Abstract

Mechanical metamaterials enable the creation of structural materials with unprecedented mechanical properties. However, thus far, research on mechanical metamaterials has focused on passive mechanical metamaterials and the tunability of their mechanical properties. Deep integration of multifunctionality, sensing, electrical actuation, information processing, and advancing data-driven designs are grand challenges in the mechanical metamaterials community that could lead to truly intelligent mechanical metamaterials. In this perspective, we provide an overview of mechanical metamaterials within and beyond their classical mechanical functionalities. We discuss various aspects of data-driven approaches for inverse design and optimization of multifunctional mechanical metamaterials. Our aim is to provide new roadmaps for design and discovery of next-generation active and responsive mechanical metamaterials that can interact with the surrounding environment and adapt to various conditions while inheriting all outstanding mechanical features of classical mechanical metamaterials. Next, we deliberate the emerging mechanical metamaterials with specific functionalities to design informative and scientific intelligent devices. We highlight open challenges ahead of mechanical metamaterial systems at the component and integration levels and their transition into the domain of application beyond their mechanical capabilities.

Mechanical metamaterials are known for their unconventional mechanical properties. In this perspective, the authors give an overview of the current state of mechanical materials research and suggest a roadmap for next-generation active and responsive mechanical metamaterials.

Details

Title
Mechanical metamaterials and beyond
Author
Jiao, Pengcheng 1 ; Mueller, Jochen 2   VIAFID ORCID Logo  ; Raney, Jordan R. 3   VIAFID ORCID Logo  ; Zheng, Xiaoyu (Rayne) 4   VIAFID ORCID Logo  ; Alavi, Amir H. 5   VIAFID ORCID Logo 

 Zhejiang University, Ocean College, Zhoushan, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X) 
 Johns Hopkins University, Department of Civil and Systems Engineering, Baltimore, USA (GRID:grid.21107.35) (ISNI:0000 0001 2171 9311) 
 University of Pennsylvania, Department of Mechanical Engineering and Applied Mechanics, Philadelphia, USA (GRID:grid.25879.31) (ISNI:0000 0004 1936 8972) 
 University of California, Department of Materials Science and Engineering, Berkeley, USA (GRID:grid.47840.3f) (ISNI:0000 0001 2181 7878) 
 University of Pittsburgh, Department of Civil and Environmental Engineering, Pittsburgh, USA (GRID:grid.21925.3d) (ISNI:0000 0004 1936 9000); University of Pittsburgh, Department of Bioengineering, Pittsburgh, USA (GRID:grid.21925.3d) (ISNI:0000 0004 1936 9000) 
Pages
6004
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2869100281
Copyright
© The Author(s) 2023. corrected publication 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.