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Peer-reviewedCC BY-NC-ND 4.0Proceedings of the National Academy of Sciences of the United States of America

Origami state machine with time-varying magnetic fields

  • Yifan Rao1
  • Konstantinos Manos2
  • Tuo Zhao3
  • Minjie Chen1,2
  • Glaucio H. Paulino3,4
4 affiliations
  1. 1Andlinger Center for Energy and the Environment, Princeton University, Princeton, NJ 08544
  2. 2Department of Electrical and Computer Engineering, Princeton University, Princeton, NJ 08544
  3. 3Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08544
  4. 4Princeton Materials Institute, Princeton University, Princeton, NJ 08544
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Abstract

Achieving reliable, remote control over multiple stable states in modular systems remains a challenge due to the coupling between modules and history-dependent transitions. Here, we present magnetic origami state machines that enable deterministic navigation from any unknown initial state to any target state under magnetic actuation. By assuming mutually distinct energy barriers in modular Kresling origami assemblies, we realize fully accessible transition graphs with scalable state spaces. Guided by the graph associated to the state machine, a rotating magnetic field induces a universal reset that autonomously drives the system to a known equilibrium state from arbitrary states without sensing or feedback, while pulsed magnetic inputs further enable programmable transitions to any target state via prescribed actuation sequences. A reduced-order Lagrangian mechanics model predicts snap-through dynamics across reset, stepwise programming (between graph nodes), and shortcuts (by adapting pulse magnitude and orientation) where inertia triggers simultaneous multicell transitions with a single pulse. These results establish a general framework for programmable magneto-mechanical state machines with autonomous state reset and full state-space control.

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Cite

BibTeXRIS
BibTeX
@article{rao2026origami,
  title = {{Origami state machine with time-varying magnetic fields}},
  author = {Yifan Rao and Konstantinos Manos and Tuo Zhao and Minjie Chen and Glaucio H. Paulino},
  journal = {Proceedings of the National Academy of Sciences of the United States of America},
  year = {2026},
  month = oct,
  doi = {10.1073/pnas.2615316123},
  url = {https://doi.org/10.1073/pnas.2615316123},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - JOUR
TI  - Origami state machine with time-varying magnetic fields
AU  - Yifan Rao
AU  - Konstantinos Manos
AU  - Tuo Zhao
AU  - Minjie Chen
AU  - Glaucio H. Paulino
PY  - 2026
DA  - 2026/10/30
JO  - Proceedings of the National Academy of Sciences of the United States of America
DO  - 10.1073/pnas.2615316123
UR  - https://doi.org/10.1073/pnas.2615316123
AB  - Achieving reliable, remote control over multiple stable states in modular systems remains a challenge due to the coupling between modules and history-dependent transitions. Here, we present magnetic origami state machines that enable deterministic navigation from any unknown initial state to any target state under magnetic actuation. By assuming mutually distinct energy barriers in modular Kresling origami assemblies, we realize fully accessible transition graphs with scalable state spaces. Guided by the graph associated to the state machine, a rotating magnetic field induces a universal reset that autonomously drives the system to a known equilibrium state from arbitrary states without sensing or feedback, while pulsed magnetic inputs further enable programmable transitions to any target state via prescribed actuation sequences. A reduced-order Lagrangian mechanics model predicts snap-through dynamics across reset, stepwise programming (between graph nodes), and shortcuts (by adapting pulse magnitude and orientation) where inertia triggers simultaneous multicell transitions with a single pulse. These results establish a general framework for programmable magneto-mechanical state machines with autonomous state reset and full state-space control.
SN  - 0027-8424
SN  - 1091-6490
ER  -