Digitally programmable kirigami metamaterials via magnetic encoding

Q Qinlian Kang (State Key Laboratory of Surface Physics and International Institute for Intelligent Nanorobots and Nanosystems,College of Intelligent Robotics and Advanced Manufacturing, Fudan University 1 , Shanghai 200438,) J Jinbo Yang (Institute of Condensed Matter and Material Physics, School of Physics) C Chenyang Ji (State Key Laboratory of Surface Physics and International Institute for Intelligent Nanorobots and Nanosystems,College of Intelligent Robotics and Advanced Manufacturing, Fudan University 1 , Shanghai 200438,) Z Zhijun Lin S Songyu Xiong (State Key Laboratory of Surface Physics and International Institute for Intelligent Nanorobots and Nanosystems,College of Intelligent Robotics and Advanced Manufacturing, Fudan University 1 , Shanghai 200438,) Y Yongfeng Mei (International Institute of Intelligent Nanorobots and Nanosystems & State Key Laboratory of Surface Physics, College of Intelligent Robotics and Advanced Manufacturing, Fudan University) J Jizhai Cui (International Institute of Intelligent Nanorobots and Nanosystems & State Key Laboratory of Surface Physics, College of Intelligent Robotics and Advanced Manufacturing, Fudan University)

Abstract

The vast configuration space of magnetic metamaterials, enabled by embedding reversibly orientable magnets into rotating-square kirigami pixels, remains largely unexplored beyond uniform magnetization patterns. To navigate this space, in-plane magnetic orientations are treated as binary bits, creating 2N×N possible states for an N×N lattice. A Monte Carlo approach, combined with a mapping of all configurations onto an N2-dimensional hypercube, allows for the systematic statistical enumeration of energy landscapes and single-bit reconfiguration paths. This framework classifies stability into neutral, monostable, bistable, and tristable classes, with occurrence probabilities converging to approximately 0, 0.6013, 0.3981, and 0.0006 as system size increases. Programmable responses—including tension–compression asymmetric stiffness, snap-through instability, and a two-stage absorption/locking energy dissipation mode—are demonstrated. The resulting digital, graph-based platform points to applications in soft modular robotics, impact-mitigation layers, deployable structures, and mechanical logic.

Article Details

Volume / Issue Vol. 128, Issue 15
Published April 13, 2026
ISSN 0003-6951
Publisher American Institute of Physics

Journal Info

Applied Physics Letters

American Institute of Physics

ISSN: 0003-6951 Physical Sciences

Authors (7)

Q

Qinlian Kang

State Key Laboratory of Surface Physics and International Institute for Intelligent Nanorobots and Nanosystems,College of Intelligent Robotics and Advanced Manufacturing, Fudan University 1 , Shanghai 200438,

J

Jinbo Yang

Institute of Condensed Matter and Material Physics, School of Physics

C

Chenyang Ji

State Key Laboratory of Surface Physics and International Institute for Intelligent Nanorobots and Nanosystems,College of Intelligent Robotics and Advanced Manufacturing, Fudan University 1 , Shanghai 200438,

Z

Zhijun Lin

S

Songyu Xiong

State Key Laboratory of Surface Physics and International Institute for Intelligent Nanorobots and Nanosystems,College of Intelligent Robotics and Advanced Manufacturing, Fudan University 1 , Shanghai 200438,

Y

Yongfeng Mei

International Institute of Intelligent Nanorobots and Nanosystems & State Key Laboratory of Surface Physics, College of Intelligent Robotics and Advanced Manufacturing, Fudan University

J

Jizhai Cui

International Institute of Intelligent Nanorobots and Nanosystems & State Key Laboratory of Surface Physics, College of Intelligent Robotics and Advanced Manufacturing, Fudan University