Dome‐Patterned Metamaterial Sheets

Abstract

The properties of conventional materials result from the arrangement of and the interaction between atoms at the nanoscale. Metamaterials have shifted this paradigm by offering property control through structural design at the mesoscale, thus broadening the design space beyond the limits of traditional materials. A family of mechanical metamaterials consisting of soft sheets featuring a patterned array of reconfigurable bistable domes is reported here. The domes in this metamaterial architecture can be reversibly inverted at the local scale to generate programmable multistable shapes and tunable mechanical responses at the global scale. By 3D printing a robotic gripper with energy-storing skin and a structure that can memorize and compute spatially-distributed mechanical signals, it is shown that these metamaterials are an attractive platform for novel mechanologic concepts and open new design opportunities for structures used in robotics, architecture, and biomedical applications.

Exploiting Mechanical Instabilities in Soft Robotics: Control, Sensing, and Actuation

“…[16] Moreover, because of the compliance of the materials commonly used in their fabrication, the bodies of soft robots lend themselves as an ideal platform to benefit from morphological computation capabilities emerging from the complex interactions of the physical body of the robot with the environment. [17][18][19][20][21][22] Unfortunately, the range of actuation forces accessible to entirely soft machines, remains narrow as they cannot exploit well-known force amplification and motion transferring strategies requiring rigid mechanisms, such as motors, hinges, or motion transmitters (gears, axles, etc.). Additionally, as soft robotic motion is mostly based on deformation, the speed of actuation of soft machines is significantly limited by the rate of deformation and elastic recovery of their compliant body.…”

Recent Progress in Active Mechanical Metamaterials and Construction Principles

“…By adjusting the combination of materials or the curvature of the structures, various metamaterials with adjustable thermal expansion coefficients can be obtained. It has been discussed in Sections 2.1.2 [ 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 ,…”

“…If implanting a set of elaborately designed energy transfer and storage mechanisms into the metamaterials, the metamaterials would behave “smart,” and realize various functions comparable to the activity of life‐like bodies. Based on this principle, a large number of new functions could be extended such as, active shape‐shifting, [ 34 , 35 , 36 ] programmable mechanical properties, [ 37 , 38 , 39 ] elastic wave propagation control, [ 40 , 41 ] and mobility. [ 42 , 43 , 44 ] AMMs is an emerging subject that continues to develop with mechanical design and material science, and has huge application prospects in engineering and science.…”

Non-orientable order and non-Abelian response in frustrated metamaterials

“…We now show that the topologically protected zerodeformation nodes and lines realise the elementary units of robust mechanical memory based on non-Abelian response. Storing, reading and erasing mechanical informa-tion require the deformations to depend on the history of the loading sequence [5][6][7][8][9][10][11][12]. One strategy consists in applying multiple loads to a material having a non-Abelian response, deformations that depends on the sequential order of the loads.…”

“…Our metamaterials escape the traditional classification of order by symmetry breaking. Considering more general stress distributions, we leverage non-orientable order to engineer robust mechanical memory [5][6][7][8][9][10][11] and achieve non-Abelian mechanical responses that carry an imprint of the braiding of local loads [12,13]. We envision this principle to open the way to designer materials that can robustly process information across multiple areas of physics, from mechanics to photonics and magnetism.…”