General-purpose mechanical computing enabled by origami circuit reconfiguration with robotic addressing and activation

Inspired by information sensing, storage, and processing capabilities of natural systems, mechanical computing built upon intelligent matters is emerging toward directly perceiving environmental changes and making autonomous decisions. However, challenges remain in achieving general-purpose mechanical computing architecture due to the trade-off between programmability and scalability. Here, we present a mechanical programmable gate array, a scalable architecture integrating dynamic activation mechanisms for general-purpose computing. By mapping local factored Quine-McCluskey logic functions onto bistable origami switch-based logic units and embedding conductive networks, we create low-redundancy, high-stability logic modules. A robotic activation mechanism, guided by magnetic instructions, dynamically configures the logic array for all input combinations, ensuring complete programmability and scalability. The architecture also interfaces with storage units for iterative processes like function reuse and neural network weight updates. With programmability, scalability, and adaptability, this approach lays the foundation for decision-making materials with applications spanning distributed edge computing and embodied intelligent robotics.

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Publication Details

Journal
Nature Communications
Published
2025-11-25
DOI
https://doi.org/10.1038/s41467-025-65464-x
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00

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article

General-purpose mechanical computing enabled by origami circuit reconfiguration with robotic addressing and activation

Ting Tan, Zhimiao Yan, Yinghua Chen
Nature Communications
Advanced Memory and Neural Computing
article

General-purpose mechanical computing enabled by origami circuit reconfiguration with robotic addressing and activation

Ting Tan, Zhimiao Yan, Yinghua Chen
article en

Abstract

Inspired by information sensing, storage, and processing capabilities of natural systems, mechanical computing built upon intelligent matters is emerging toward directly perceiving environmental changes and making autonomous decisions. However, challenges remain in achieving general-purpose mechanical computing architecture due to the trade-off between programmability and scalability. Here, we present a mechanical programmable gate array, a scalable architecture integrating dynamic activation mechanisms for general-purpose computing. By mapping local factored Quine-McCluskey logic functions onto bistable origami switch-based logic units and embedding conductive networks, we create low-redundancy, high-stability logic modules. A robotic activation mechanism, guided by magnetic instructions, dynamically configures the logic array for all input combinations, ensuring complete programmability and scalability. The architecture also interfaces with storage units for iterative processes like function reuse and neural network weight updates. With programmability, scalability, and adaptability, this approach lays the foundation for decision-making materials with applications spanning distributed edge computing and embodied intelligent robotics.

Nature CommunicationsVol. 16(1)
Shanghai Jiao Tong University (CN), Shanghai Ocean University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 64%
Advanced Memory and Neural Computing
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General-purpose mechanical computing enabled by origami circuit reconfiguration with robotic addressing and activation — Ting Tan, Zhimiao Yan, et al. · Nature Communications (2025) | TGRS Research Map | TGRS