为研究变密度结构设计对三维机织角联锁复合材料面外力学性能的影响,设计制备了三维机织角联锁不变密度复合材料、三维机织角联锁经纱变密度复合材料和三维机织角联锁纬纱变密度复合材料。结合扫描电子显微镜、数字图像相关技术和X射线...为研究变密度结构设计对三维机织角联锁复合材料面外力学性能的影响,设计制备了三维机织角联锁不变密度复合材料、三维机织角联锁经纱变密度复合材料和三维机织角联锁纬纱变密度复合材料。结合扫描电子显微镜、数字图像相关技术和X射线计算机断层扫描等检测技术,对角联锁变密度复合材料的面外压缩力学行为、内部损伤量化和渐进损伤等进行了测试与表征。研究结果表明:上疏下密角联锁纬纱变密度复合材料展现出优异的压缩性能,其压缩比强度比不变密度复合材料高3.40%;同时,上疏下密角联锁纬纱变密度复合材料损伤体积仅为11.64 mm 3,远低于不变密度复合材料的26.90 mm 3。进一步分析得到,不变密度复合材料压缩破坏以剪切失效为主,而上疏下密角联锁纬纱变密度复合材料则为基体开裂。展开更多
Structural connections between components are often weak areas in engineering applications.In nature,many biological materials with remarkablemechanical performance possess flexible and creative sutures.In this work,w...Structural connections between components are often weak areas in engineering applications.In nature,many biological materials with remarkablemechanical performance possess flexible and creative sutures.In this work,we propose a novel bioinspired interlocking tab considering both the geometry of the tab head and neck,and demonstrate a new approach to optimize the bio-inspired interlocking structures based on machine learning.Artificial neural networks for different optimization objectives are developed and trained using a database of thousands of interlocking structures generated through finite element analysis.Results show that the proposed method is able to achieve accurate prediction of the mechanical response of any given interlocking tab.The optimized designs with different optimization objectives,such as strength,stiffness,and toughness,are obtained efficiently and precisely.The optimum design predicted by machine learning is approximately 7.98 times stronger and 2.98 times tougher than the best design in the training set,which are validated through additive manufacturing and experimental testing.The machine learning-based optimization approach developed here can aid in the exploration of the intricate mechanism behind biological materials and the discovery of new material designs boasting orders of magnitude increase in computational efficacy over conventional methods.展开更多
Two-dimensional(2D)materials have attracted considerable interest thanks to their unique electronic/physical-chemical characteristics and their potential for use in a large variety of sensing applications.However,few-...Two-dimensional(2D)materials have attracted considerable interest thanks to their unique electronic/physical-chemical characteristics and their potential for use in a large variety of sensing applications.However,few-layered nanosheets tend to agglomerate owing to van der Waals forces,which obstruct internal nanoscale transport channels,resulting in low electrochemical activity and restricting their use for sensing purposes.Here,a hybrid MXene/rGO aerogel with a three-dimensional(3D)interlocked network was fabricated via a freeze-drying method.The porous MXene/rGO aerogel has a lightweight and hierarchical porous architecture,which can be compressed and expanded several times without breaking.Additionally,a flexible pressure sensor that uses the aerogel as the sensitive layer has a wide response range of approximately 0-40 kPa and a considerable response within this range,averaging approximately 61.49 kPa^(-1).The excellent sensing performance endows it with a broad range of applications,including human-computer interfaces and human health monitoring.展开更多
文摘为研究变密度结构设计对三维机织角联锁复合材料面外力学性能的影响,设计制备了三维机织角联锁不变密度复合材料、三维机织角联锁经纱变密度复合材料和三维机织角联锁纬纱变密度复合材料。结合扫描电子显微镜、数字图像相关技术和X射线计算机断层扫描等检测技术,对角联锁变密度复合材料的面外压缩力学行为、内部损伤量化和渐进损伤等进行了测试与表征。研究结果表明:上疏下密角联锁纬纱变密度复合材料展现出优异的压缩性能,其压缩比强度比不变密度复合材料高3.40%;同时,上疏下密角联锁纬纱变密度复合材料损伤体积仅为11.64 mm 3,远低于不变密度复合材料的26.90 mm 3。进一步分析得到,不变密度复合材料压缩破坏以剪切失效为主,而上疏下密角联锁纬纱变密度复合材料则为基体开裂。
基金supported by the National Natural Science Foundation of China,Grant No.51875440.
文摘Structural connections between components are often weak areas in engineering applications.In nature,many biological materials with remarkablemechanical performance possess flexible and creative sutures.In this work,we propose a novel bioinspired interlocking tab considering both the geometry of the tab head and neck,and demonstrate a new approach to optimize the bio-inspired interlocking structures based on machine learning.Artificial neural networks for different optimization objectives are developed and trained using a database of thousands of interlocking structures generated through finite element analysis.Results show that the proposed method is able to achieve accurate prediction of the mechanical response of any given interlocking tab.The optimized designs with different optimization objectives,such as strength,stiffness,and toughness,are obtained efficiently and precisely.The optimum design predicted by machine learning is approximately 7.98 times stronger and 2.98 times tougher than the best design in the training set,which are validated through additive manufacturing and experimental testing.The machine learning-based optimization approach developed here can aid in the exploration of the intricate mechanism behind biological materials and the discovery of new material designs boasting orders of magnitude increase in computational efficacy over conventional methods.
基金financial support from the National Natural Science Foundation of China(NSFC Grant No.61625404,61888102,62174152)Young Elite Scientists Sponsorship Program by CAST(2018QNRC001)+1 种基金the Strategic Priority Program of the Chinese Academy of Sciences,Grant No XDA16021100the Science and Technology Development Plan of Jilin Province(20210101168JC).
文摘Two-dimensional(2D)materials have attracted considerable interest thanks to their unique electronic/physical-chemical characteristics and their potential for use in a large variety of sensing applications.However,few-layered nanosheets tend to agglomerate owing to van der Waals forces,which obstruct internal nanoscale transport channels,resulting in low electrochemical activity and restricting their use for sensing purposes.Here,a hybrid MXene/rGO aerogel with a three-dimensional(3D)interlocked network was fabricated via a freeze-drying method.The porous MXene/rGO aerogel has a lightweight and hierarchical porous architecture,which can be compressed and expanded several times without breaking.Additionally,a flexible pressure sensor that uses the aerogel as the sensitive layer has a wide response range of approximately 0-40 kPa and a considerable response within this range,averaging approximately 61.49 kPa^(-1).The excellent sensing performance endows it with a broad range of applications,including human-computer interfaces and human health monitoring.
