Silk Protein Based Volatile Threshold Switching Memristors for Neuromorphic Computing. (4th January 2022)

• Record Type: Journal Article
• Authors: Zhao, Momo; Wang, Saisai; Li, Dingwei; Wang, Rui; Li, Fanfan; Wu, Mengqi; Liang, Kun; Ren, Huihui; Zheng, Xiaorui; Guo, Chengchen; Ma, Xiaohua; Zhu, Bowen; Wang, Hong; Hao, Yue
• Is Part Of: Advanced Electronic Materials. Volume 8:Number 4(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-01-04
• Subjects: bioelectronics -- leaky integrate‐and‐fire neuron -- neuromorphic computing -- silk protein -- threshold switching; Materials -- Electric properties -- Periodicals; Materials science -- Periodicals; Magnetic materials -- Periodicals; Electronic apparatus and appliances -- Periodicals; 537
• DOI: 10.1002/aelm.202101139
• Languages: English
• ISSNs: 2199-160X

Abstract

Abstract: Memristors based neuromorphic devices can efficiently process complex information and fundamentally overcome the bottleneck of traditional computing based on von Neumann architecture. Meanwhile, natural biomaterials have attracted significant attention for biologically integrated electronic devices due to their excellent biocompatibility, mechanical flexibility, and controllable biodegradability. Thus, biomaterial‐based memristors may have a transformative impact on bridging electronic neuromorphic systems and biological systems. However, the working voltage in biological system is low, but the operation voltages of conventional memristors are high, violating the energy‐efficient biological system. Here, high‐performance silk fibroin‐based threshold switching (TS) memristors are demonstrated, which reveal an on‐current of 1 mA, a low threshold voltage ( V th ) of 0.17 V, a high selectivity of 3 × 10 6, and a steep turn‐on slope of <2.5 mV dec –1 . Meanwhile, the silk TS devices depict outstanding device uniformity and stability even at high humidity (80%) and temperature (70 °C) environments. The silk TS devices exhibit typical short‐term plasticity (STP) of biological synapses including pair‐pulse facilitation (PPF). More importantly, a leaky integrate‐and‐fire (LIF) artificial neuron is successfully realized based on the volatile characteristics of silk TS memristors. These achievements pave the way for utilizing silk biomaterials in advanced bioelectronics and neuromorphic computing. Abstract : A volatile threshold switching (TS) memristor based on silk biomaterials doped with uniformly dispersed silver nanoparticles is achieved, which reveals an on‐current of 1 mA, a low operative voltage of 0.17 V, and high uniformity. The silk TS device can function as both artificial synapses and leaky integrate‐and‐fire artificial neurons, promising for future bio‐integrated low‐power neuromorphic electronics.