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Mechanical Metamaterials with Reprogrammable Sequential Deformation for Analog-to-Digital Encoding and Computing
Siyu Yin1, Tie Mei1, Chang Qing Chen1,2
1Department of Engineering Mechanics, CNMM and AML, Tsinghua University, Beijing, People's Republic of China.
Advanced Materials (Deerfield Beach, Fla.)
|August 5, 2026
Summary
This study introduces intelligent mechanical metamaterials that can process continuous stimuli into digital outputs. Reprogrammable sequential deformation allows a single material to perform complex computations, advancing material-based computing.
Area of Science:
- Materials Science
- Computational Mechanics
- Robotics
Background:
- Mechanical metamaterials offer intelligent sensing and response capabilities.
- A key challenge is converting continuous physical inputs into discrete digital outputs.
Purpose of the Study:
- To develop a mechanical metamaterial for digital encoding and computation of continuous stimuli.
- To enable reprogrammable sequential deformation for versatile logic operations.
Main Methods:
- Engineered a multistable architecture exhibiting sequential snap-through events under uniaxial compression.
- Employed an inverse design strategy to tune deformation sequences by adjusting stiffness.
- Demonstrated in situ reprogramming by selectively activating/deactivating constituent units.
Main Results:
- Achieved nearly arbitrary digital encoding and computation of continuous stimuli.
- Showcased mechanical analog-to-digital conversion and signal processing.
- Performed field-programmable gate array (FPGA)-like logic operations using a single material system.
Conclusions:
- The developed metamaterial enables material-based computing through reprogrammable deformation.
- This work presents a promising pathway toward intelligent mechanical metamaterials with advanced computational abilities.
