2024/09/30 by Theophile Louvet, Louvet, Theophile, Parisa Omidvar +3 · 3 citations
Engineering · #Advanced Materials and Mechanics #Emerging Technologies (cs.ET) #FOS: Computer and information sciences #FOS: Physical sciences #Soft Condensed Matter (cond-mat.soft) #Structural Analysis and Optimization
paper · pdf · doi:10.48550/arxiv.2409.20425
openalex publication_date 2024/09/30 · openalex created_date 2024/10/28 · openalex updated_date 2026/07/28
Matrix-vector multiplications are a fundamental building block of artificial intelligence; this essential role has motivated their implementation in a variety of physical substrates, from memristor crossbar arrays to photonic integrated circuits. Yet their realization in soft-matter intelligent systems remains elusive. Here, we experimentally demonstrate a reprogrammable elastic metamaterial that computes matrix-vector multiplications using floppy modes -- deformations with near-zero stored elastic energy. Floppy modes allow us to program complex deformations without being hindered by the natural stiffness of the material; but their practical application is challenging, as their existence depends on global topological properties of the system. To overcome this challenge, we introduce a continuously parameterized unit cell design with well-defined compatibility characteristics. This unit cell is then combined to form arbitrary matrix-vector multiplications that can even be reprogrammed after fabrication. Our results demonstrate that floppy modes can act as key enablers for embodied intelligence, smart MEMS devices and in-sensor edge computing.