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Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
Published on: March 9, 2019
A voltage-controlled reconfigurable memristor with dual-mode synaptic plasticity for adaptive neuromorphic computing
Kai Sun1, Hongxia Liu1, Ye Yang1
1The Key Laboratory for Wide Bandgap Semiconductor Materials and Devices of Education, School of Microelectronics, Xidian University, Xi'an 710071, People's Republic of China.
None:
In this study, we propose and experimentally validate a simple planar-integrated dual-device memristor structure based on HfO2/Al2O3heterostructure, which demonstrates voltage-modulated switching behavior between analog and digital resistance switch (A-RS/D-RS) modes. Low-voltage operation (less than 1 V) achieves A-RS for continuous conductance modulation (emulating synaptic plasticity), while higher voltages (more than 2 V) trigger D-RS for abrupt threshold transitions (suitable for binary neural networks). Experimental validation through simulated array configurations empirically validates the device's capacity for achieving robust compatibility with diverse neural network architectures through its multi-model operational capabilities. COMSOL multiphysics simulations further confirmed our elucidation of the switching mechanism. This functional versatility demonstrates critical cross-platform adaptability essential for neuromorphic computing implementations. This dynamically mode-switchable device between dual resistance switching modes offers a scalable solution for energy-efficient reconfigurable neuromorphic systems, demonstrating promising potential in next-generation intelligent sensing-computing co-architectures.
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