Active Metamaterials with Tunable Shear Nonreciprocity and Nonlinear Dynamics

Actively and smoothly tunable mechanical metamaterials are in high demand for adaptive, variable-stiffness structures in smart machines. However, existing designs are largely restricted to tunable transverse deformation, reciprocal response, and linear dynamics. Here, we propose a novel gear-based design paradigm-using Taiji planar gears and planetary gear assemblies as building blocks-that overcomes these limitations by enabling simultaneous control of translational and torsional stiffnesses, shear nonreciprocity, and programmable nonlinear dynamics. Our metamaterials achieve in situ, continuous tuning of shear stiffness by 30-100×, break reciprocity under positive versus negative loads, and allow the nonreciprocity ratio to be tuned by over 100×. Meta-resonators constructed from these units showcase an application example exhibit broadly tunable transverse and torsional resonant frequencies. Furthermore, we demonstrate that static nonreciprocity serves as a precise control knob for dynamic nonlinearity-a property traditionally fixed and nearly impossible to tune in conventional materials. Analytical models and analyses elucidate the underlying mechanisms and extendable design freedoms. This work bridges the critical gaps in mechanical metamaterials and dynamics, offering a practical pathway to control both linear and nonlinear structural deformations, elastic waves, and vibrations.

Authors

Institutions

Publication Details

Journal
Advanced Science
Published
2026-03-12
DOI
https://doi.org/10.1002/advs.74736
Primary Topic
Acoustic Wave Phenomena Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Active Metamaterials with Tunable Shear Nonreciprocity and Nonlinear Dynamics

L.M. Cheng, Tao Yu, Dianlong Yu, Xin Fang
Advanced Science
Acoustic Wave Phenomena Research
article

Active Metamaterials with Tunable Shear Nonreciprocity and Nonlinear Dynamics

L.M. Cheng, Tao Yu, Dianlong Yu, Xin Fang
article en

Abstract

Actively and smoothly tunable mechanical metamaterials are in high demand for adaptive, variable-stiffness structures in smart machines. However, existing designs are largely restricted to tunable transverse deformation, reciprocal response, and linear dynamics. Here, we propose a novel gear-based design paradigm-using Taiji planar gears and planetary gear assemblies as building blocks-that overcomes these limitations by enabling simultaneous control of translational and torsional stiffnesses, shear nonreciprocity, and programmable nonlinear dynamics. Our metamaterials achieve in situ, continuous tuning of shear stiffness by 30-100×, break reciprocity under positive versus negative loads, and allow the nonreciprocity ratio to be tuned by over 100×. Meta-resonators constructed from these units showcase an application example exhibit broadly tunable transverse and torsional resonant frequencies. Furthermore, we demonstrate that static nonreciprocity serves as a precise control knob for dynamic nonlinearity-a property traditionally fixed and nearly impossible to tune in conventional materials. Analytical models and analyses elucidate the underlying mechanisms and extendable design freedoms. This work bridges the critical gaps in mechanical metamaterials and dynamics, offering a practical pathway to control both linear and nonlinear structural deformations, elastic waves, and vibrations.

Advanced Science
Hong Kong Polytechnic University (HK), National University of Defense Technology (CN)
Openalex Percentile: Top 24%
Acoustic Wave Phenomena Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.