A robust graphene oxide memristor enabled by organic pyridinium intercalation for artificial biosynapse application
Yang Li1,§(), Songtao Ling1,§, Ruiyu He1, Cheng Zhang1(), Yue Dong1, Chunlan Ma1, Yucheng Jiang1, Ju Gao1, Jinghui He2, Qichun Zhang3,4()
Jiangsu Key Laboratory of Micro and Nano Heat Fluid Flow Technology and Energy Application, School of Physical Science and Technology, Suzhou University of Science and Technology, Suzhou 215009, China
College of Chemistry, Chemical Engineering, and Materials Science, Soochow University, Suzhou 215123, China
Department of Materials Science and Engineering, City University of Hong Kong, Kowloon, Hong Kong 999077, China
Department of Chemistry & Center of Super-Diamond and Advanced Films (COSDAF), City University of Hong Kong, Kowloon, Hong Kong 999077, China
§ Yang Li and Songtao Ling contributed equally to this work.
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Graphical Abstract
A graphene oxide-based memristor with a novel layered structure is presented. The organic pyridinium intercalation succeeds in serving as a buffer layer to control the randomness and the overgrowth of ion migration path, leading to stable progressive bidirectional conductance tuning rather than the disordered abrupt change. The artificial learning of biological synaptic behaviors is achieved, which is a promising advance toward flexible, energy-saving, and fast speed switching bio-inspired neuromorphic computing systems.
Abstract
Graphene oxide (GO)-based memristors offer the promise of low cost, eco-friendliness, and mechanical flexibility, making them attractive candidates for outstanding flexible electronic devices. However, their resistive transitions often display abrupt change rather than bidirectional progressive tuning, which largely limits their applications for biological synapse emulation and neuromorphic computing. Here, a memristor with a novel layered structure of GO/pyridinium/GO is presented with tunable bidirectional feature. The inserted organic pyridinium intercalation succeeds in serving as a satisfactory buffer layer to intrinsically control the formation of conductive filaments during device operation, leading to progressive conductance regulation. Thus, the essential synaptic behaviors including analog memory characteristics, excitatory postsynaptic current, paired pulse facilitation, prepulse inhibition, spike-timing-dependent plasticity, and spike-rate-dependent plasticity are replicated. The emulation of brain-like “learning-forgetting-relearning” process is also implemented. Additionally, the instant responses of the memristor can be stimulated by low operational voltages and short pulse widths. This study paves one way for GO-based memristors to actuate appealing features such as bidirectional tuning and fast speed switching that are desirable for the development of bio-inspired neuromorphic systems.
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Li Y, Ling S, He R, et al. A robust graphene oxide memristor enabled by organic pyridinium intercalation for artificial biosynapse application. Nano Research, 2023, 16(8): 11278-11287. https://doi.org/10.1007/s12274-023-5789-5
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