The residual stress generated in the manufacturing process of inertial platform causes the drift of inertial platform parameters in long-term storage condition.However,the existing temperature cycling experiment could...The residual stress generated in the manufacturing process of inertial platform causes the drift of inertial platform parameters in long-term storage condition.However,the existing temperature cycling experiment could not meet the increased repeatability technical requirements of inertial platform parameters.In order to solve this problem,in this paper,firstly the Unigraphics（UG） software and the interface compatibility of ANSYS software are used to establish the inertial platform finite element model.Secondly,the residual stress is loaded into finite element model by ANSYS function editor in the form of surface loads to analyze the efficiency.And then,the generation based on ANSYS simulation inertial platform to accelerate the stability of experiment profile is achieved by the application of the analysis method of orthogonal experimental design and ANSYS thermal-structural coupling.The optimum accelerated stability experiment profile is determined finally,which realizes the rapid,effective release of inertial platform residual stress.The research methodology and conclusion of this paper have great theoretical and practical significance to the production technology of inertial platform.展开更多
Since its emergence in 2009,perovskite photovoltaic technology has achieved remarkable progress,with efficiencies soaring from 3.8%to over 26%.Despite these advancements,challenges such as long-term material and devic...Since its emergence in 2009,perovskite photovoltaic technology has achieved remarkable progress,with efficiencies soaring from 3.8%to over 26%.Despite these advancements,challenges such as long-term material and device stability remain.Addressing these challenges requires reproducible,user-independent laboratory processes and intelligent experimental preselection.Traditional trial-and-error methods and manual analysis are inefficient and urgently need advanced strategies.Automated acceleration platforms have transformed this field by improving efficiency,minimizing errors,and ensuring consistency.This review summarizes recent developments in machine learning-driven auto-mation for perovskite photovoltaics,with a focus on its application in new transport material discovery,composition screening,and device preparation optimization.Furthermore,the review introduces the concept of the self-driven Autonomous Material and Device Acceleration Platforms(AMADAP)labora-tory and discusses potential challenges it may face.This approach streamlines the entire process,from material discovery to device performance improve-ment,ultimately accelerating the development of emerging photovoltaic technologies.展开更多
Traditional Chinese Medicine(TCM)has been used in prevention and treatment of disease in clinical practice for thousands of years,with an indispensable role of multiple ingredients.Thus,a rapid and effective chemical ...Traditional Chinese Medicine(TCM)has been used in prevention and treatment of disease in clinical practice for thousands of years,with an indispensable role of multiple ingredients.Thus,a rapid and effective chemical ingredients analysis was of necessary to be established for the evaluation of the holistic quality of TCM.As could afford the data with high resolution and high sensitivity,展开更多
文摘The residual stress generated in the manufacturing process of inertial platform causes the drift of inertial platform parameters in long-term storage condition.However,the existing temperature cycling experiment could not meet the increased repeatability technical requirements of inertial platform parameters.In order to solve this problem,in this paper,firstly the Unigraphics（UG） software and the interface compatibility of ANSYS software are used to establish the inertial platform finite element model.Secondly,the residual stress is loaded into finite element model by ANSYS function editor in the form of surface loads to analyze the efficiency.And then,the generation based on ANSYS simulation inertial platform to accelerate the stability of experiment profile is achieved by the application of the analysis method of orthogonal experimental design and ANSYS thermal-structural coupling.The optimum accelerated stability experiment profile is determined finally,which realizes the rapid,effective release of inertial platform residual stress.The research methodology and conclusion of this paper have great theoretical and practical significance to the production technology of inertial platform.
基金support of“ELF-PV-Design and development of solution processed functional materials for the next generations of PV technologies”(No.44-6521a/20/4)and“Solar Factory of the Future”(FKZ 20.2-3410.5-4-5)by the Bavarian State Governmentthe German Federal Ministry for Economic Affairs and Climate Action(project Pero4PV,FKZ:03EE1092A)+3 种基金SolMAP and SolarTAP-a Technology Acceleration Platform for emerging Photovoltaics project by Helmholtz Associationsupport from the China Scholarship Council(CSC)support from the Sino-German Postdoc Scholarship Program(CSC-DAAD)support from the Villum Foundation,Grant no.50440.Open Access funding enabled and organized by Projekt DEAL.
文摘Since its emergence in 2009,perovskite photovoltaic technology has achieved remarkable progress,with efficiencies soaring from 3.8%to over 26%.Despite these advancements,challenges such as long-term material and device stability remain.Addressing these challenges requires reproducible,user-independent laboratory processes and intelligent experimental preselection.Traditional trial-and-error methods and manual analysis are inefficient and urgently need advanced strategies.Automated acceleration platforms have transformed this field by improving efficiency,minimizing errors,and ensuring consistency.This review summarizes recent developments in machine learning-driven auto-mation for perovskite photovoltaics,with a focus on its application in new transport material discovery,composition screening,and device preparation optimization.Furthermore,the review introduces the concept of the self-driven Autonomous Material and Device Acceleration Platforms(AMADAP)labora-tory and discusses potential challenges it may face.This approach streamlines the entire process,from material discovery to device performance improve-ment,ultimately accelerating the development of emerging photovoltaic technologies.
文摘Traditional Chinese Medicine(TCM)has been used in prevention and treatment of disease in clinical practice for thousands of years,with an indispensable role of multiple ingredients.Thus,a rapid and effective chemical ingredients analysis was of necessary to be established for the evaluation of the holistic quality of TCM.As could afford the data with high resolution and high sensitivity,
