Silk Protein Based Volatile Threshold Switching Memristors for Neuromorphic Computing
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...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley-VCH
2022-04-01
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| Series: | Advanced Electronic Materials |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/aelm.202101139 |
| _version_ | 1797542958103265280 |
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| author | Momo Zhao Saisai Wang Dingwei Li Rui Wang Fanfan Li Mengqi Wu Kun Liang Huihui Ren Xiaorui Zheng Chengchen Guo Xiaohua Ma Bowen Zhu Hong Wang Yue Hao |
| author_facet | Momo Zhao Saisai Wang Dingwei Li Rui Wang Fanfan Li Mengqi Wu Kun Liang Huihui Ren Xiaorui Zheng Chengchen Guo Xiaohua Ma Bowen Zhu Hong Wang Yue Hao |
| author_sort | Momo Zhao |
| collection | DOAJ |
| description | 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 (Vth) of 0.17 V, a high selectivity of 3 × 106, 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. |
| first_indexed | 2024-03-10T13:37:54Z |
| format | Article |
| id | doaj.art-8f73b28c5d3c4d8e9ee2d604d92e6090 |
| institution | Directory Open Access Journal |
| issn | 2199-160X |
| language | English |
| last_indexed | 2024-03-10T13:37:54Z |
| publishDate | 2022-04-01 |
| publisher | Wiley-VCH |
| record_format | Article |
| series | Advanced Electronic Materials |
| spelling | doaj.art-8f73b28c5d3c4d8e9ee2d604d92e60902023-11-21T07:01:06ZengWiley-VCHAdvanced Electronic Materials2199-160X2022-04-0184n/an/a10.1002/aelm.202101139Silk Protein Based Volatile Threshold Switching Memristors for Neuromorphic ComputingMomo Zhao0Saisai Wang1Dingwei Li2Rui Wang3Fanfan Li4Mengqi Wu5Kun Liang6Huihui Ren7Xiaorui Zheng8Chengchen Guo9Xiaohua Ma10Bowen Zhu11Hong Wang12Yue Hao13Key Laboratory of Wide Band Gap Semiconductor Technology School of Microelectronics Xidian University Xi'an 710071 ChinaKey Laboratory of Wide Band Gap Semiconductor Technology School of Microelectronics Xidian University Xi'an 710071 ChinaKey Laboratory of 3D Micro/Nano Fabrication and Characterization of Zhejiang Province School of Engineering Westlake University Hangzhou 310024 ChinaKey Laboratory of Wide Band Gap Semiconductor Technology School of Microelectronics Xidian University Xi'an 710071 ChinaKey Laboratory of Wide Band Gap Semiconductor Technology School of Microelectronics Xidian University Xi'an 710071 ChinaKey Laboratory of 3D Micro/Nano Fabrication and Characterization of Zhejiang Province School of Engineering Westlake University Hangzhou 310024 ChinaKey Laboratory of 3D Micro/Nano Fabrication and Characterization of Zhejiang Province School of Engineering Westlake University Hangzhou 310024 ChinaKey Laboratory of 3D Micro/Nano Fabrication and Characterization of Zhejiang Province School of Engineering Westlake University Hangzhou 310024 ChinaKey Laboratory of 3D Micro/Nano Fabrication and Characterization of Zhejiang Province School of Engineering Westlake University Hangzhou 310024 ChinaKey Laboratory of 3D Micro/Nano Fabrication and Characterization of Zhejiang Province School of Engineering Westlake University Hangzhou 310024 ChinaKey Laboratory of Wide Band Gap Semiconductor Technology School of Microelectronics Xidian University Xi'an 710071 ChinaKey Laboratory of 3D Micro/Nano Fabrication and Characterization of Zhejiang Province School of Engineering Westlake University Hangzhou 310024 ChinaKey Laboratory of Wide Band Gap Semiconductor Technology School of Microelectronics Xidian University Xi'an 710071 ChinaKey Laboratory of Wide Band Gap Semiconductor Technology School of Microelectronics Xidian University Xi'an 710071 ChinaAbstract 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 (Vth) of 0.17 V, a high selectivity of 3 × 106, 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.https://doi.org/10.1002/aelm.202101139bioelectronicsleaky integrate‐and‐fire neuronneuromorphic computingsilk proteinthreshold switching |
| spellingShingle | Momo Zhao Saisai Wang Dingwei Li Rui Wang Fanfan Li Mengqi Wu Kun Liang Huihui Ren Xiaorui Zheng Chengchen Guo Xiaohua Ma Bowen Zhu Hong Wang Yue Hao Silk Protein Based Volatile Threshold Switching Memristors for Neuromorphic Computing Advanced Electronic Materials bioelectronics leaky integrate‐and‐fire neuron neuromorphic computing silk protein threshold switching |
| title | Silk Protein Based Volatile Threshold Switching Memristors for Neuromorphic Computing |
| title_full | Silk Protein Based Volatile Threshold Switching Memristors for Neuromorphic Computing |
| title_fullStr | Silk Protein Based Volatile Threshold Switching Memristors for Neuromorphic Computing |
| title_full_unstemmed | Silk Protein Based Volatile Threshold Switching Memristors for Neuromorphic Computing |
| title_short | Silk Protein Based Volatile Threshold Switching Memristors for Neuromorphic Computing |
| title_sort | silk protein based volatile threshold switching memristors for neuromorphic computing |
| topic | bioelectronics leaky integrate‐and‐fire neuron neuromorphic computing silk protein threshold switching |
| url | https://doi.org/10.1002/aelm.202101139 |
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