Mechanical cloak via data-driven aperiodic metamaterial design.
Liwei WangJagannadh BoddapatiKe LiuPing ZhuChiara DaraioWei ChenPublished in: Proceedings of the National Academy of Sciences of the United States of America (2022)
SignificanceAn invisibility cloak to conceal objects from an outside observer has long been a subject of interest in metamaterial design. While cloaks have been manufactured for optical, thermal, and electric fields, limited progress has been made for mechanical cloaks. Most existing designs rely on mapping-based methods, which have so far been limited to special base cells and a narrow selection of voids with simple shapes. In this study, we develop a fundamentally different approach by exploiting data-driven designs to offer timely, customized solutions to mechanical cloaking that were previously difficult to obtain. Through simulations and experimental validations, we show that excellent cloaking performance can be achieved for various boundary conditions, shapes of voids, base cells, and even multiple voids.