly increased the bearing capacity. However, the ultimate displacement was significantly lower than ZJ1 as the H-steel beam provided higher stiffness.Prefabricated connections ZHJ2 and ZHJ3 with welded reinforcement connections exhibited smaller hysteretic responses than specimens ZHJ1 and ZHJ4 with the bolted end plate connections. The pinching phenomenon was larger owing to the more severe damage to the plastic hinge on the prefabricated beam degrading the energy dissipation. The prefabricated beam types and cantilever H-steel beam length of specimens ZHJ2 and ZHJ3 were different, but their load–displacement hysteretic curves were essentially similar. After reaching the peak load, the two curves had a steep decrease in loading resistance caused by the fracturing of the longitudinal reinforcements. As the difference between ZHJ1 and ZHJ4 lay within whether the connection used end plates and SFRC, the bolted end plates and SFRC were important factors affecting the strength degradation, stiffness degradation, energy dissipation, and bearing capacity for this new type of connection. Among all the specimens, the ultimate displacement of the prefabricated specimen ZHJ4 was the largest. This increased maximum displacement was primarily because the SFRC and bolted end plates improved the concrete spalling and enhanced the deformation resistance capacity. For prefabricated connections, when H-steel beams were used in the precast column to connect the precast beam, the stress was transferred effectively from the beam ends to the joint, resulting in a fuller hysteretic response, regardless of steel skeleton in the beam and fabrication method.The ductility of a beam–column connection, reflecting the plastic deformation capacity without significant loss of strength after yielding, is a vital index of seismic performance. The ductility of the connection is frequently quantified using the ductility factor calculated as the ratio of the ultimate displacement to yield displacement. The ductility factors for all connections are listed in The average ductility factors for the monolithic connection and four prefabricated connections were 2.4, 2.1, 2.1, 2.0, and 2.4, respectively. According to ASCE/SEI 41-06 classification standards [The strength degradation ratio (SDR) is a vital indicator of assessing the seismic behavior of specimens under cyclic loading, and it is calculated using Equation , where Pfi and Psi are the strengths of the first and second loading cycles at the ith displacement level, respectively., specimens ZHJ2 and ZHJ3 with welded reinforcement connections exhibited the larger strength degradation ratio, followed by specimens ZHJ1 and ZHJ4 with the bolted end plate connections. The monolithic connection had the lowest SDR. Prefabricated specimens ZHJ2 and ZHJ3 exhibited a steep strength degradation at the final loading stage owing to the fracturing of the welded longitudinal reinforcements and severe crushing of concrete caused by the high stress at the connecting section. The strength degradation ratio curves of prefabricated specimens ZHJ1 and ZHJ4 were stable and had slight fluctuations. This could be attributed to the connection method between the cantilevered H-steel beam and anchored H-steel beam being more reliable. Additionally, the strength degradation of ZHJ4 was more stable owing to the pouring of SFRC, which could adequately restrain the crack development in the joint region. Moreover, the bolted end plates might have a positive effect on the strength degradation owing to the slight slippage caused by the fully bolted connection. To avoid the steep strength degradation, H-steel were required in the precast beam to connect with the precast column, regardless of SFRC usage and fabrication method.The strength degradation ratio of the monolithic connection and four prefabricated specimens was in the range of 0.8–1.0. The strength degradation of all specimens was less than 20%, which satisfied the requirements of ACI 374.1-05 []. The prefabricated specimens with H-steel connectors had less strength degradation owing to the H-steel having larger stiffnesses and bearing higher loads without significant strength loss under the reversed cyclic loading.A structure with sufficient stiffness can avoid excessive deformation and maintain stability under earthquake loads. Therefore, assessing the stiffness and stiffness degradation of the specimens is important to understanding the seismic performance of specimens. Stiffness degradation can be characterized by the variation in the scant stiffness during the loading process. The scant stiffness is defined as the peak load at the ith loading level by the corresponding displacement, calculated using Equation where + Pi and +Δi indicate the peak load and corresponding displacement at the ith loading level in the positive direction, respectively. Similarly, −Pi and −Δi are in the negative direction, respectively.). At each displacement level, the scant stiffness of the prefabricated specimens was greater than that of the monolithic specimen with the aid of the cantilever H-steel beam in increasing the bearing capacity. For the monolithic specimen, the yielding of the reinforcement bars and aggravation of the concrete cracks in the joint core severely affected the stiffness degradation. Similarly, the yielding of the H-steel web and damaged concrete in the joint core resulted in stiffness degradation of specimens ZHJ1 and ZHJ4. The stiffness degradation of specimens ZHJ2 and ZHJ3 was caused by the damaged concrete and fracturing of the longitudinal reinforcements at the connection segment at the beam, which should be considered to be strengthened at the steel–concrete transition section via decreasing the stirrup intervals.To better understand the trend of stiffness degradation, we define the stiffness degradation ratio as the ratio of the secant stiffness to the initial secant stiffness. shows the stiffness degradation ratio curves. The stiffness degradation ratios of the prefabricated connections ZHJ1–ZHJ4 were larger than that of the monolithic specimen after yielding, indicating the developed connecting methods alleviated stiffness degradation owing to the use of the H-steel beam, which had a larger elastic stiffness and can effectively transfer the load under earthquake actions.The inelastic deformation of the connection results in a large amount of energy dissipation. It reduces the energy transmission from a seismic action to other structural components to prevent structural collapse. Cumulative energy dissipation, which is frequently used to evaluate energy dissipation capacity, can be expressed by the sum of the areas enclosed by the load–displacement hysteretic loops., the cumulative energy dissipation of all specimens increased gradually owing to small concrete cracks before the displacement reached 40 mm. Subsequently, the cumulative energy dissipation increased rapidly due to the development of concrete cracks and the yielding of reinforcements and steel connectors. The cumulative energy dissipation of four prefabricated connections was greater than the monolithic specimen because H-steel beams were used in the prefabricated connections, indicating that the former had better energy dissipation owing to fuller hysteretic curves with smaller shrinks and a larger load-carrying capacity caused by less damage in the joint (). Additionally, specimen ZHJ4 with SFRC dissipated less energy than connection ZHJ1 owing to less concrete damage in the joint region. We deduced that SFRC restrained the concrete cracks and had a beneficial effect on concrete damage.The viscous damping ratio (he) is defined by Equation where SABCD is the area enclosed by curve ABCD, and SOEB + SOFD is the summation of triangular areas OEB and OFD., the four prefabricated specimens exhibited higher viscous damping ratios than the monolithic specimen because of the fuller hysteresis loops owing to the use of H-steel beams, which had a larger elastic stiffness and higher load-carrying capacity, resulting in effectively resisting earthquake loads. Specimens ZHJ1 and ZHJ4 with the bolted end plates exhibited the largest viscous damping ratio, followed by specimens ZHJ2 and ZHJ3 with welded reinforcements. Therefore, the H-steel used both in the precast beam and precast column connected through welding or bolting had positive a positive impact on energy dissipation. If the H-steel at the beam end dissipated much greater energy under reversed cyclic loading after yielding, the connections exhibited higher energy dissipation capacities. Similar results were reported by Xu et al. [The rotation capacity in the plastic hinge region can be estimated using moment–rotation hysteretic curves. The rotations of the specimens were measured using LVDTs 1–12 (). The bending moment at the beam end of the specimens was equal to the applied force (P) multiplied by the number of lever arms. shows the moment–rotation hysteresis curves for each specimen.Compared with the monolithic specimen, the four prefabricated specimens exhibited higher ultimate bending moments but lower maximum rotations. The results revealed that the increased moment capacity and rotation stiffness of the prefabricated specimens was caused by the cantilever H-steel beam in the columns. Compared with ZHJ1, ZHJ3, and ZHJ4, the length of the cantilever H-steel beam of the prefabricated connection ZHJ2 was larger, which decreased the rotation due to enhanced stiffness caused by H-steel. The length of the cantilever H-steel beam significantly influenced the rotation capacity. Additionally, specimen ZHJ3 exhibited a larger rotation at the final stage owing to the fracturing of the longitudinal reinforcements at the beam. Specimens ZHJ1 and ZHJ4 with the bolted end plates exhibited fuller moment–rotation hysteretic loops than other specimens. We can deduce that the proposed connection using H-steel can effectively transfer a load to increase the plastic deformation at the beam end. When the stiffness in the steel–concrete section changes abruptly, the stirrup spacing should be adequately decreased to achieve a ductility failure mode.The strain–displacement hysteretic curves of the H-steel beam web in the joint region are shown in The yield and ultimate strains of H-steel beam web were approximately 1492 and 2227 με, respectively, according to the material properties test results. The strain in the H-steel beams web of specimens ZHJ1 and ZHJ4 with the bolted end plates exceeded the yield strain at the displacement of 50 mm, which was consistent with the phenomenon of initial splitting cracks. After the displacement reached 70 mm, the strain in the H-steel beam web of the specimen ZHJ4 exceeded the ultimate value in the negative loading direction, and it was lower than the specimen ZHJ1 in the same displacement level. This was attributed to the phenomenon in which SFRC delayed crack propagation owing to the bridging mechanism. The maximum strain in the H-steel beam web of specimen ZHJ2 with welded reinforcement connection exceeded the ultimate strain, and it had a smaller strain in the positive loading direction. The average maximum strain of both ZHJ2 and ZHJ3 was close to the ultimate value because concrete was not damaged in the joint core region. The longitudinal reinforcements of the beam and column in specimens ZHJ1 and ZHJ4 did not yield, while the transverse reinforcements were yielded owing to the joint failure. For connections ZHJ2 and ZHJ3, the column longitudinal reinforcements and transverse reinforcements did not yield, but the beam longitudinal reinforcements were fracture resulted in flexural failure. shows the schematic shear deformation in the joint region. The shear deformation was measured using LVDTs 13 and 14 (where |AB| and |AD| are the horizontal and vertical distances between the diagonal LVDTs, respectively; Δ|AC| and Δ|BD| are the lengths AC and BD after joint occurred deformation, respectively. The shear force can be defined by Equation depicts shear force–shear deformation curves for beam–column connections.The ultimate shear forces of the four prefabricated connections were greater than the monolithic joint, indicating better shear bearing capability. The four prefabricated specimens had lower maximum shear deformations than the monolithic specimen owing to improved concrete spalling in the joint region at failure. The H-steel beams and SFRC restricted the joint shear deformation and enhanced the shear strength. At the same shear force level, the prefabricated connections exhibited less shear deformation than the monolithic specimen, which indicated that H-steel improved the stiffness in the joint region. Prefabricated specimens ZHJ1 and ZHJ4 with the bolted end plates experienced a larger maximum shear deformation than prefabricated specimens ZHJ2 and ZHJ3 with welded reinforcement connections, which was related to their failure modes. Before the joint shear failure, specimens ZHJ2 and ZHJ3 failed through flexural failure due to a significant change in stiffness caused by the fracturing of the welded longitudinal reinforcements.The shear demand (Vu) and shear strength (Vn) were calculated using Equations , respectively according to JGJ 138–2016 []. The shear strength was the sum of the contributions of the H-steel web, concrete, and stirrup in the core area. Particularly for the contributions of the steel web, the test result indicated that the H-steel web was in the shear yield state when the specimen reached the peak load, which was not local buckling owing to the effective constraints of concrete. Because the influence of axial compressive force was small, and the H-steel web was subjected to force in the plane, the shear strength provided by the H-steel web could be determined using 0.58fatwhw in Equation , which could significantly affect the joint shear strength.Vn=1γRE[2.3φjηjftbjhj+fyvAsvs(h0−as′)+0.58fatwhw]where Mar and Mal are the beam moments; Z is the distance from the upper reinforcement center to the lower one; Hc is the column height (2800 mm); ft is the concrete tensile strength (2.99 MPa); fyv is the transverse reinforcement tensile strength; fa is the steel yield strength; Asv and s are the sectional area and interval of the transverse reinforcements, respectively; tw and hw are the web thickness and web height of steel beam, respectively; h0 is the effective column depth; bj and hj are the effective joint width and depth, respectively; as' is the distance from the column compressive reinforcements to extreme compression layer; φj and ηj are the joint type coefficient and beam constraint influence coefficient, respectively (1.0); γRE is the seismic adjustment coefficient (0.85).The shear demands for ZHJ1, ZHJ2, ZHJ3, and ZHJ4 were 1722, 1760, 1790, and 1757 kN, respectively. The difference in shear demand for all prefabricated connections with different connecting configurations was small. The SFRC also slightly affected the shear demand. Based on JGJ 138–2016, the contribution of SFRC to the shear strength was neglected. Thus, the connections ZHJ2–ZHJ4 with SFRC had the same shear strength with specimen ZHJ1. The value of shear strength was 1646 kN, which was approximate to the shear demand of prefabricated connections. Specimens ZHJ1 and ZHJ4 with H-steel both in the precast beam and column were evaluated to be unsafe because the shear demand was larger than the shear strength, which was consistent with the failure mode (This paper proposes prefabricated steel–concrete beam–column connections with different configurations that are suitable for moment-resisting concrete frames. The following conclusions of the cyclic loading test conducted for five beam–column specimens can be drawn:The monolithic specimen and prefabricated connections with bolted end plates or weld-bolted H-steel connections failed via joint shear failure, whereas the prefabricated connections had less concrete crushing. The prefabricated connections with welded reinforcement connections exhibited flexural failure owing to a dramatic change in stiffness.The prefabricated H-steel concrete connections with different configurations demonstrated high energy dissipation capacities and shear strengths. Moreover, the prefabricated connections with the bolted end plates and SFRC exhibited larger deformation capacities and more stable load–displacement hysteretic responses.The proposed prefabricated H-steel concrete beam–column connections with different configurations were reliable, and the H-steel connector can effectively transfer loads under earthquake action. The different connecting forms had only a slight influence on strength and stiffness, while it significantly affected the failure modes and ductility.SFRC, instead of the normal concrete, is an attractive method of delaying crack propagation. Thus, it can be used in the vital region of the prefabricated connections.Jianxin Zhang: Conceptualization, Investigation, Writing-Original draft, Writing- Review & Editing.Chenchen Li: Investigation, Writing-Original draft, Writing-Review & Editing.Xiaowei Zhang: Investigation, Validation.Yanyan Li: Visualization, Investigation.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.Reliability analysis for cementless hip prosthesis using a new optimized formulation of yield stress against elasticity modulus relationshipUsing classical design optimization methods for implant-bone studies does not completely guarantee a safety and satisfactory performance, due in part to the randomness of bone properties and loading. Here, the material properties of the different bone layers are considered as uncertain parameters. So their corresponding yield stress values will not be deterministic, that leads to integrate variable limitations into the optimization process. Here there is a strong need to find a reliable mathematical relationship between yield stress and material properties of the different bone layers. In this work, a new optimized formulation for yield stress against elasticity modulus relationship is first developed. This model is based on some experimental results. A validation of the proposed formulation is next carried out to show its accuracy for both bone layers (cortical and cancellous). A probabilistic sensitivity analysis is then carried out to show the role of each input parameter with respect to the limit state function. The new optimized formulation is next integrated into a reliability analysis problem in order to assess the reliability level of the stem–bone study where we deal with variable boundary limitations. An illustrative application is considered as a bi-dimensional example (contains only two variables) in order to present the results in an illustrative 2D space. Finally, a multi-variable problem considering several daily loading cases on a hip prosthesis shows the applicability of the proposed strategy.Traditional deterministic design methods have accounted for uncertainties through empirical safety factors. The designer does not take into account uncertainties concerning materials, geometry and loading. A number of uncertainties are encountered during the design of osteo-articular systems. These uncertainties are resulted from the variability of applied loads and materials properties, in addition to that resulting from the design modeling. They can be grouped in three main categories, namely irreducible, reducible and statistical uncertainties Design variables xi: the design variables are deterministic variables defined in order to optimize the system. They represent control parameters of the mechanical system (e.g., dimensions, materials, loads) and of the probabilistic model (e.g., mean values and/or standard-deviations of random variables).Random variables yi: the uncertainties are modeled by stochastic physical variables affecting the failure scenario. These variables can represent geometrical dimensions, material characteristics or applied external loading. The knowledge of these variables is not, at best, more than statistical information and it can be admitted as a representation in the form of random variables. The random physical variables represent the structural uncertainties, which are identified by probabilistic distributions.Normalized variables ui: they represent the transformation of the random variables from the physical space to a normalized one according to certain probabilistic distribution laws.The material of this paper is organized as follows: some objectives concerning reliability analysis are first presented in Section . A review of the previous formulations of material properties, especially, Young’s modulus and yield stress against density relationship, are presented in Section with our generalized formulation of the yield stress against Young’s modulus relationship in Section . Using some experimental results, the generalized formulation is next developed to find our optimized constants of proportionality in Section . A numerical validation of the proposed formulation for cortical and cancellous experimental results is carried out in Section . Two numerical stem–bone examples considering several daily loading cases are presented in Section . The first numerical example of a bi-dimensional variable case is considered as an illustrative 2D space modeling and the second one is a multi-dimensional variable case to show applicability of the reliability integration using the proposed formulation and Section The notion of reliability is very old. Ancient civilizations constructed huge buildings and mechanisms and many of these structures still exist, i.e., they have proven to be very reliable designs. However, the cost of construction of these structures was tremendous. Nowadays, the two main objectives in the design of structural systems are to design systems that have satisfactory reliability and are as inexpensive as possible There is no way to make a perfectly safe design. Ignoring uncertainty and using safety factors usually leads to designs with inconsistent reliability levels. Three types of uncertainties can be considered Irreducible uncertainty: irreducible (or Inherent) uncertainty is due to the inherent randomness in physical phenomena and processes. It arises during the description of a physical process and still exists even if unlimited data is available.Reducible uncertainty: reducible (or model) uncertainty may happen due to the use of imperfect models to predict outcomes of an action. It results from the simplification of modeling a true physical process and can be minimized by using more sophisticated model.Statistical uncertainty: it is due to the lack of data for modeling uncertainty. Or, it is related to the fitting of a parametric distribution and this uncertainty can be decreased by increasing the number of fitting data points. shows a simplified diagram for design under uncertainty. The design optimization process controls the input parameters (quantified uncertainties) presented by statistical diagram in order to satisfy the required output parameters (calculated uncertainties). The test process is a comparative process between the calculated output and the quantified input until convergence, as shown in Several strategies can be used for uncertainty measurements such as: Safety factor, Worst case scenario-convex models, Taguchi methods, Fuzzy set methods, Probabilistic methods… These strategies lead a high computing time to compute the probability of failure. An efficient optimization method based on reliability index can be easily implemented and perform the reliability analysis with a reasonable computing time.To estimate the reliability index, several techniques have been developed during the last 40 years, namely FORM (First Order Reliability Methods), SORM (Second Order Reliability Method) and simulation techniques ). For a given failure scenario, the reliability index β is evaluated by solving a constrained minimization problem:where u is the vector modulus in the normalized space (or so-called distribution parameters), measured from the origin see . In FORM approximation, the probability of failure is simply evaluated bywhere Φ(⋅) is the standard Gaussian cumulated function given as follows: gives sufficiently accurate estimation of the failure probability. defines the most probable failure point (MPP) see b. The resulting minimum distance between the limit state function H(u) = 0 and the origin, is called the reliability index βThe mechanical properties of bone depend on composition and structure. However, composition is not constant in living tissues. It changes permanently in terms of the mechanical environment, ageing, disease, nutrition and other factors. Kopperdahl and Keaveny where ρα is the ash density. This expression explains over 96% of the statistical variation in the mechanical behavior of combined vertebral and femoral data over the range of ash density (ρα |
= (0.03–1.22 g/cm3)). Using the previous equations, the Young’s modulus and the yield stress in compression are respectively: E |
= (1.47–17643.65 MPa) and σC |
= (0.15–173.12 MPa). Furthermore, Keyak et al. For a simple test, let us consider an acceptable value of the ash density for trabecular bone, as: ρα |
= 0.25 g/cm3. According to the model of Keller In this work, the relationship between the yield stress and the Young’s modulus is first generalized to meet the different design requests. Let us present the developed models or equations using some constants. The Young’s modulus and the yield stress against the ash density relationship can be respectively generalized as follows:where AE and Aσ are constants of proportionality, nE and nσ are exponents of proportionality. Since both Young’s modulus and yield stress are related with the ash density or apparent one, the Young’s modulus with yield stress can be related using a logarithmic transformation. Eq. After having simple developments, a generalized relationship between the yield stress in compression and the Young’s modulus can be written as follows:where Rσ/E |
= |
nσ/nE is the ratio of exponents. The different studies indicate that the mathematical dependency of bone compressive mechanical properties on composition is closely dependent upon the density and mineral content range examined and, in terms of a single compositional measure, is best predicted by apparent ash density expressed as a power function. We have focused on compression strength because the ultimate tension strength of bone tissue is usually established as a percentage of the compression strength. The tension yield stress can be written:Different values have been used for this ratio, from 0.5 to 0.7 for cortical bone and from 0.7 to 1 for cancellous bone According to some experiments, the constants of Eq. can be determined. It is also easy to determine the ratio of exponents Rσ/E |
= |
nσ/nE using two experiment points: (σCi,Ei) and (σCi+1,Ei+1). Eq. This way the ratio of exponents can be written as follows:In order to get all constants with an optimum fitting curve, an iterative (optimization) method can be used for at least three given experiment points: (σCi,Ei),(σCi+1,Ei+1) and (σCi+2,Ei+2).Let us consider the three experimental results for cortical bone presented in . Three logarithmic equations can be formulated as follows:The three logarithmic equations are optimized in order to find the constant values with an optimum fitness. The resulting optimum constants are presented in . Here, the relationship can be written as follows.When using the new model for both cortical and cancellous layers (), the results seem to be much closer to the experimental values than those produced by the classical model of Keller Thus, when designing a stem, we recommend optimizing the developed model to obtain the different constants for different bone material behaviors (isotropic, orthotropic…). To show the importance of the proposed model, two numerical applications are next carried out.a shows a 3D model of the studied stem, however, for simplicity a 2D model will be considered during the optimization process. An illustration of the studied stem with different layers is shown in The number of elements considered for optimization is 1476 nonlinear elements (8-node/PLANE82) and the total number of nodes is 4825 nodes. According to , the cortical (or compact) bone part is assumed to be a homogeneous and isotropic material with Young’s modulus E |
= 17 GPa and Poisson’s ratio ν |
= 0.3. The corresponding experimental yield stress is: σy |
= 132 MPa where ɛ is the strain tensor and D is the elastic tensor. According to Huiskes et al. , the minimum stress value can be computed as follows:where E is the uniaxial Young’s modulus. To ensure long-term fixation, the minimum stress value in the surrounding bone has to exceed the threshold value σTar. Thus, the corresponding number of elements for metal region is 557 elements. In the present work three representative daily loading conditions of one-legged stance (L1), extreme ranges of motion of abduction (L2), and adduction (L3) are assumed . The boundary conditions at the distal end have no effect on the stresses in the proximal region. The fixation is carried out on lower bone cut (on the cortical layer) to avoid rigid-body motion.In order to evaluate the reliability level, the limit state function and the random variables should be determined. To determine the limit state function, a direct simulation can be carried out to get the different response results. To determine the most effective variable a sensitivity analysis is required. The random variables are presented by their mean and standard-deviation values.The output parameters can be represented by an indication of fracture stresses and loosening of prosthesis. The von-Mises stresses give an indication of the fracture stress at the different layers of the studied structure. The minimum stress value in the surrounding bone has to be kept above a certain minimum levels (Eq. ) to avoid the loosening of prosthesis functionality. According to , the third loading case is the most critical one. The limit state function is represented by the cancellous region stresses. Here, we note that the maximum von-Mises stress (σmax2=5.63MPa) is the closet one to the fracture ( shows the von-Mises stress distribution for the three loading cases. In the first and second cases, the maximum stresses are located in the metallic stem. But in the third one, the maximum von-Mises stress is located at the bottom right region of the cortical layer. Here, we can distinguish a tension failure case.The evaluation of the probabilistic sensitivities is based on the correlation coefficients between all random input variables and a particular random output parameter. The sensitivity plots only include the significant random input variables. shows the sensitivity measurements of the limit state function (output parameter) with respect to the input random variables (6 variables). When considering the three daily loading cases, there is a variant influence of the input parameters. However, the Young’s modulus of the cancellous and cortical regions has a higher influence relative to the other input parameters. This way when decreasing the Young’s modulus of the cortical bone, the maximum stress of cancellous regions will decrease (positive influence). In contrast, when decreasing the Young’s modulus of the cancellous bone, the maximum stress of cancellous regions will increase (negative influence).The objective is to find the Most Probable Point (MPP) which is represented by the minimum distance between of the origin of the normalized space and the most critical failure surface (limit state function). According to the previous stem–bone simulation, the limit state function is represented by the von-Mises stress at the cancellous layer. In order to formulate the reliability problem, Eqs. can be integrated to problem 1. Thus, for the given failure scenario (cancellous layer), the reliability index β is obtained by solving a constrained minimization problem:min:d(ui)=∑i=1nui2s.t.:H(ui,yi)=σmaxCan(ui,yi)-RT/C.AσeRσ/Elny2AE=0:g1(ui,yi)=σmaxCor(ui,yi)-RT/C.AσeRσ/Elny1AE⩽0:g2(ui,yi)=σmaxM(ui,yi)-σyM⩽0:g3(ui,yi)=σmaxM/B(ui,yi)-2y2U⩽0b) rather than in the space of physical variables (a). Hence, we adopt the law for a normal distribution, and define a normalized variable ui by the transformationwhere yi is a random variable with the mean value myi and standard-deviation σyi. The mean value myi may be adopted as a design variable xi (a). The standard deviations σyi are proposed proportional to the mean values (10%). According to the sensitivity analysis, we find two random variables are the most effective in the structure. Here, the physical space and normalized one in a pedagogical way (bi-dimensional space) can modeled in order to get the global optimum. However, when considering several random variables, the results are subject to classical difficulties in nonlinear programming: existence of local minima, gradient approximation and computational time. Since the reliability analysis is carried out in a normalized space (b), a special technique is developed in order to take advantage of the particular form of the reliability problem using APDL (ANSYS Parametric Design Language). The optimization algorithm, which is illustrated in , supplies us all information about the objective and constraint functions. This algorithm minimizes the minimum distance d(ui), which is carried out in the normalized space.For simplicity, the random variables xi corresponding to the Young’s modulus of the cortical and cancellous bone (E1, |
E2) are normally considered distributed. Their mean values are presented in and their standard deviations are proposed proportional to the mean values (10%). shows the reliability indices for three different loading cases when considering 2 parameters.a shows the optimization problem modeling in a physical space where the limit state functions are presented by G(E1, |
E2) = 0, however b shows the problem modeling in a normalized space where the limit state functions are presented by H(u1, |
u2) = 0. In the physical space, the mean value is presented by the coordinates (x1, |
x2), the MPP is represented by the coordinates (y1, |
y2) and the reliability levels are presented by ellipses. We model the tension limit states by three limitation curves (continuous lines: GL1T(E1,E2)=0,GL2T(E1,E2)=0 and GL3T(E1,E2)=0) corresponding to the three loading cases and the compression limit states by three limitation curves (intermittent lines: GL1C(E1,E2)=0,GL2C(E1,E2)=0 and GL3C(E1,E2)=0) corresponding to the three loading cases. Here, the MPP is located on the minimum distance between the mean value and the failure limit L3 for tension limit state curve (GL3T(E1,E2)=0). However, in the normalized space, the mean value is presented by the origin (0, 0), the MPP is represented by the coordinates (u1, |
u2) and the reliability levels are presented by circles according to Eq. . We model the tension limit states by three limitation curves (continuous lines: HL1T(E1,E2)=0,HL2T(E1,E2)=0 and HL3T(E1,E2)=0) corresponding to the three loading cases and the compression limit states by three limitation curves (intermittent lines: HL1C(E1,E2)=0,HL2C(E1,E2)=0 and HL3C(E1,E2)=0) corresponding to the three loading cases. Here, the MPP is located on the minimum distance between the origin and the failure limit L3 for tension limit state curve (HL3T(E1,E2)=0). We can also note that the third loading case L3 in tension is the most critical case. It is called the failure limit (or surface) and divides the space into safe and failure regions. The most probable failure point (MPP) is then found for βL3T=2.16 when considering tension failure case that leads to a reasonable level of probability of failure: Pf=1.54% using Eqs. . The reliability index is bigger when considering compression failure case: βL3C=4.38 that leads to a very small probability of failure: Pf |
= 5.93 × 10−6.In this case, the random variables xi corresponding to the Young’s modulus and the Poisson’s ratio of different layers (E1, |
E2, |
E3, |
ν1, |
ν2, |
ν3) are normally considered distributed. Their mean values are presented in and their standard deviations are proposed proportional to the mean values (10%). shows the reliability indices for three different loading cases when considering 6 parameters.For this six parameter optimization process, the most probable failure point (MPP) is also found for β |
= 2.16 when considering tension failure case that leads to a reasonable level of probability of failure: Pf=1.54%. The reliability index is bigger when considering compression failure case: βL3C=5.28 that leads to a very small probability of failure: Pf |
= 6.46 × 10−8. shows that the most effective parameter is the Young’s modulus of the cancellous layer. According to the experimental test of Aleixo et al. ). The experimental results are also prone to different errors (testing protocols…). To improve our design, the ratio of RT/C |
≈ 0.7 is considered during the optimization process. Furthermore, the composition of bone materials can be changed according to several factors such as ageing, and disease. It is strongly recommended to integrate the randomness of material behaviors into the prosthesis design strategy. In the literature, several works correlate mechanical properties of bone materials with its composition The proposed strategy essentially consists in integrating reliability analysis into prosthesis design. When considering the randomness or uncertainty on the material properties of the bone, the change of these properties leads to change of its resistance. For example, when changing the elasticity modulus of the bone, the corresponding yield strength will be changed. In general, the composite structure of bone contains organic and inorganic components. Inorganic components are essentially responsible for the compression strength and stiffness, while organic components provide the corresponding tension properties. The developed formulation is mainly based on the inorganic component effects (explicit relationship). According to several experimental works, some coefficients are added to the proposed model in order to take in account the organic component effects (implicit relationship). The optimized formulation for yield stress against elasticity modulus relationship is then developed. Some experimental results are next used to show the proposed model accuracy relative to existing ones. To integrate the reliability concept, a sensitivity analysis is carried out to identify all material parameter roles. Two numerical examples considering several daily loading cases are optimized in order to show the importance of the proposed optimized model (formulation) and also the reliability integration during the design process. In both studied cases, the elasticity modulus of the cancellous layer is the most sensitive parameter. The different results lead to a reasonable level of probability of failure for tension failure case (most dangerous case). The new optimized formulation can be considered as a practical tool for osteoarticular system designers and can be easily implemented into design optimization process. For future developments of this model, the different bone behaviors (orthotropic, anisotropic…) can be considered in order to get realistic results. This integration also allows us finding the optimum position of the implant relative to bone layers with object of insuring a high reliability (confidence) level.Type and orientation of yielded trabeculae during overloading of trabecular bone along orthogonal directionsTrabecular architecture plays a major role in bone mechanics. Osteoporosis leads to a transition from a plate-like to a more rod-like trabecular morphology, which may contribute to fracture risk beyond that predicted by changes in density. In this study, microstructural finite element analysis results were analyzed using individual trabeculae segmentation (ITS) to identify the type and orientation of trabeculae where tissue yielded during compressive overloads in two orthogonal directions. For both apparent loading conditions, most of the yielded tissue was found in longitudinally oriented plates. However, the primary loading mode of yielded trabeculae was axial compression with superposed bending for on-axis loading in contrast to bending for transverse loading. For either loading direction, most plate-like trabeculae yielded in the same loading mode, regardless of their orientation. In contrast, rods oriented parallel to the loading axis yielded in compression, while rods oblique or perpendicular to the loading axis yielded in combined bending and tension. The predominance of tissue yielding in plates during both on-axis and transverse overloading explains why on-axis overloading is detrimental to the off-axis mechanical properties. At the same time, a large fraction of the tissue in rod-like trabeculae parallel to the loading direction yielded in both on-axis and transverse loading. Hence, rods may be more likely to be damaged and potentially resorbed by damage mediated remodeling.Trabecular tissue loss in osteoporotic and aging patients is accompanied by topological changes in microstructure, including the conversion of trabecular plates to rods (). Such changes negatively affect the elastic, yield, and damage behaviors, as trabecular plates play more crucial roles than rods in apparent modulus, apparent yield strength, and microdamage formation (). More rod-like morphologies, characterized by an increase in structure model index (SMI), are associated with a decrease in toughness and strength () and increased microdamage susceptibility during overloading of bovine tibiae (). SMI is also positively correlated with in vivo microdamage burden in human vertebrae (). If microdamage stimulates increased remodeling () that in turn leads to more rod-like morphologies (), unstable degradation of the mechanical properties may result.Trabecular bone is subjected to a variety of loads during activities of daily living, and the orientation of the applied strains with respect to the trabecular orientation plays an important role in trabecular tissue yielding. Thinning of trabeculae and perforation of plates are not uniform in osteoporotic bone, resulting in disproportionate changes in the mechanical properties along the longitudinal and horizontal directions. Trabeculae oriented horizontally tend to be perforated, become thinner, or eventually disappear (), while those oriented longitudinally tend to retain their thickness (). Such structures are more susceptible to buckling under normal axial compressive loads and damage from unusual or off-axis loading (). Computational models have been used to successfully study apparent level yielding () in trabecular bone. In bovine trabecular bone, computational simulations indicate less tissue level yielding for transverse loading than on-axis loading (). These results are consistent with experiments where an on-axis overload caused a 35% reduction in the elastic modulus of human vertebral trabecular bone along the transverse direction, while transverse overloading caused only a statistically insignificant 10% decrease in the on-axis properties (Understanding the effects of trabecular architecture on the mechanics of trabecular bone under various loading conditions should provide insight into bone quality, which will be useful in the development and evaluation of treatments for osteoporosis. The objective of this study was to identify the trabecular morphologies that are susceptible to tissue level yielding in trabecular bone. Specifically, the aims of this study were to (1) identify the yielded tissue in trabecular bone samples overloaded in on-axis and transverse compression using microstructural finite element analysis (micro-FEA) models; (2) decompose the samples into individual plate and rod elements that contained yielded tissue using individual trabeculae segmentation (ITS) technique (); (3) categorize the failure modes of individual trabeculae according to the predominant stress states; (4) compare the failure modes between the two apparent loading modes.Ten cylindrical bovine proximal tibial trabecular bone specimens from a previous study () were analyzed. The orientation of the specimens was controlled using micro-CT imaging to ensure that the principal trabecular orientation was aligned with the axis of the specimens (). The specimens were scanned at 20 μm isotropic resolution in a micro-CT scanner (μCT-80, Scanco Medical AG, Brüttisellen, Switzerland) and the architecture was quantified using the standard software (μCT Evaluation Program V4.3, Scanco Medical AG, Brüttisellen, Switzerland, ). The threshold for evaluation and subsequent finite element modeling was chosen to match the image volume fraction with that measured by Archimedes’s principle.Microstructural finite element models were created for each specimen by directly converting bone voxels into eight-node finite elements (). Cuboid regions, 5×5×6 mm3 in size, were taken from the center of the cylindrical specimens, allowing application of boundary conditions for uniform transverse loading. The images were downsampled to 40 μm isotropic resolution by region-averaging in order to reduce computational time while satisfying the requirements for numerical convergence (). The trabecular tissue was modeled as a homogenous isotropic material with a specimen-specific back-calculated tissue modulus. Briefly, a single step linear FEA was performed to calculate the ratio of tissue modulus to apparent modulus for each specimen. The specimen-specific tissue modulus was obtained by multiplying this ratio with the experimentally determined apparent modulus for each specimen (). A bilinear elastic tissue constitutive model with an asymmetric principal strain yield criterion () was applied with compressive and tensile tissue yield strains of 0.83% and 0.41%, respectively (). The Poisson’s ratio was set to 0.3. Each sample was analyzed twice, first with boundary conditions corresponding to 1.2% on-axis compressive strain, then with 1.2% transverse compressive strain. Geometric nonlinearity was not included, but the effects would be small for the dense plate-like samples and low apparent strains used in this study (ITS was used to identify individual plates and rods within each sample (), and the amount of bone tissue in each trabecular type – plate or rod – was quantified. Trabeculae were further classified as longitudinal, oblique, or horizontal based on their orientation with respect to the specimen axis, which was aligned with the principal trabecular orientation (The tissue strains were calculated from the models, and regions that exceeded the yield strains were identified. Due to the porous architecture of trabecular bone, bone tissue can yield due to either compressive or tensile strain under apparent compressive loading. As such, tissue that yielded due to exceeding the compressive or tensile strain limit was detected and segmented separately. The distribution of the yielded tissue within trabecular types and orientations, and the fraction of the total tissue within each trabecular type and orientation combination that yielded was calculated.Failed trabeculae were identified, and the fraction of trabeculae of each type or orientation that failed was quantified. Most trabeculae contained some yielded tissue due to the irregular mesh boundary introducing artificial stress concentrations (). As such, a threshold of 15% of the tissue within a trabecula was used to identify trabeculae that had failed. A parameter study was conducted to determine the effect of using different thresholds, and the results were not sensitive to this parameter when varied over a range from 5% to 20%. The trabeculae were further categorized as having failed in compression, bending, or tension based on the volume ratio of tissue that yielded in tension to compression being less than 1/4, from 1/4 to 3/4, or greater than 3/4.Statistical analysis was performed with Student’s t-test in Microsoft Excel. The Tukey post-hoc test was used to identify groups with significant differences for ANOVA using JMP 7.0 (SAS Institute Inc., Cary, NC).The samples were primarily composed of longitudinally oriented plates. On average, 80±10% (Mean±SD) of the tissue was found in plates, over 70% of which were oriented in the longitudinal direction. In contrast, over 70% of the rods were oriented in the horizontal direction. Longitudinal trabeculae had a greater volume than horizontal trabeculae (). Visualization software AVS (Advanced Visual Systems Inc., Waltham, MA) was used to verify the rod- and plate-like morphologies of the segmented trabeculae and their orientations (Most of the tissue that yielded was in plates and longitudinally oriented trabeculae for both loading conditions. Plates contained 81±11% of the yielded tissue for on-axis loading, and 69±12% of the yielded tissue was found in plates for transverse loading (a). Similarly, 78±8% of the yielded tissue was found in longitudinal trabeculae for on-axis and 63±10% for transverse loading (b). Combining these data, longitudinally oriented plates were the primary site of yielding, accounting for 73±11% of the total yielded tissue in apparent on-axis compression and 60±12% in apparent transverse compression, respectively.The apparent loading direction affected whether tissue yielded due to compressive vs. tensile strain. When compressed on-axis, over twice as much tissue yielded due to compressive vs. tensile strain in plates (p<0.01, a). In contrast, tensile yielding was more common in plates for apparent level transverse compression. Similarly, in rods over 1.3 times as much tissue yielded due to compressive vs. tensile strain for apparent level on-axis compression, while compressive and tensile yielding were equally common for apparent level transverse compression.When compared by trabecular orientation, the yielding modes differed for the two apparent loading directions. During apparent level on-axis compression, the ratio of tissue that yielded in compression to tension was greater than two in longitudinal trabeculae, but tensile yielding was predominant in horizontal trabeculae (b). In contrast, during transverse compression, tensile yielding dominated in longitudinal trabeculae (p<0.05), while there was similar amount of tissue yielded in both compression and tension for horizontal trabeculae (p>0.15).The fraction of tissue that yielded due to compressive vs. tensile strain within each trabecular type depended on apparent loading direction and trabecular orientation. In plates, there was a higher fraction of tissue that yielded due to compressive strain than tensile strain for on-axis loading (a), while tensile yielding dominated for transverse loading (b), regardless of the plate orientation. However, the yielding modes of rods depended on both the loading direction and their orientations. Following on-axis compression, the volume ratio of the yielded tissue that was strained in compression to tension was over four in longitudinal rods, between one and two in oblique rods, and less than one in horizontal rods during on-axis loading (a). This trend was reversed for transverse loading (In trabeculae oriented parallel to the apparent loading direction, the volume ratio of tissue that yielded due to compressive vs. tensile strain was higher in rods than in plates. During on-axis loading, the ratio was 5.2±2.4 for longitudinal rods, in contrast to 2.2±0.6 for longitudinal plates (p=0.001, a). During transverse loading, the ratios were 1.2±0.3 for horizontal rods and 0.6±0.3 for horizontal plates (p=0.002, b). When considering all yielded tissue, a higher fraction of the total tissue in rods parallel to the loading direction yielded than for similarly oriented plates for both apparent loading modes (p<0.05).The distribution of the failed trabeculae – those where more than 15% of the tissue yielded – depended on trabecular type and orientation for on-axis loading but not transverse loading (). Following on-axis overloading, the fraction of trabeculae that failed in compression and bending was higher than that in tension in plates and longitudinal trabeculae, while the fraction of trabeculae that failed in bending was the highest in rods and oblique trabeculae (p<0.05, a, c). The fraction of trabeculae that failed in tension and bending was the highest in horizontal trabeculae (p<0.05, c). In contrast, during transverse loading, there was no preferred trabecular failure mode, although a slightly smaller fraction of trabeculae failed in compression than in tension or bending for plates, longitudinal and oblique trabeculae (p<0.05, Understanding which trabecular microstructures are most susceptible to damage and failure under various loading conditions should provide insight into bone quality and the mechanisms of osteoporosis treatments. Longitudinal plates were the main site of trabecular yielding for both apparent on-axis and transverse compression in dense plate-like architectures, revealing the structural importance of these trabecular elements. However, during on-axis loading, longitudinal plates were axially compressed with superposed bending – as indicated by the predominance of compressive yielding – while during transverse loading, the plates were primarily bent as indicated by more tensile yielding. Bending was the most important failure mode in rods and off-axis trabeculae for both on-axis and transverse loading.The main strength of this study was the identification of the specific trabecular types and orientations using the ITS technique where yielded tissue was predicted by micro-FEA. The quantity of data and the need to investigate the trends for a population make such methods invaluable for post-processing micro-FEA results. However, there are also important limitations that must be considered when interpreting the results. First, bovine tibial trabecular bone specimens, which are plate-dominated structures, were used in the study, and the results may differ in rod-dominated structures, such as vertebral trabecular bone. Second, the relationships between tissue level yielding and microdamage formation or modulus decreases have not been fully established. As such, further studies of these correlations are needed.An important limitation of this study is the tissue level constitutive model. This constitutive model results in correct prediction of the apparent level yield behavior (), and the strain limits in the tissue level constitutive model are consistent with the yield limits measured in cortical bone tissue (). While these factors support its validity, there has been no direct correlation of the yielded tissue in the models to either permanent deformation or microdamage in actual samples. There is a correlation between the proportion of the predicted yielded tissue that occurs in longitudinal rods and the measured microcrack density (), but in general tissue level yielding does not correlate with microcrack density. Indeed, while microdamage occurs in regions of higher local stress and strain calculated by linear finite element models (), not all high-stress regions are damaged. As such, the yielded regions do not necessarily represent regions of visible microdamage. Neither permanent deformation nor submicroscopic forms of tissue damage have been quantified and compared to finite element models. As such, the constitutive model is a plausible, but not a proven model.The findings further explain the differences in the morphology of the predicted yielded regions between on-axis and transverse overloading (). Yielded regions are larger and more oriented during on-axis compression, because they occur in plates. In transverse compression, the plates do not have a single yielded region of a single mode, but instead have adjacent tensile and compressive yielded regions. In general, plates provide most of the mechanical support in the trabecular structure, and their yielding modes differ between apparent loading modes but are similar for all trabecular orientations. Recent studies that reached similar conclusions did not explore the yielding modes (). In contrast, rods of each orientation have different proportions of tensile and compressive yielding. When taking into account the loading orientation, rods parallel and perpendicular to the apparent loading direction always have greater fractions of compressive and tensile yielding, respectively.The results complement experimental studies of damage and overloading in trabecular bone. The major contribution from longitudinal plates during both on-axis and transverse loading suggests that damage caused by on-axis compression may also affect transverse mechanical properties. This is consistent with the experiments that found on-axis overloading caused a significant decrease in the shear modulus of bovine trabecular bone (), and a 35% reduction in the transverse apparent elastic modulus in human vertebral trabecular bone (). As such, in vivo microdamage that is associated with normal loading during activities of daily living may be detrimental to the mechanical properties for shear or other abnormal loads (The results also complement recent work by , which found that human femoral trabecular bone, when loaded off-axis has lower levels of tissue yielding and a higher proportion of tissue that yielded in tension than compression. Our results further confirm the concept of increased bending of the plate-like trabeculae when the apparent level loading is transverse to the principal trabecular orientation.The results extend our understanding of the relative roles of trabecular plates and rods beyond the elastic range () to the yielding stage. Although rods play a role in both on-axis and transverse compressive loading depending on their orientation relative to the loading direction, the greatest volume of yielded tissue occurs in trabecular plates for both loading modes. In osteoporotic and aging trabecular bone, horizontal trabeculae are preferentially thinned and perforated while longitudinal trabeculae maintain their thickness, leading to a more anisotropic structure that has a greater susceptibility to fractures (). This altered structure has a decreased number of plates along the horizontal direction, and the present results show that rods oriented along the apparent loading axis are more likely to fail than plates. Since yielding in rods is directly correlated to increased microcrack density (), the transition of horizontal trabeculae to a more rod-like morphology in osteoporotic bone may make the whole structure more vulnerable to damage from unusual or off-axis loading.None of the authors have any financial or personal interests with organizations that may benefit from this work.Supplementary data associated with this article can be found in the online version at The role of sclerotic changes in the starting mechanisms of collapse: A histomorphometric and FEM study on the femoral head of osteonecrosisTo assess the distributions of stress, strain, and fractured areas using a finite element model (FEM), and examine the osteoclastic activity histopathologically in osteonecrosis of the femoral head.Three femoral heads were obtained during hip arthroplasty for femoral head osteonecrosis. One sample with a normal area, two samples with a non-sclerotic boundary without collapse (Type 1), two samples with a non-collapsed sclerotic boundary (Type 2), and two samples with a collapsed sclerotic boundary (Type 3) were collected from each femoral head for the FEM and histopathological analyses. FEM was performed using CT data, and the distributions of von Mises equivalent stress, octahedral shear stress, octahedral shear strain, and simulated fractured area were evaluated. Furthermore, the osteoclast count at the boundary was compared for each type.In normal and Type 1 samples, the distributions of von Mises equivalent stress, octahedral shear stress, octahedral shear strain, and the fractured area were equally concentrated along the whole analytical range; however, in the Type 2 and 3 samples, they were concentrated along the thickened bone trabeculae at the boundary, which corresponded to the fractured area. Histopathologically, a significantly increased osteoclast number was observed only at the collapsed sclerotic boundary.These results demonstrated that both shear stress and shear strain tend to be concentrated on thickened bone trabeculae at the boundary. Fracture analyses revealed that the boundary of sclerotic changes, which results from the repair process, may be the starting point of the fracture. Additionally, the osteoclastic activity increases after collapse.Osteonecrosis of the femoral head (ONFH) is considered to be a bone infarction caused by ischemia To date, there are two hypotheses regarding the mechanism of collapse. One is based on the effects of shear stress at the boundary of necrotic and normal areas The three-dimensional finite element model (FEM) can be used to analyze the stress distribution by simulating loading and force In this study, we assessed the distributions of stress, strain, and the simulated fractured area in normal and boundary areas by FEM analyses. In addition, the osteoclastic activity in each area was examined using a histopathological examination.This study was approved by the institutional review board. Three femoral heads were used in this study. The femoral heads were obtained during hip arthroplasty for association research circulation osseous (ARCO) stage-3 ONFH from two males and one female with a mean age of 53 years (range: 34–63) The femoral heads were fixed in 4% para-formalin for three days and cut into 3-mm-thick sections parallel to the cervical axis. All three femoral heads were used for both the FEM and histopathological analyses, which were performed to examine osteoclastic activity. From the cut slices of one femoral head, the following samples (Width: 20 mm × Height: 15 mm × Depth: 3 mm) were collected based on both a macroscopic examination and specimen radiographs: one sample of a normal area, two samples with a non-sclerotic boundary without collapse (Type 1), two samples with a non-collapsed sclerotic boundary (Type 2), and two samples with a collapsed sclerotic boundary (Type 3) (). In total, 21 samples were collected from 3 femoral heads. Regarding the conditions at the boundaries, the samples that included a boundary were classified into three types: a non-sclerotic boundary without collapse (Type 1), a non-collapsed sclerotic boundary (Type 2), and a collapsed sclerotic boundary (Type 3).All of the 21 samples were scanned with high-resolution μCT (R_mCT T1, Rigaku, Tokyo, Japan). CT was performed at a voltage of 60 kV, current of 60 μA, resolution of 50 μm per pixel, and a slice thickness of 0.4 mm. Structural indices of trabecular bone were calculated using a 3D image analysis system (TRI/3D-BON; RATOC System Engineering, Tokyo, Japan). The parameters were calculated in 3D as follows: the trabecular volumetric bone mineral density (vBMD) was determined using a reference phantom (Kyoto Kagaku, Kyoto, Japan) b). In the fracture analysis, von Mises equivalent stress > 4.2 MPa was defined as the stress that induces trabecular fracture After obtaining measurements of FEM, all samples were soaked in 70% ethanol to remove fat from the bone marrow for one day. Thereafter, the samples were decalcified using EDTA for seven days, embedded in paraffin and cut into 3 μm sections. Hematoxylin and eosin (HE) staining was performed in all samples. In addition, tartrate-resistant acid phosphatase (TRAP) staining was performed in 21 samples to count the number of osteoclasts using a TRAP staining kit (WAKO, Osaka, Japan). Osteoclasts were defined as TRAP-positive multinucleated cells with more than three nuclei that existed around the trabecular bone The average numbers of osteoclasts among the three boundary types (Types 1, 2, and 3) were compared using a Poisson regression analysis. The statistical analysis was performed using the JMP 11.0 software package (SAS Institute, Cary, NC, USA). A p-value of < 0.05 was considered to be statistically significant.In three normal area samples, the distributions of von Mises equivalent stress, octahedral shear stress, and octahedral shear strain were equally concentrated along the whole analytical range (). In Type 1 samples (n = 6), the distributions of these mechanical properties were equally concentrated along the whole analytical range, including the necrotic, normal and boundary areas (g–k). In contrast, these mechanical properties were concentrated at the boundary in Type 2 samples (n = 6), (m–q), where the thickened bone trabeculae were observed. In Type 3 samples (n = 6), the distributions of these mechanical properties were also concentrated at the boundary (s–w). In fracture analysis, the simulated fractured area was distributed along the whole analytical range in the normal area and Type 1 samples (f, l), whereas it was mainly seen at the sclerotic boundary in Type 2 and Type 3 samples (In Type 1, no thickened bone trabeculae were observed at the boundary, where only small number of osteoclasts was present, similar to that seen in the normal area (). In Type 2, the number of osteoclasts remained small (c), even at the boundary where the thickened bone trabeculae were observed. On the other hand, in Type 3, a significantly increased number of osteoclasts was observed along the fractured bone trabeculae (To our knowledge, this is the first study to demonstrate the distributions of stress and strain at the non-collapsed boundary, where the concentration of these mechanical properties was observed along the thickened bone trabeculae; in contrast to the equal distributions noted in the normal area. The type classifications that were used to represent the conditions at the boundary in the present study seem to correspond to the ARCO stage, with ARCO stages 1, 2 and 3 corresponding to Type 1 (non-sclerotic boundary without collapse), Type 2 (non-collapsed sclerotic boundary), and Type 3 (collapsed sclerotic boundary), respectively. In Type 1, the distributions of shear stress and shear strain were equivalent in each area, which was completely different from the concentration of shear stress and shear strain seen at the sclerotic boundary in Type 2. These results suggest that the concentration of shear stress and shear strain at the non-collapsed boundary may depend on the degree of sclerotic changes due to thickening of the bone trabeculae. Furthermore, the results of the fracture analysis suggest that the non-collapsed sclerotic boundary may be the starting point of the fracture. In our recent study using SPECT/CT with 99 m technetium hydroxymethylene diphosphonate, the osteoblastic activity in the pre-collapsed stage was found to gradually increase around the necrotic lesion Based on the hypothesis that osteoclastic bone resorption at the boundary may be a cause of collapse, several studies have reported that alendronate, a bisphosphonate compound, shows effectiveness for the prevention of femoral head collapse in cases of ONFH Although the distributions of both shear stress and shear strain were found to be concentrated along the sclerotic boundary in this study, these distributions may not necessarily correspond to the site of collapse in clinical cases. Collapse is known to appear not only inside the necrotic lesion, but also in the subchondral region In this study, plain radiographs showed the sclerotic line in all of the femoral heads before the surgery. Nevertheless, no sclerotic line was observed in some of the slice samples that included the boundary, which might indicate differences in the progression of the sclerotic changes in each sample. The location and extent of the necrotic area are considered to be the most important factors affecting the occurrence of collapse. The rate of collapse in cases where the necrotic area involves more than two-thirds of the weight-bearing portion of the femoral head is reported to be around 94% This study is associated with several limitations. Each sample was collected from a collapsed femoral head, although an ideal analysis of the distributions of stress and strain at the boundary should involve analyses of the whole femoral head before collapse. However, it is impossible to obtain such specimens of the entire femoral head prior to collapse, since the patient has no pain. Therefore, surgically resected femoral heads containing a non-collapsed medial boundary were used in this study. The second limitation is the small number of samples that were examined, mainly due to the rarity of femoral head specimens containing a non-collapsed medial boundary. Furthermore, it was difficult to collect samples containing a boundary corresponding to each type from the same femoral head. Although the data of the current study were not sufficient for proving whether the concentration of stress and strain at the sclerotic boundary of the necrotic lesion actually causes collapse, our results may at least serve as basic data for future studies designed to clarify the mechanisms of collapse.In conclusion, the current study demonstrated that both shear stress and shear strain tend to be concentrated on thickened bone trabeculae at the boundary along with the progression of sclerotic changes, whereas increased osteoclastic activity is not observed unless collapse has occurred. The results of the fracture analysis revealed that boundary areas, in which sclerotic changes resulting from the repair process are present, may be the starting point of fracture. We therefore consider that sclerotic changes at the boundary may play an important role in the pathomechanism of collapse.The authors declare no conflicts of interest in association with the present study.Study design: KK, TY, and GM. Acquisition of samples: KK, TY, GM, KS, and YK. Study conduct: KK, TY, GM, KS, and YK. Drafting manuscript: KK. Revising manuscript: TY and GM. Approving final version of manuscript: KK, TY, GM, KS, YK, and YI. KK and TY take responsibility for integrity of the data analysis.Photothermally enabled MXene hydrogel membrane with integrated solar-driven evaporation and photodegradation for efficient water purificationSustainable and energy-efficient water purification making use of solar energy is highly desirable to address water scarcity and pollution crisis. However, it remains a challenge to achieve full solar spectrum utilization with photothermal and photodegradation capability. Herein, inspired by the unique optical property of MXene, a novel assembly of MXene hydrogel membrane with synergistic photothermal and photocatalysis effect is proposed for integrated water purification. The MXene hydrogel membrane is fabricated based on the structure-directing of self-stacking MXene nanosheets and its abundant molecular interactions with the polymer matrix, polyvinyl alcohol (PVA), and the multifunctional layer-crosslinker, porphyrin. The obtained MXene hydrogel membrane exhibits fascinating physicochemical properties combining dynamic hydrophilic network of hydrogel and permeability of membrane, making it a preferred medium for both vapor generation and photodegradation. Moreover, calculation and experimental results illustrates the charge redistributions and coupling interactions between MXene and porphyrin, which imparts enhanced photothermal effect and photocatalytic activitiy. As a result, the MXene hydrogel membrane exhibits an high solar-driven water evaporation rate (1.82 kg m−2 |
h−1) and a photodegradation efficiency (90.5 %), rendering an integrated water purification capability under one sun irradiation. This work presents a feasible and effective route towards develop of MXene-mediated cooperative photochemical and photothermal solar energy conversion for sustainable water purification.Freshwater scarcity is a daunting challenge which will continue to aggregate in the future with the development of global economy and society. This situation can be further exacerbated by the on-going water pollutions, which poses great threats to the environment and human health due to the presence of hazardous organic pollutants in wastewater Fundamentally, to achieve efficient water purification by integrated solar-driven evaporation and photodegradation, functional materials with cooperative photothermal conversion and photocatalytic activity is highly sought after Recently, titanium carbide (Ti3C2Tx, T = –F, –O, and –OH), a kind of two-dimensional (2D) MXene materials, has drawn considerable attention due to its broad solar-spectrum absorption, outstanding photothermal effect, and hydrophilic 2D interlayered channels In this work, we present a novel and versatile application of MXene for the assembly of hydrogel membrane (MAP) for photothermally enabled integrated water purification. Our design mainly makes use of the fascinating physicochemical properties of hydorgel membrane that combinesd dynamic hydrophilic network of hydrogel and permeability of membrane, which makes it a preferred medium for both vapor generation and photodegradation All working solutions were prepared using American Chemical Society-grade chemicals and Milli-Q water. Ti3AlC2 (MAX, purity > 98 wt%). Nylon filter film and PVDF filter film (pore size ∼ 0.22 μm) was purchased from Millipore. Meso-tetra(4-carboxyphenyl) porphyrin (H2TCPP) suspension was purchased from Frontier Scientific Co., Ltd, and Polyvinyl Alcohol (PVA) was purchased from Alfa Aesar.Ti3C2Tx nanosheets were synthesised based on an LiF and HCl etching method. In this process, 0.5 g Ti3AlC2 was immersed in an HCl (9 M) and LiF (0.5 g) aqueous solution and the resulting mixture was magnetically stirred at 35 °C for 24 h. The resulting Ti3C2Tx solution was extensively washed and then dispersed in deionised water (DI), followed by a mild ultrasonication process. After a further centrifugation and washing process, the Ti3C2Tx MXene dispersion colloids was obtained.Typically, an optimized MXene dispersion colloids (10.0 mg) was first fully stirred and mixed with Polyvinyl alcohol (PVA) in an optimized ratio of 1.0:0.3 (w/w), followed by the addition of porphyrin. The resulting mixtures were fully stirred and subjected to a further filtration process on filter film (∼0.22 μm), leading to formation of the MXene-PVA-Porphyrin (MAP) hydrogel membranes. After being washed three times with DI and dried at 60 °C under vacuum for 24 h, the dry MAP hydrogel membrane could be peeled off after the fully self-crosslinking. Series of MAP hydrogel membranes consist of different mass ratios of MXene and porphyrin (1.0:0.05, 1.0:0.1, and 1.0:0.2) were fabricated, denoted as MAP5, MAP10, and MAP20, respectively. The MAP20 hydrogel membrane was chosen as the typical membrane after a comprehensive optimization. As a comparison, MXene membrane without porphyrin content was also fabricated based on the same process.Material structures were characterized by transmission electron microscopy (TEM; JEOL 2011F) and field-emission scanning electron microscopy (FESEM; FEI Quanta 450). Grazing incidence X-ray diffraction (GIXRD; Ultima IV) was used to determine the crystalline structure of the membrane samples. Water contact-angle measurements were carried on the sessile drop method using a drop-shape analyser (FM 4000, Krüss, Germany). Optical coherence tomography (OCT, THORLABS) was used to obtain 3D optical sections of the internal structure. Raman spectrometry was conducted with a Renishaw-200 visual Raman microscope using a 633 nm laser beam. Elemental chemical states were detected using X-ray photoelectron spectroscopy (XPS; GESCALAB220i-XL). Absorption spectra were measured on an ultraviolet–visible spectrometer (UV–Vis 3600, Shimadzu) incorporating an attached integrating sphere. The membrane’s thermal conductivity was measured by a Mathis TCi thermal conductivity analyser (C-Therm). Swelling properties of the membranes were evaluated by immersing a ∼0.01 g dry membrane in 100 g DI water at room temperature. The swelling ratio, SW, was calculated based on the equation:where W0, and Wt represent the mass of the membrane at the initial and time t, respectively.Photothermal evaporation experiments were carried out using a Xe short-arc lamp (CEL-HXF300) as the illuminator, equipped with an optical filter for standard AM 1.5G spectrum. RhB solution (5 mg L−1), seawater (3.5 wt%, Science Park, Hong Kong), and high salinity water (10.0 % NaCl) were treated. Before test, the membrane was fully wetted to achieve the adsorption–desorption equilibrium. During these tests, the indoor test humidity and temperature were ∼ 60% and ∼ 25 °C, respectively. Weight changes were monitored using an electronic analytical scale (accurate to 0.1 mg) and were recorded in real-time. Surface temperature and IR thermographs were captured using an IR camera (FLIR E5).Photodegradation tests were carried out in a 100 mL quartz beaker containing an aqueous suspension of Rhodamine B (RhB, 30 mL, 5 mg L−1), and a piece of membrane about ∼ 10.0 mg. The light intensity was kept at one-sun (1 kW m−2) using Xe short-arc lamp (CEL-HXF300) as the light source for the duration. Before being subjected to sunlight irradiation, the membranes were kept in the RhB solution in the dark for 120 mins to get the adsorption–desorption equilibrium. For studying RhB photodegradation, the maximum UV–Vis absorption peak (553 nm) was selected for concentration monitoring. The total organic carbon (TOC) of the system was measured using a TOC analyser (TOC-VCSH, Shimadzu). The photocatalytic capability was evaluated using phenol (30 mL, 5 mg L−1) as as another model pollutant, and its degradation rate was measured by monitoring absorbance peak at 270 nm. Direct confirmation of the generation of radical species, trapped by 5, 5-dimethyl-1-pyrroline N-oxide (DMPO) was done using an electron spin resonance spectrometer (ESR, Bruker Elexsys A200).Density Functional Theory (DFT) calculation was performed by using the VASP package. The exchange correlation energy was depicted based on generalized gradient approximation by functional of PBE. The plane wave basis set of 550 eV cutoff and spin polarization were used in all calculations. The k-point grids of 2 × 2 × 1 and vacuum space>12 Å were used. The zero damping DFT-D3 dispersion correction method of Grimme was applied to illustrate the van der Waals (VdW) interactions of the system. The tolerance convergence accuracy with the total energy less than 2.0 × 10−5 eV/atom was set, the maximum force on per atom was less than 0.01 eV/nm. The charges transferred in the system was computed by Bader charge analysis.a displays the fabrication process of MAP hydrogel membrane. Typically, Ti3C2Tx MXene colloid dispersion was firstly prepared though selective etching of Al layers from the Ti3AlC2 phase (), followed by being exfoliated in DI water under ultrasonication (). Then, the optimized amount of PVA and porphyrin () was added to MXene colloid dispersion, yielding a stable MAP hydrogel membrane after a filtration process. The self-stacking Ti3C2Tx serves as efficient structure-directing based on abundant molecular interactions during the assembly process. Besides, the flexible PVA acts as effective polymer matrix, which provides sufficient mechanical strength and hydrophilic groups. Also, porphyrin, characterized by the conjugated π-π interactions and ring-shaped distribution of –COOH groups, contributes largely to hydrophilic network as a multifunctional crosslinker and photothermal and photocatalytic activity.b and c, the exfoliated Ti3C2Tx nanosheets demonstrates an interlayer distance of approximately 14.8 Å. The slightly broadened interlayer spacing provides abundant channels for the water transport. As shown in the SEM image (d and inset), the MAP hydrogel membrane at dry state displays a relatively smooth surface topology with porphyrin uniformly distributed within interlayers. The membrane had an observed average thickness of ∼ 12.0 μm, with abundant inter-layered channels created by the stacking of MXene nanosheets. In addition, the elemental mapping of MAP hydrogel membrane shows a uniform distribution of C, Ti, and N (e), further verifying the homogeneous distribution of porphyrin and MXene. Also, the swelling behaviour of MAP hydrogel membrane is schematically illustrated in f, and the corresponding images of membranes before and after swelling were shown in g and the inset. The membrane area increased from 4.15 cm2 in the dry state to 9.62 cm2 in the swollen state, indicating a favourable hydrophilic network. Especially, the sufficient water transport channels and good hydrophilicity of hydrogel membrane can be further verified by the SEM image of sample freeze-dried at swollen state (h), initial contact angle (55.1°, inset of a, the characteristic peaks corresponding to (2 0 0) planes of MXene demonstrates a low angle shift in comparison with control MXene (), indicating a broaden interlayer spacing. This interlayer spacing can be further broadened after fully swelling in water, while still maintains a stable structure. Further evidence can be obtained by the OCT images (b), in which MAP hydrogel membrane displays stable structure with much more green pixels at swollen state, compared with the original state. The swelling behaviour and hydrophilicity of the MAP hydrogel membrane in DI water was investigated. exhibits a good water absorption dynamic and a swelling equilibrium ratio of about 85.0 % in 60 mins, which is equivalent to a high-water absorption rate of 21.6 kg m-2h−1. In comparison, the control MXene membrane exhibits much slower swelling behaviour with low swelling ratio of 30.0 %, which cannot be classified as hydrogel membrane.In addition, the structural interactions of MAP hydrogel membrane were characterized by XPS spectra. shows MAP hydrogel membrane displays the characteristic peaks of Ti3C2Tx, corresponding to the C–Ti (281.7 eV) and O–Ti (529.5 eV). Further, more characteristic peaks of C = O (285.9 eV) and O = C (531.9 eV) can be detected, related to the –COOH group of porphyrins. Besides, the FTIR-ATR spectra () exhibit the characteristic peaks of Ti-C, Ti-O, Ti-F, and C-F bonds that related to Ti3C2Tx MXene, as well as a red shift of C-O, –COO-, and C = O bonds as a result of the strong interactions generated in MAP. Taking advantage of these strong molecular interactions between porphyrin and MXene, the MAP assures stable structure with enabled electron density shift and enhanced localized electric field. The increased local electric fields of MAP can be well illustrated by the enhanced Raman signals (f), which reveals enhanced characteristic peaks at 399.3 and 620.8 cm−1, corresponding to the Eg group vibrations of Ti, C and the surface functional groups. Peaks assigned to D band (1320 cm−1) and G band (1570 cm−1) that related to the highly disordered (amorphous) carbon structure and defects, are also greatly increased in the MAP at the presence of porphyrin. Noted that these abundant interactions of MAP simultaneously ensure a stable mechanical property, exhibiting a high tensile strength of 68.2 ± 2 MPa, with a Young modulus of 31.2 ± 1 MPa (To evaluate the solar absorption ability of membranes, UV–Vis-NIR absorption and reflection spectra were measured (). All the MXene based membranes display the distinct absorption of Ti3C2Tx, which consist of two characteristic strong absorption peaks centred at 610 nm and 1148 nm. These absorptions fit well with the AM 1.5G solar spectrum and covers the UV–Vis-NIR region, which could harvest the maximum amount of distributed light energy of the sun. Moreover, the MAP exhibits much stronger and broader bandwidth of solar absorption compared with the control MXene membrane. This is mainly due to the enhanced absorption in UV–vis bandwidths (≤600 nm), and absorption in the high near-infrared bandwidths (≥1148 nm) after coupling with porphyrin. As a result, the MAP was endowed with outstanding photothermal effect, which can be further quantified in terms of the temperature increase under one-sun illumination (1.0 kW m−2). As shown in b, the surface temperature of MAP increases rapidly to 60. 4 °C in 60 s, much higher than that of control MXene membrane (40.9 °C). Accordingly, the same trend can be verified by the surface temperature profiles as a function of time (c). Especially, the highest ΔT of MAP is 39.3 °C after 5 mins, which is nearly 1.6 times that of MXene (24.6 °C), indicating largely enhanced photothermal conversion.The efficient photothermal effect of MAP is largely attributable to the synergistic effects of MXene and porphyrin, which generate coupling physicochemical environment based on plasmonic MXene and the π-conjugated porphyrin. This favourable coupling interactions and charge redistribution can be further illustrated by density functional theory (DFT) calculations. According to difference charge distribution map (d-f), the yellow isosurface surrounding porphyrin and between the interface of porphyrin-MXeen layer demonstrates strong positive charge accumulation, while the blue isosurface appears near the top of MXene layer exhibts the charge depletion, indicating significant charge redistribution. Based on the Bader analysis results, there are approximately 4.4 electrons transfered from Ti3C2Tx to per porphyrin molecule. Moreover, the calculated projected density of states (PDOS) of porphyrin-MXene system (g) exhibits greatly increased electron states and a high value of local states across the Fermi level, further indicating enhanced electron motilities and metallic behaviour.Fundamentally, taking advantaging of the coupling physicochemical environment, the conjugated porphyrin ring could behave as the electron collector and antenna, which contributes to photothermal conversion and generation of high-energy state of photoinduced charge. Moreover, the unique plasmonic MXene could enable the high-density metal-like free electron to induce the localized surface plasmon resonances generation in forms of collective oscillation of photoexcited hot electrons. It therefore not only imparts efficient localized photothermal heating, but also promotes the transfer dynamic of active photon carriers for enhanced photocatalytic capability h, the band gaps of membrane were calculated based on the extrapolation of the linear range obtained from modified Kubelka–Munk function [A(hν)]2 versus photon energy (hν). MAP exhibits a band gap (Eg) narrowing (1.0 eV) compared with the control MXene (1.25 eV), which could absorb more photons with higher energy greater than the bandgap value, indicating more efficient photocatalytic activity.On one hand, solar-driven evaporation performance was evaluated using a lab-designed solar-thermal device () under one-sun irradiation. During test, the membrane, which had a thermal conductivity of 6.5 W m−1 K−1, was placed on top of a piece of cotton cloth-wrapped polystyrene foam that could float on top of the solution as a thermal insulator and support. a shows the surface temperature monitored using an IR camera. The MAP hydrogel membrane demonstrates a rapid increase of temperature within 10 min and reaches a steady state at about 41.8 °C after 60 mins, which is much higher than that of the bulk water (29.6 °C). The corresponding time-dependent IR images (Inset of a) further verify this temperature increase process. b and c shows the time-dependent mass changes within 120 mins. Results shows that the evaporation rate of MAP hydrogel membrane is as high as 1.82 kg m−2 |
h−1, which is about 1.5 times and 6 times of that of MXene membrane and bulk water, respectively. Additionally, the solar-to-vapour conversion efficiency (η) of the MAP hydrogel membrane was calculated based on the following Equation: where ṁ denotes the evaporation rate under illumination, |
hLV |
represents the apparent liquid–vapor phase change enthalpy (including the sensible heat Hs and phase change enthalpy Hv), and |
qi |
is the solar illumination. Like the hydrogel materials, the apparent enthalpy of the hydrogel membrane was evaluated based on the darkness experiment with pure water, which exhibited an evaporation rate of 0.086 and 0.156 kg m−2 |
h−1, respectively (). Therefore, the MAP20 hydrogel membrane exhibited a η value of 73.5%. The outstanding solar evaporation performance is largely attributable to the superior features of the hydrogel membrane, which not only assures efficient photothermal conversion for heat localization, but also provides a stable hydrophilic network for continuous water pumping.On the other hand, photocatalytic capability was first evaluated based on a photodegradation experiment using RhB solution as a typical model pollutant. d shows the UV–vis absorption spectra of RhB solution as function of time during photodegradation at present of MAP hydrogel membrane. The typical absorbance peak for RhB (554 nm) which is proportional to the concentration, gradually decreases due to the degradation of RhB. Moreover, the degradation dynamics were calculated based on the following equation:where Co and Ct are the concentrations of dye at time 0 and t, respectively. e exhibits that photodegradation of RhB at the presence of the MAP drops rapidly from 1 to about 0.095, indicating a high degradation efficiency of 90.5 %. It is much higher than that of control MXene membrane (76.0 %) and the blank RhB solution without any photocatalyst (4.5%). Moreover, the long-term cycling test () further verifies good photocatalytic stability and reusability of the MAP. Considering photothermal conversion occurs concurrently with the photocatalysis process, which induces a temperature increase in the system, photodegradation process under a constant temperature, controlled by cooling water (25 °C), was also studied for comparison. As expected, e shows that both MAP and MXene membrane under a constant cooling temperature of 25 °C demonstrate a relatively lower degradation efficiency, which in turns indicates strong photothermal effect on photocatalytic capability.We further evaluate the photocatalytic efficiency based on the pseudo-first-order model according to the following equation:where k is related to the photodegradation rate constant. As shown in f, the value of k for MAP is about 0.0116 min−1, which is much higher than that of the control MXene (0.0072 min−1) and for the blank RhB solution (0.0002 min−1). Particularly, when compared with the k values obtained at constant temperature (25 °C, 0.0036 min−1), the MAP demonstrates a photodegradation rate enhancement of 222.2 %. It can also be noted that the relationship between ln(C0/C) and t is not so linear as the slope increases for MAP, indicating a photothermal-enhanced photocatalytic capability. Meanwhile, the MAP hydrogel membrane demonstrates a TOC removal efficiency of 81.2% (), indicating good mineralization performance. Also, when treating a phenol solution as the typical pollution, a degradation efficiency of 72.2% was achieved (The photocatalytic mechanism process of RhB can be summarized in the following steps (1–5). Specifically, the ESR spectra of the MAP () indicates the generation of the hydroxyl radicals (·OH–) and the superoxide radicals (·O2–) during the photocatalytic reaction in the system The synergetic process of MAP hydrogel membrane during water purification can be illustrated in g. Combing with the DFT calculation in Part 3.3, MXene, by virtue of its unique metal-like electronic structure and plasmonic effect, plays the base role to absorb sunlight, induce localized photothermal heating, and generate active species for photocatalytic functions. Moreover, coupling with the conjugated porphyrin enables MXene hydrogel membrane a preferred photothermal and photocatalyst medium to induce more efficient localized photothermal heating and accelerate dynamic and efficiency of photoexcitation for enhanced photocatalytic capability. Therefore, the MAP hydrogel membrane demonstrates great potential for integrated water purification by solar-driven evaporation and photodegradation. Under one-sun irradiation, the setup could generate 1.82 kg m−2 |
h−1 freshwater by evaporation and achieves 10.5 kg m−2 |
h−1 by wastewater purification photodegradation. According to , the color of the treated solution is initially dark pink, which fades gradually during the photocatalysis process, while the water produced by solar evaporation is totally transparent. This efficient photodegradation performance in turn endows the MAP membrane with good self-cleaning performance and ensures stable long-term evaporation stability (). The well-maintained structural and functional stability can be verified by the XRD, SEM and UV–vis-NIR result after long term testing (), further indicating its good chemical of MXene. In addition to the wastewater, the MAP hydrogel membrane also works well in real seawater (3.5 wt%, Science Park, Kong), exhibiting a stable water evaporation rate of 1.72 ± 0.4 kg m-2h−1 (). The salt-rejection behaviour is largely attributed to the excellent hydrophilic network of the hydrogel membrane which imparts it with an efficient capillarity force, osmotic expansion effect, and transpiration effect, which allows the concentrated salt could diffuse down back into the bulk water and avoid salt precipitation [62]. The TOC values decrease from the original 56.616 ppm to 1.303 ppm in the condensed water by evaporation and 9.488 ppm in the degradation water by photodegradation, respectively. However, currently it is not much suitable for high salinity seawater desalination due to salt-deposition without other assisting strategies, i.e., structural optimization or salt crystallization inhibition.In conclusion, we have demonstrated a feasible fabrication of MXene hydrogel membrane based on the structure-directing role of self-stacking MXene nanosheets and its molecular interactions with porphyrin and polyvinyl alcohol, for efficient integrated water purification. Taking advantage of the coupling interactions and charge redistribution between MXene and porphyrin, the hydrogel membrane was endowed with fascinating physicochemical properties combining stable hydrophilic dynamic networks, synergistically enhanced photothermal effect, and photothermal-enabled photocatalytic activity. When evaluated for water purification process, the hydrogel membrane exhibited outstanding solar-driven water evaporation of 1.82 kg m−2 |
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Stress Engineering Literature
This dataset is a compilation of research articles that contain information on stress strain properties. The articles were scraped from the publishers Elsevier, Springer Nature, and Wiley. The plain text content was extracted using the reader package in ChemDataExtractor.
This resulting text dataset contains approximately 1.2 billion tokens and was used to pre-train domain specific BERT models.
See the associated paper for more details.
Citation:
If you use this model, please cite:
@article{mechbert-kumar2025,
title={MechBERT: Language Models for Extracting Chemical and Property Relationships about Mechanical Stress and Strain},
author={Pankaj Kumar, Saurabh Kabra, Jacqueline M. Cole},
journal={Journal of Chemical Information and Modelling},
doi={10.1021/acs.jcim.4c00857},
year={2025}
}
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Size of the auto-converted Parquet files (First 5GB):
2.39 GB
Number of rows (First 5GB):
1,134,477
Estimated number of rows:
1,794,912