Abstract
Constructing an artificial intelligence interactive system is still challenging due to the lack of an integrated artificial sensing and processing system with high performance. In this work, an artificial tactile perception system with integrated sensing, storage, and computing functions is designed based on silk fibroin composite memristors and piezoresistive pressure sensors. The sensors based on polydimethylsiloxane/silver nanowires can sense the external pressure stimulation with fast response speed. In addition, the composite memristor based on silk fibroin possesses good cyclic stability and synaptic plasticity simulation and acts as an artificial synapse to process tactile information. As a result, the integrated tactile perception system realizes the perception, storage, and processing of pressure information, demonstrating the possibility to simulate the biological tactile perception nervous system. This type of system may promote potential applications in artificial intelligence, such as autonomous driving, wearable, flexible electronic devices, and bionic robots.
摘要
构筑人工智能交互系统依然存在挑战, 其原因在于缺少高性能 的感知-计算集成系统. 本研究基于丝素蛋白复合忆阻器与压阻式传感 器设计了集感-存-算功能于一体的人工触觉感知系统. 传感器由聚二甲 基硅氧烷/银纳米线构成, 可快速响应外界压力刺激. 丝素蛋白复合忆 阻器具有优异的循环稳定性及突触可塑性模拟功能, 可作为人工突触 处理触觉信息. 本文集成的触觉感知系统可实现对压力信号的感知、 存储及加工, 证实了其模拟生物体触觉神经系统的可能, 有望在自动驾 驶、可穿戴柔性电子、仿生机器人等人工智能领域广泛应用.
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Phong Truong T, Toan Le H, Thi Nguyen T. A reconfigurable hardware platform for low-power wide-area wireless sensor networks. J Phys-Conf Ser, 2020, 1432: 012068
Wang S, Wang R, Cao Y, et al. Bio-voltage memristors: from physical mechanisms to neuromorphic interfaces. Adv Elect Mater, 2023, 9: 2200972
Pan X, Wang J, Deng Z, et al. A memristor-based bioinspired multi-modal sensory memory system for sensory adaptation of robots. Adv Intelligent Syst, 2022, 4: 2200031
Xia SY, Guo LY, Long Y, et al. Integrated sensing–memory–computing artificial tactile system based on force sensors and memristors. Appl Phys Lett, 2023, 122: 183504
Xia Q, Qin Y, Zheng A, et al. A multifunctional biomimetic flexible sensor based novel artificial tactile neuron with perceptual memory. Adv Mater Inter, 2021, 8: 2101068
Zhang Y, Fan S, Zhang Y. Bio-memristors based on silk fibroin. Mater Horiz, 2021, 8: 3281–3294
Hota MK, Bera MK, Kundu B, et al. A natural silk fibroin protein-based transparent bio-memristor. Adv Funct Mater, 2012, 22: 4493–4499
Shi C, Wang J, Sushko ML, et al. Silk flexible electronics: from Bombyx mori silk Ag nanoclusters hybrid materials to mesoscopic memristors and synaptic emulators. Adv Funct Mater, 2019, 29: 1904777
Zhang Y, Fan S, Niu Q, et al. Intrinsically ionic conductive nanofibrils for ultra-thin bio-memristor with low operating voltage. Sci China Mater, 2022, 65: 3096–3104
Hecht DS, Hu L, Irvin G. Emerging transparent electrodes based on thin films of carbon nanotubes, graphene, and metallic nanostructures. Adv Mater, 2011, 23: 1482–1513
Kai C, Yingping H, Dandan S, et al. A lossless fiber pressure sensor based on PDMS. IEEE Access, 2020, 8: 189036–189042
Wang M, Zhang K, Dai XX, et al. Enhanced electrical conductivity and piezoresistive sensing in multi-wall carbon nanotubes/polydimethylsiloxane nanocomposites via the construction of a self-segregated structure. Nanoscale, 2017, 9: 11017–11026
Tan X, Zheng J. A novel porous PDMS-AgNWs-PDMS (PAP)-sponge-based capacitive pressure sensor. Polymers, 2022, 14: 1495
Zhang Y, Han F, Fan S, et al. Low-power and tunable-performance biomemristor based on silk fibroin. ACS BioMater Sci Eng, 2021, 7: 3459–3468
Sun F, Lu Q, Hao M, et al. An artificial neuromorphic somatosensory system with spatio-temporal tactile perception and feedback functions. npj Flex Electron, 2022, 6: 72
Wang WS, Zhu LQ. Recent advances in neuromorphic transistors for artificial perception applications. Sci Tech Adv Mater, 2023, 24: 2152290
Liu S, Cheng Y, Han F, et al. Multilevel resistive switching memristor based on silk fibroin/graphene oxide with image reconstruction functionality. Chem Eng J, 2023, 471: 144678
Fan S, Liu S, Xie Y, et al. Silk fibroin/graphene quantum dots composite memristor with multi-level resistive switching for synaptic emulators. J Mater Chem C, 2024, 12: 3730–3738
Winkler R, Zintler A, Petzold S, et al. Controlling the formation of conductive pathways in memristive devices. Adv Sci, 2022, 9: 2201806
Wan H, Zhao J, Lo LW, et al. Multimodal artificial neurological sensory–memory system based on flexible carbon nanotube synaptic transistor. ACS Nano, 2021, 15: 14587–14597
Sun T, Feng B, Huo J, et al. Artificial intelligence meets flexible sensors: emerging smart flexible sensing systems driven by machine learning and artificial synapses. Nano-Micro Lett, 2023, 16: 14
Yan X, Qin C, Lu C, et al. Robust Ag/ZrO2/WS2/Pt memristor for neuromorphic computing. ACS Appl Mater Interfaces, 2019, 11: 48029–48038
Liu Y, Wu Y, Wang B, et al. Versatile memristor implemented in van der Waals CuInP2S6. Nano Res, 2023, 16: 10191–10197
Wu Q, Wang H, Luo Q, et al. Full imitation of synaptic metaplasticity based on memristor devices. Nanoscale, 2018, 10: 5875–5881
Zhao M, Wang S, Li D, et al. Silk protein based volatile threshold switching memristors for neuromorphic computing. Adv Elect Mater, 2022, 8: 2101139
Wu Y, Wei Y, Huang Y, et al. Capping CsPbBr3 with ZnO to improve performance and stability of perovskite memristors. Nano Res, 2016, 10: 1584–1594
Ilyas N, Li C, Wang J, et al. A modified SiO2-based memristor with reliable switching and multifunctional synaptic behaviors. J Phys Chem Lett, 2022, 13: 884–893
Chen X, Pan J, Fu J, et al. Polyoxometalates-modulated reduced graphene oxide flash memory with ambipolar trapping as bidirectional artificial synapse. Adv Elect Mater, 2018, 4: 1800444
Singh R, Kumar M, Iqbal S, et al. Highly transparent solid-state artificial synapse based on oxide memristor. Appl Surf Sci, 2021, 536: 147738
Liu Z, Cheng P, Kang R, et al. Inorganic lead-free and bismuth-based perovskite nanoscale-thick films for memristors and artificial synapse applications. ACS Appl Nano Mater, 2023, 6: 21000–21015
Duan H, Wang D, Gou J, et al. Memristors based on 2D MoSe2 nanosheets as artificial synapses and nociceptors for neuromorphic computing. Nanoscale, 2023, 15: 10089–10096
Peng Z, Wu F, Jiang L, et al. HfO2-based memristor as an artificial synapse for neuromorphic computing with tri-layer HfO2/BiFeO3/HfO2 design. Adv Funct Mater, 2021, 31: 2107131
Cui ZQ, Wang S, Chen JM, et al. Direct probing of electron and hole trapping into nano-floating-gate in organic field-effect transistor nonvolatile memories. Appl Phys Lett, 2015, 106: 123303
Cui Z, Sun J, Niu X, et al. Photo-generated charge behaviors in allpolymer solar cells studied by Kelvin probe force microscopy. Org Electron, 2016, 39: 38–42
Gogurla N, Mondal SP, Sinha AK, et al. Transparent and flexible resistive switching memory devices with a very high ON/OFF ratio using gold nanoparticles embedded in a silk protein matrix. Nanotechnology, 2013, 24: 345202
Mukherjee C, Hota MK, Naskar D, et al. Resistive switching in natural silk fibroin protein-based bio-memristors. Phys Status Solidi A, 2013, 210: 1797–1805
Jian M, Zhang Y, Liu Z. Natural biopolymers for flexible sensing and energy devices. Chin J Polym Sci, 2020, 38: 459–490
Li B, Liu Y, Wan C, et al. Mediating short-term plasticity in an artificial memristive synapse by the orientation of silica mesopores. Adv Mater, 2018, 30: 1706395
Xia Q, Qin Y, Zheng A, et al. A low-power and flexible bioinspired artificial sensory neuron capable of tactile perceptual and associative learning. J Mater Chem B, 2023, 11: 1469–1477
Acknowledgement
This work was supported by Shanghai Rising-Star Program (22QA1400400), the Basic Research Project of the Science and Technology Commission of Shanghai Municipality (21JC1400100), the National Natural Science Foundation of China (52173031), and the Oriental Talent Plan (Leading Talent Program, 152). Thanks to Dr. Renwei Liu (Shimadzu) for assisting in AFM measurements, including CAFM and KPFM.
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Author contributions Zhang Y and Fan S conceived and directed this research; Xie Y carried out the experiments and analyzed the data; Xie Y, Kundu SC, Fan S and Zhang Y drafted and revised the paper. All authors participated in data discussions and gave approval to the final version of the manuscript.
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Xie Yulong received his bachelor’s degree in polymer materials and engineering from Anhui Polytechnic University in 2021. He received his Master’s degree in materials science from Donghua University in 2024. His research mainly focuses on silk fibroin based bio-memristors.
Suna Fan is an associate professor at the College of Materials Science and Engineering, Donghua University (DHU). She received her PhD in materials physics and chemistry from Jilin University, China, in 2017. From 2017 to 2018, she was an assistant professor at Wenzhou Institute of Biomaterials and Engineering, Chinese Academy of Sciences (CAS) (renamed as Wenzhou Institute, University of CAS in 2019). She joined DHU in 2018 and is working on the research of conducting polymers and silk-based smart materials.
Yaopeng Zhang is a professor at the State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, DHU. He received his PhD in materials science from DHU in 2002. From 2004 to 2007 he was a postdoctoral research fellow at Kawamura Institute of Chemical Research, Japan. He served as a visiting scholar at Akita University, Japan and Stony Brook University, USA, respectively. His current research is silk materials for bioelectronic and biomedical applications.
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Supporting Information: Memristor-based artificial tactile perception systems with integrated functions of sensing, storage and computing
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Xie, Y., Kundu, S.C., Fan, S. et al. Memristor-based artificial tactile perception systems with integrated functions of sensing, storage and computing. Sci. China Mater. (2024). https://doi.org/10.1007/s40843-024-3072-4
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DOI: https://doi.org/10.1007/s40843-024-3072-4