A physical adaptive material motor unit neural network: a hygromorph composite material machine
Advances in novel materials science enable structures to function as intelligent machines by embedding memory and learning capabilities directly into materials. Our work introduces a physical adaptive material motor unit neural network,leveraging a new generation of controllable actuators composed of wood- and carbon black-based composites, sensitive to temperature and relative humidity. These material actuators are assembled into a motor unit-like structure inspired by muscle contraction trigger, forming an intelligent machine capable of dynamic shading control that can be used, for example, in buildings. The machine is governed by a neural network trained on over 350 experimental data p...
| Authors | Charles de Kergariou, David Correa, Adam W. Perriman et al. |
|---|---|
| Primary category | cs.ET |
| Published | 5 June 2026 |
| Last updated at source | 5 June 2026 |
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