Artificial synapses based on Ag-sericin memrister for bioinspired neuromorphic computing

• Published in: Journal of materials science. Materials in electronics Vol. 35; no. 17; p. 1170
• Main Authors: Enming, Zhao, Shengchuan, Deng, Xiaoqi, Li, Guangyu, Liu, Jianbo, Jiang, Bao, Zhou, Jilei, Zhang, Chuang, Luo, Bobo, Chen, Hongyi, Zhao
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.06.2024; Springer Nature B.V
• Subjects: Biocompatibility; Bionics; Brain research; Characterization and Evaluation of Materials; Chemistry and Materials Science; Composite materials; Electrodes; Materials Science; Memristors; Neuromorphic computing; Optical and Electronic Materials; Plastic properties; Sandwich structures; Silver; Switching; Synapses
• ISSN: 0957-4522; 1573-482X
• DOI: 10.1007/s10854-024-12924-7

As a potential solution for neuromorphic applications, memristor is widely considered as a highly promising option to replicate biological synapses owing to its distinctive analog characteristics and diverse plasticity. In this study, we propose using Ag-sericin composite memristors to mimic the biological synaptic function. The memristor with a sandwich structure, consisting of Ag-sericin composite as the functional layer was fabricated. Ag-sericin memrister demonstrates typical analog resistive switching characteristics and exhibits excellent conductance modulation capability. The resistive switching characteristics are primarily determined by the formation and rupture of silver conductive paths within the sericin matrix. The synaptic plasticities, such as paired pulse facilitation, spike time-dependent plasticity, spike amplitude-dependent plasticity, spike frequency-dependent plasticity, and potentiation and depression, have been successfully replicated using Ag-sericin memristers. These findings will contribute to the advancement of intelligent computing and bionics.