ArticleNature communications2026
Mechanical hysterons with tunable interactions of general sign.
Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Collective behavior and memory states in flow networks with tunable bistability.Nature communications · 2026Article
- Hysteretic slit-snapping and multistability in buckled beams with partial cuts.Science advances · 2026Article
- Reprogrammable sequencing for physically intelligent underactuated robots.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Transition graphs of interacting hysterons: structure, design, organization and statistics.Royal Society open science · 2025Article
- Generalizing multiple memories from a single drive: The hysteron latch.Science advances · 2025Article
Corrections and comments
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Authors and funding
1 author.
Funding
Abstract
Hysterons are elementary units of hysteresis that underlie many complex behaviors of non-equilibrium matter. Because models of interacting hysterons can describe disordered matter, this suggests that artificial systems could respond to mechanical inputs in precise and targeted ways. Specifying the properties of hysterons and their interactions could thus be a general method for realizing arbitrary non-equilibrium behaviors. Elastic structures including slender beams, creased sheets, and shells are clear candidates for artificial hysterons, but complete control of their interactions has seemed impractical or impossible. Here we report a mechanical hysteron composed of rigid bars and linear springs, which has controllable properties and tunable interactions of general sign that can be reciprocal or non-reciprocal. We derive a mapping from the system parameters to the hysteron properties, and we show how collective behaviors of multiple hysterons can be targeted by adjusting geometric parameters on the fly. By transforming an abstract hysteron model into a physical design platform, our work demonstrates a route toward designed materials that can sense, compute, and respond to their mechanical environment.
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Registered trials
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