首页|Study Data from Guangxi University Provide New Insights into Machine Learning (M achine Learning-accelerated Inverse Design of Programmable Bi-functional Metamat erials)
Study Data from Guangxi University Provide New Insights into Machine Learning (M achine Learning-accelerated Inverse Design of Programmable Bi-functional Metamat erials)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Machine Learning is now available. According to news reporting from Nanning, People’s Republic of China , by NewsRx journalists, research stated, “Bi-functional metamaterials with prog rammable coefficients of thermal expansion (CTEs) and Poisson’s ratios (PRs) hav e garnered significant attention among researchers due to the ability to manifes t desired deformations under thermal and mechanical loads. Nevertheless, a curre nt challenge lies in efficiently achieving the inverse design of these metamater ials to meet diverse application requirements.” Financial supporters for this research include National Natural Science Foundati on of China (NSFC), The 2024 Open Project of Failure Mechanics and Engineering D isaster Prevention, Key Lab of Sichuan Province. The news correspondents obtained a quote from the research from Guangxi Universi ty, “This paper presents a machine learning (ML) model that can establish a logi cal mapping relationship between geometric/ material parameters and mechanical pr operties, and it is applied to the inverse design of bi-functional metamaterials with desired CTEs and PRs. Furthermore, the inverse design capability of the ML model was validated by the finite element analysis and experimental test. The r esults demonstrate that the geometric models obtained from the inverse predictio n can effectively exhibit the desired deformation behavior under thermal and mec hanical loads.”
NanningPeople’s Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine LearningGuangxi University
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