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Updated: Aug 1, 2025

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
Published on: March 9, 2019
Synaptic plasticity and learning behaviour in multilevel memristive devices
M Asif1,2, Yogesh Singh1,2, Atul Thakre3
1CSIR-National Physical Laboratory Dr K. S. Krishnan Marg New Delhi-110012 India ashok553@nplindia.org.
Abstract:
This research explores a novel two-terminal heterostructure of the Pt/Cu2Se/Sb2Se3/FTO memristor, which exhibited essential biological synaptic functions. These synaptic functions play a critical role in emulating biological neural systems and overcoming the limitations of traditional computing architectures. By repeating a fixed pulse train, in this study, we realized a few crucial neural functions toward weight modulation, such as nonlinear conductance changes and potentiation/depression characteristics, which aid the transition of short-term memory to long-term memory. However, we also employed multilevel switching, which provides easily accessible multilevel (4-states, 2-bit) states, for high-density data storage capability along with endurance (102 pulse cycles for each state) in our proposed device. In terms of synaptic plasticity, the device performed well by controlling the pulse voltage and pulse width during excitatory post-synaptic current (EPSC) measurements. The spike-time-dependent plasticity (STDP) highlights their outstanding functional properties, indicating that the device can be used in artificial biological synapse applications. The artificial neural network with Pt/Cu2Se/Sb2Se3/FTO achieved a significant accuracy of 73% in the simulated Modified National Institute of Standards and Technology database (MNIST) pattern. The conduction mechanism of resistive switching and the artificial synaptic phenomena could be attributed to the transfer of Se2- ions and selenium vacancies. The neuromorphic characteristics of the Pt/Cu2Se/Sb2Se3/FTO devices demonstrate their potential as futuristic synaptic devices.
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