The rapid miniaturization of electronic devices has fueled unprecedented demand for flexible,high-performance sensors across fields ranging from medical devices to robotics.Despite advances in fabrication techniques,t...The rapid miniaturization of electronic devices has fueled unprecedented demand for flexible,high-performance sensors across fields ranging from medical devices to robotics.Despite advances in fabrication techniques,the development of micro-and nano-scale flexible force sensors with superior sensitivity,stability,and biocompatibility remains a formidable challenge.In this study,we developed a novel conductive photosensitive resin specifically designed for two-photon polymerization,systematically optimized its printing parameters,and improved its structural design,thereby enabling the fabrication of high-precision micro-spring force sensors(MSFS).The proposed photosensitive resin,doped with MXene nanomaterials,combines exceptional mechanical strength and conductivity,overcoming limitations of traditional materials.Using a support vector machine model in machine learning techniques,we optimized the polymerizability of the resin under varied laser parameters,achieving a predictive accuracy of 92.66%.This model significantly reduced trial-and-error in the TPP process,accelerating the discovery of ideal fabrication conditions.Finite element analysis was employed to design and simulate the performance of the MSFS,guiding structural optimization to achieve high sensitivity and mechanical stability.The fabricated MSFS demonstrated outstanding electromechanical performance,with a sensitivity coefficient of 5.65 and a fabrication accuracy within±50 nm,setting a new standard for MSFS precision.This work not only pushes the boundaries of sensor miniaturization but also introduces a scalable,efficient pathway for the rapid design and fabrication of highperformance flexible sensors.展开更多
Grinding is one of the most widely used material removal methods at the end of many process chains.Grinding force is related to almost all grinding parameters,which has a great influence on material removal rate,dimen...Grinding is one of the most widely used material removal methods at the end of many process chains.Grinding force is related to almost all grinding parameters,which has a great influence on material removal rate,dimensional and shape accuracy,surface and subsurface integrity,thermodynamics,dynamics,wheel durability,and machining system deformation.Considering that grinding force is related to almost all grinding parameters,grinding force can be used to detect grinding wheel wear,energy calculation,chatter suppression,force control and grinding process simulation.Accurate prediction of grinding forces is important for optimizing grinding parameters and the structure of grinding machines and fixtures.Although there are substantial research papers on grinding mechanics,a comprehensive review on the modeling of grinding mechanics is still absent from the literature.To fill this gap,this work reviews and introduces theoretical methods and applications of mechanics in grinding from the aspects of modeling principles,limitations and possible future trendencies.展开更多
文摘The rapid miniaturization of electronic devices has fueled unprecedented demand for flexible,high-performance sensors across fields ranging from medical devices to robotics.Despite advances in fabrication techniques,the development of micro-and nano-scale flexible force sensors with superior sensitivity,stability,and biocompatibility remains a formidable challenge.In this study,we developed a novel conductive photosensitive resin specifically designed for two-photon polymerization,systematically optimized its printing parameters,and improved its structural design,thereby enabling the fabrication of high-precision micro-spring force sensors(MSFS).The proposed photosensitive resin,doped with MXene nanomaterials,combines exceptional mechanical strength and conductivity,overcoming limitations of traditional materials.Using a support vector machine model in machine learning techniques,we optimized the polymerizability of the resin under varied laser parameters,achieving a predictive accuracy of 92.66%.This model significantly reduced trial-and-error in the TPP process,accelerating the discovery of ideal fabrication conditions.Finite element analysis was employed to design and simulate the performance of the MSFS,guiding structural optimization to achieve high sensitivity and mechanical stability.The fabricated MSFS demonstrated outstanding electromechanical performance,with a sensitivity coefficient of 5.65 and a fabrication accuracy within±50 nm,setting a new standard for MSFS precision.This work not only pushes the boundaries of sensor miniaturization but also introduces a scalable,efficient pathway for the rapid design and fabrication of highperformance flexible sensors.
基金co-supported by the Enterprise Innovation and Development Joint Program of the National Natural Science Foundation of China (No. U20B2032)National Natural Science Foundation of China (No. 51875135)
文摘Grinding is one of the most widely used material removal methods at the end of many process chains.Grinding force is related to almost all grinding parameters,which has a great influence on material removal rate,dimensional and shape accuracy,surface and subsurface integrity,thermodynamics,dynamics,wheel durability,and machining system deformation.Considering that grinding force is related to almost all grinding parameters,grinding force can be used to detect grinding wheel wear,energy calculation,chatter suppression,force control and grinding process simulation.Accurate prediction of grinding forces is important for optimizing grinding parameters and the structure of grinding machines and fixtures.Although there are substantial research papers on grinding mechanics,a comprehensive review on the modeling of grinding mechanics is still absent from the literature.To fill this gap,this work reviews and introduces theoretical methods and applications of mechanics in grinding from the aspects of modeling principles,limitations and possible future trendencies.
