Automatic design of mechanical metamaterial actuators.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
20 08 2020
20 08 2020
Historique:
received:
20
12
2019
accepted:
23
07
2020
entrez:
22
8
2020
pubmed:
21
8
2020
medline:
21
8
2020
Statut:
epublish
Résumé
Mechanical metamaterial actuators achieve pre-determined input-output operations exploiting architectural features encoded within a single 3D printed element, thus removing the need for assembling different structural components. Despite the rapid progress in the field, there is still a need for efficient strategies to optimize metamaterial design for a variety of functions. We present a computational method for the automatic design of mechanical metamaterial actuators that combines a reinforced Monte Carlo method with discrete element simulations. 3D printing of selected mechanical metamaterial actuators shows that the machine-generated structures can reach high efficiency, exceeding human-designed structures. We also show that it is possible to design efficient actuators by training a deep neural network which is then able to predict the efficiency from the image of a structure and to identify its functional regions. The elementary actuators devised here can be combined to produce metamaterial machines of arbitrary complexity for countless engineering applications.
Identifiants
pubmed: 32820158
doi: 10.1038/s41467-020-17947-2
pii: 10.1038/s41467-020-17947-2
pmc: PMC7441157
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
4162Références
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