Encoding reprogrammable properties into magneto-mechanical materials via topology optimization  

作　　者：Zhi Zhao Xiaojia Shelly Zhang 

机构地区：[1]Department of Civil and Environmental Engineering,University of Illinois Urbana-Champaign,Urbana,IL,USA [2]Department of Mechanical Science and Engineering,University of Illinois Urbana-Champaign,Urbana,IL,USA

出　　处：《npj Computational Materials》2023年第1期1770-1780,共11页计算材料学（英文）

基　　金：The authors acknowledge the financial support from the U.S.National Science Foundation(NSF)CAREER Award(CMMI-2047692);the U.S.Defense Advanced Research Projects Agency(DARPA)Young Faculty Award(N660012314013).

摘　　要：The properties of materials and structures typically remain fixed after being designed and manufactured.There is a growing interest in systems with the capability of altering their behaviors without changing geometries or material constitutions,because such reprogrammable behaviors could unlock multiple functionalities within a single design.We introduce an optimization-driven approach,based on multi-objective magneto-mechanical topology optimization,to design magneto-active metamaterials and structures whose properties can be seamlessly reprogrammed by switching on and off the external stimuli fields.This optimized material system exhibits one response under pure mechanical loading,and switches to a distinct response under joint mechanical and magnetic stimuli.We discover and experimentally demonstrate magneto-mechanical metamaterials and metastructures that realize a wide range of reprogrammable responses,including multi-functional actuation responses,adaptable snap-buckling behaviors,switchable deformation modes,and tunable bistability.The proposed approach paves the way for promising applications such as magnetic actuators,soft robots,and energy harvesters.

关 键 词：DEFORMATION optimization TOPOLOGY 

分 类 号：TG14[一般工业技术—材料科学与工程]