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February 19, 2026Materials Horizons2 citationsOpen Access

Physically reconfigurable synaptic plasticity and learning in stretchable neuromorphic systems

SLSeung-Woo LeeSeoul National University of Science and TechnologyKKK. B. KimSeoul National UniversitySMSangjun MaSeoul National University

Key Points

  • The aim is to explore how physical reconfiguration can enhance synaptic plasticity in computing systems.
  • Developing a neuromorphic platform with reconfigurable architectures
  • Programming synaptic functions using gate electrode assembly
  • Demonstrated programmable synaptic plasticity
  • Enabled adaptable functions for various computing tasks

Abstract

A physically reconfigurable neuromorphic platform enables the programming of synaptic plasticity via gate electrode assembly. This strategy provides task-adaptable functions for versatile neuromorphic computing.

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Cite This Study

Lee et al. (2026) studied this question.

synapsesocial.com/papers/6996a879ecb39a600b3ef2f5https://doi.org/10.1039/d5mh01319d
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