Please wait a minute...
材料导报  2026, Vol. 40 Issue (6): 25030127-13    https://doi.org/10.11896/cldb.25030127
  无机非金属及其复合材料 |
负持续光电导效应及其神经形态计算应用
李亚超1,2, 胡令祥2, 刘威2, 叶志镇3,4, 诸葛飞2,4,5,6,*
1 宁波大学材料科学与化学工程学院,浙江 宁波 315211;
2 中国科学院宁波材料技术与工程研究所,浙江 宁波 315201;
3 浙江大学材料科学与工程学院硅及先进半导体材料全国重点实验室,杭州 310027;
4 浙江大学温州研究院,浙江 温州 325006;
5 中国科学院脑科学与智能技术卓越创新中心,上海 200031;
6 中国科学院大学材料科学与光电技术学院,北京 100029
Negative Persistent Photoconductance Effect and Its Neuromorphic Computing Applications
LI Yachao1,2, HU Lingxiang2, LIU Wei2, YE Zhizhen3,4, ZHUGE Fei2,4,5,6,*
1 School of Materials Science and Chemical Engineering, Ningbo University, Ningbo 315211, Zhejiang, China;
2 Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, Zhejiang, China;
3 State Key Laboratory of Silicon and Advanced Semiconductor Materials, School of Materials Science and Engineering, Zhejiang University, Hangzhou 310027, China;
4 Institute of Wenzhou, Zhejiang University, Wenzhou 325006, Zhejiang, China;
5 Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China;
6 School of Materials Science and Optoelectronic Technology, Chinese Academy of Sciences, Beijing 100029, China
下载:  全 文 ( PDF ) ( 43309KB ) 
输出:  BibTeX | EndNote (RIS)      
摘要 随着人工智能的快速发展,传统冯·诺依曼架构在算力提升上面临瓶颈,难以满足深度学习等算法对高效、高速计算的需求。神经形态计算应运而生,其受人脑启发,采用数据处理与存储一体架构,具备高度并行性和超低功耗优势。负持续光电导(Negative persistent photoconductance,NPPC)效应是指半导体材料或器件电导在光照下降低,且停止光照后仍可较长时间保持的现象。基于NPPC效应的神经形态器件能够在光信号变化时灵活调节电导,从而实现更精准的信息感知和处理,在复杂交互环境中展现出显著优势,并有助于降低系统能耗,简化硬件架构,这些特性使其在神经形态计算领域具有重要的应用价值和发展潜力。本文从光电导效应的基本原理出发,梳理了NPPC效应的物理机制,包括电荷转移、缺陷捕获、电荷隧穿和极化切换。进一步从模拟突触和模拟神经元的角度系统分析了NPPC效应在神经形态计算中的应用,并展望了NPPC神经形态器件未来面临的机遇和挑战。
服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
李亚超
胡令祥
刘威
叶志镇
诸葛飞
关键词:  负持续光电导  神经形态计算  突触  神经元    
Abstract: With the rapid advancement of artificial intelligence, the traditional von Neumann architecture is encountering a bottleneck in boosting computational power, making it difficult to satisfy the need for efficient and high-speed computing required by complex algorithms such as deep learning. Neuromorphic computing has emerged as a solution to this challenge. Inspired by the human brain, it utilizes an integrated architecture for data processing and storage, offering high parallelism and extremely low power consumption. The negative persistent photoconductance (NPPC) effect refers to the phenomenon where the electrical conductance of a semiconducting material or device decreases under light illumination, with the reduced conductance persisting for a relatively long time even after the light is removed. Neuromorphic devices leveraging the NPPC effect can flexibly adjust their conductance in response to changes in light signals, thereby enhancing information sensing and processing accuracy. This capability provides significant advantages in complex interactive environments, while also reducing energy consumption and simplifying hardware architecture. These features make NPPC devices highly promising for neuromorphic computing applications. This paper first introduces the fundamental concept of photoconductance and systematically discusses the physical mechanisms underlying the NPPC effect, including charge transfer, defect trapping, charge tunneling, and polarization switching. It then details the applications of NPPC in neuromorphic computing, focusing on simulating synaptic and neuronal functions. Finally, it provides an outlook on the future opportunities and challenges faced by NPPC-based neuromorphic devices.
Key words:  negative persistent photoconductance    neuromorphic computing    synapses    neurons
出版日期:  2026-03-25      发布日期:  2026-04-03
ZTFLH:  TN36  
基金资助: 国家自然科学基金(62304228;U25A20498);浙江省自然科学基金(LD25F040006);宁波市自然科学基金(2023J356)
通讯作者:  *诸葛飞,中国科学院宁波材料技术与工程研究所研究员、博士研究生导师。主要从事低维半导体材料与器件及其在类脑人工智能领域的应用研究。zhugefei@nimte.ac.cn   
作者简介:  李亚超,宁波大学材料科学与化学工程学院与中国科学院宁波材料技术与工程研究所联合培养硕士研究生,在诸葛飞研究员的指导下进行研究。目前主要研究领域为氧化物忆阻器负向光电导。
引用本文:    
李亚超, 胡令祥, 刘威, 叶志镇, 诸葛飞. 负持续光电导效应及其神经形态计算应用[J]. 材料导报, 2026, 40(6): 25030127-13.
LI Yachao, HU Lingxiang, LIU Wei, YE Zhizhen, ZHUGE Fei. Negative Persistent Photoconductance Effect and Its Neuromorphic Computing Applications. Materials Reports, 2026, 40(6): 25030127-13.
链接本文:  
https://www.mater-rep.com/CN/10.11896/cldb.25030127  或          https://www.mater-rep.com/CN/Y2026/V40/I6/25030127
1 Chou M J, Tsui D C, Weimann G. Applied Physics Letters, 1985, 47(6), 609.
2 Zhu X, Gao C, Ren Y, et al. Advanced Materials, 2023, 35(24), 2301468.
3 Ahmed T, Kuriakose S, Abbas S, et al. Advanced Functional Materials, 2019, 29(39), 1901991.
4 Lai H, Zhou Y, Zhou H, et al. Advanced Materials, 2022, 34(19), 2110278.
5 Xie L, Chen X, Dong Z, et al. Advanced Electronic Materials, 2019, 5(8), 1900458.
6 Von Neumann J. IEEE Annals of the History of Computing, 1993, 15(4), 27.
7 Zidan M A, Strachan J P, Lu W D. Nature Electronics, 2018, 1(1), 22.
8 Bliss T V P, Collingridge G L. Nature, 1993, 361(6407), 31.
9 Liu C N, Michaelis M, Amir R, et al. Journal of Neurophysiology, 2000, 84(1), 205.
10 Drachman D A. Neurology, 2005, 64(12), 2004.
11 Attwell D, Laughlin S B. Journal of Cerebral Blood Flow & Metabolism, 2001, 21(10), 1133.
12 Cheng Z, Ríos C, Pernice W H P, et al. Science Advances, 2017, 3(9), e1700160.
13 Dresbach T, Qualmann B, Kessels M M, et al. Cellular and Molecular Life Sciences CMLS, 2001, 58(1), 94.
14 Boahen K. Nature, 2022, 612(7938), 43.
15 Roy K, Jaiswal A, Panda P. Nature, 2019, 575(7784), 607.
16 Shan H, Ying H, Cheng P, et al. Chinese Journal of Luminescence, 2025, 46(2), 245 (in Chinese).
单海, 应宏微, 程培红, 等. 发光学报, 2025, 46(2), 245.
17 Indiveri G, Liu S C. Proceedings of the IEEE, 2015, 103(8), 1379.
18 Indiveri G, Linares-Barranco B, Legenstein R, et al. Nanotechnology, 2013, 24(38), 384010.
19 Wang J, Zhuge F. Advanced Materials Technologies, 2019, 4(3), 1800544.
20 Wang Z, Zeng T, Ren Y, et al. Nature Communications, 2020, 11(1), 1510.
21 Wang Z, Joshi S, Savel'ev S, et al. Nature Electronics, 2018, 1(2), 137.
22 Hu L, Yang J, Wang J, et al. All-optically controlled memristor, https:∥doi. org/10. 48550/arXiv. 2004. 08077.
23 Hu L, Yang J, Wang J, et al. Advanced Functional Materials, 2021, 31(4), 2005582.
24 Yu Z, Xu J, Han X, et al. Materials Reports, 2024, 38(13), 47 (in Chinese).
余志强, 徐佳敏, 韩旭, 等. 材料导报, 2024, 38(13), 47.
25 Fuller E J, Keene S T, Melianas A, et al. Science, 2019, 364(6440), 570.
26 Ding K, Wang J, Zhou Y, et al. Science, 2019, 366(6462), 210.
27 Krzysteczko P, Münchenberger J, Schäfers M, et al. Advanced Materials, 2012, 24(6), 762.
28 Kim D, Jeon Y R, Ku B, et al. ACS Applied Materials & Interfaces, 2021, 13(44), 52743.
29 Sengupta A, Al Azim Z, Fong X, et al. Applied Physics Letters, 2015, 106(9), 93704.
30 Wang T, Ran H, Zhou G. Journal of Inorganic Materials, 2023, 38(4), 437.
31 Chen X, Lou Y, Zhao N, et al. Materials Reports, 2022, 36(10), 21 (in Chinese).
陈晓平, 楼玉民, 赵宁宁, 等. 材料导报, 2022, 36(10), 21.
32 Kang D J, Park J U, Bae B S, et al. Optics Express, 2003, 11(10), 1144.
33 Cao Z, Aharonian F A, An Q, et al. Nature, 2021, 594(7861), 33.
34 Yang Y, Peng X, Kim H S, et al. Nano Letters, 2015, 15(9), 5875.
35 Hori T, Ozono T, Orihashi N, et al. Journal of Applied Physics, 2006, 99(6), 64508.
36 Wang L, Wang H, Liu J, et al. Advanced Materials, 2024, 36(38), 2403538.
37 Maier P, Hartmann F, Rebello S D M, et al. Applied Physics Letters, 2016, 109(2), 023501.
38 Zhang Z, Wang S, Liu C, et al. Nature Nanotechnology, 2022, 17(1), 27.
39 Jin C, Wang J, Yang S, et al. Advanced Materials, 2025, 37(1), 2410398.
40 Panigrahi S, Bera A, Basak D. ACS Applied Materials & Interfaces, 2009, 1(10), 2408.
41 Ye Y, Zhao J, Xiao L, et al. ACS Applied Materials & Interfaces, 2018, 10(22), 19002.
42 Lu C, Meng J, Song J, et al. Nano Letters, 2024, 24(5), 1667.
43 Hu L, Shao J, Wang J, et al. Applied Physics Reviews, 2024, 11(1), 011411.
44 Lo I, Chen S J, Lee Y C, et al. Physical Review B, 1998, 57(12), R6819.
45 Tong T, Wang S, Zhao J, et al. Nanoscale Horizons, 2019, 4(1), 138.
46 Hong Z, Zhao J, Li S, et al. Nanoscale, 2019, 11(7), 3360.
47 Höpfel R A. Applied Physics Letters, 1988, 52(10), 801.
48 Davidenko N A, Davidenko I I, Derevyanko N A, et al. High Energy Chemistry, 2011, 45(3), 240.
49 Sirunyan A M, Tumasyan A, Adam W, et al. Physical Review D, 2019, 99(11), 112003.
50 Kumar A, Intonti K, Viscardi L, et al. Materials Horizons, 2024, 11(10), 2397.
51 Qin J X, Yang X G, Lv C F, et al. Journal of Physical Chemistry Letters, 2021, 12(16), 4079.
52 Hong Z, Zhao J, Huang K, et al. Journal of Materials Chemistry C, 2019, 7(14), 4259.
53 Jiang J, Xu W, Sun Z, et al. Small, 2024, 20(13), 2306068.
54 Yang J, Hu L, Shen L, et al. Fundamental Research, 2024, 4(1), 158.
55 Miao J, Song B, Li Q, et al. ACS Nano, 2017, 11(6), 6048.
56 Biswas C, Güneş F, Loc D D, et al. Nano Letters, 2011, 11(11), 4682.
57 Lui C H, Frenzel A J, Pilon D V, et al. Physical Review Letters, 2014, 113(16), 166801.
58 Baek E, Rim T, Schütt J, et al. Nano Letters, 2017, 17(11), 6727.
59 Wang Y, Liu E, Gao A, et al. ACS Nano, 2018, 12(9), 9513.
60 Chen Y, Zhang M, Li D, et al. ACS Nano, 2023, 17(13), 12499.
61 Yang C, Sun B, Zhou G, et al. ACS Materials Letters, 2023, 5(2), 504.
62 Wu X, Dang B, Wang H, et al. Advanced Intelligent Systems, 2022, 4(3), 2100151.
63 Wang C, Yang Z, Wang S, et al. Advanced Intelligent Systems, 2020, 2(1), 1900103.
64 Wang Y, Gong Y, Huang S, et al. Nature Communications, 2021, 12(1), 5979.
65 Hamdioui S, Xie L, Nguyen H A D, et al. In: Design, Automation and Test in Europe Conference and Exhibition. Grenoble, 2015, pp. 1718.
66 Park S O, Jeong H, Park J, et al. Nature Communications, 2022, 13(1), 2888.
67 Liu Z, Tang J, Gao B, et al. Nature Communications, 2020, 11(1), 4234.
68 Ziegler M, Riggert C, Hansen M, et al. IEEE Transactions on Biomedical Circuits and Systems, 2015, 9(2), 197.
69 Bi G, Poo M. Journal of Neuroscience, 1998, 18(24), 10464.
70 Caporale N, Dan Y. Annual Review of Neuroscience, 2008, 31(1), 25.
71 Hu L, Zhuge X, Wang J, et al. Advanced Electronic Materials, 2025, 11(3), 2400482.
72 Jo S H, Chang T, Ebong I, et al. Nano Letters, 2010, 10(4), 1297.
73 Prezioso M, Merrikh-Bayat F, Hoskins B D, et al. Nature, 2015, 521(7550), 61.
74 Agnus G, Zhao W, Derycke V, et al. Advanced Materials, 2010, 22(6), 702.
75 Liu K, Zhang Q, Liao Y, et al. Chinese Journal of Luminescence, 2024, 45(2), 317 (in Chinese).
刘凯, 张晴怡, 廖延安, 等. 发光学报, 2024, 45(2), 317.
76 Mead C. Proceedings of the IEEE, 1990, 78(10), 1629.
77 Merolla P A, Arthur J V, Alvarez-Icaza R, et al. Science, 2014, 345(6197), 668.
78 Pei J, Deng L, Song S, et al. Nature, 2019, 572(7767), 106.
79 Shan X, Zhao C, Wang X, et al. Advanced Science, 2022, 9(6), 2104632.
80 Gu L, Li Y, Xie D, et al. IEEE Transactions on Electron Devices, 2022, 69(8), 4382.
81 Gao Z, Jiang R, Deng M, et al. Advanced Materials, 2024, 36(29), 2401585.
82 Zheng J, Du Y, Dong Y, et al. Applied Physics Letters, 2024, 124(13), 133502.
83 Li D, Ren H, Chen Y, et al. Advanced Functional Materials, 2023, 33(42), 2303198.
84 Jiang J, Shan X, Xu J, et al. Advanced Functional Materials, 2024, 34(51), 2409677.
85 Zhang Y, Guo Q, Duan Y, et al. Advanced Functional Materials, 2024, 34(13), 2310001.
86 Zhou G, Li J, Song Q, et al. Nature Communications, 2023, 14(1), 8489.
87 Xiao Y, Li W, Lin X, et al. Advanced Electronic Materials, 2023, 9(10), 2300388.
88 Xie T, Leng Y, Sun T, et al. Advanced Functional Materials, 2025, 35(7), 2415457.
89 Farrant M, Nusser Z. Nature Reviews Neuroscience, 2005, 6(3), 215.
90 Markram H, Toledo-Rodriguez M, Wang Y, et al. Nature Reviews Neuroscience, 2004, 5(10), 793.
91 Izhikevich E M. IEEE Transactions on Neural Networks, 2004, 15(5), 1063.
92 Hodgkin A L, Huxley A F. Journal of Physiology, 1952, 116(4), 473.
93 Hodgkin A L, Huxley A F. Journal of Physiology, 1952, 116(4), 449.
94 Wan C, He Y, Jiang S, et al. ACS Applied Electronic Materials, 2020, 2(2), 389.
95 Ma Q, Haider M R, Shrestha V L, et al. Analog Integrated Circuits and Signal Processing, 2012, 73(1), 329.
96 Kwon M W, Baek M H, Hwang S, et al. Journal of Applied Physics, 2018, 124(15), 152107.
97 Chatterjee D, Kottantharayil A. IEEE Electron Device Letters, 2019, 40(8), 1301.
98 Laughlin S B, De Ruyter Van Steveninck R R, Anderson J C. Nature Neuroscience, 1998, 1(1), 36.
99 Pulido C, Ryan T A. Science Advances, 2021, 7(49), 9.
100 Li Z, Hu L, Wang J, et al. Journal of Inorganic Materials, 2024, 39(4), 345 (in Chinese).
李宗晓, 胡令祥, 王敬蕊, 等. 无机材料学报, 2024, 39(4), 345.
101 Li Z, Geng X, Wang J, et al. Frontiers in Neuroscience, 2021, 15(7179), 717947.
102 Hu L, Li Z, Shao J, et al. Nano Letters, 2024, 24(35), 10865.
103 Huang Y, Tan Y, Kang Y, et al. Advanced Functional Materials, 2024, 34(38), 2402677.
104 Wang C Y, Liang S J, Wang S, et al. Science Advances, 2020, 6(26), 6173.
105 Kumar K, Sharma P, Verma S, et al. Advanced Functional Materials, 2024, 34(40), 2405364.
106 Zhang H, Yao J, Shao J, et al. Scientific Reports, 2014, 4(1), 5876.
107 Yan J, Ying J, Yan M, et al. Advanced Functional Materials, 2021, 31(40), 2103982.
108 Cao A, Li S, Chen H, et al. Materials Horizons, 2023, 10(11), 5099.
109 Wang M, Ouyang D, Dai Y, et al. Advanced Materials, DOI:10. 1002/adma. 202500049.
110 Liu K, Zhang T, Dang B, et al. Nature Electronics, 2022, 5(11), 761.
111 Huang B, Lan L, Pan J, et al. Small Science, DOI:10. 1002/smsc. 202400511.
112 Fang H, Ma S, Wang J, et al. Advanced Functional Materials, 2024, 34(49), 2409045.
113 Tian Q, Xun K, Li Z, et al. Journal of Semiconductors, 2025, 46(2), 22407.
114 Yao J, Wang Q, Zhang Y, et al. Nature Communications, 2024, 15(1), 6147.
115 Liu Z, Wang Y, Zhang Y, et al. Advanced Materials, 2025, 37(4), 2410783.
[1] 杨瀚, 刘国柱, 魏轶聃, 赵伟, 魏应强, 周颖, 隋志远, 刘美杰, 尤兴宇, 魏敬和. 面向存储和神经形态计算应用的CBRAM发展综述[J]. 材料导报, 2025, 39(21): 24100167-12.
[2] 韩坤原, 柳凤琦, 叶益聪. 纳米银基神经形态网络的制备与应用研究进展[J]. 材料导报, 2025, 39(19): 24070124-11.
[3] 施纯言, 张程, 毕冉, 李毅翔, 何瑞钰, 袁俊尉, 李阳. 基于新型有机-无机杂化材料的忆阻器在人工突触与神经形态计算领域的应用研究进展[J]. 材料导报, 2025, 39(14): 23080054-13.
[4] 王淼儒, 柴晓杰, 闫泽宇, 索丁丁, 冀健龙. 高稳定性氧化镓基忆阻器的构筑和神经形态计算应用[J]. 材料导报, 2025, 39(11): 25020107-6.
[5] 刘菁, 张建, 赵波. 光电忆阻器用于突触仿生领域的研究进展[J]. 材料导报, 2024, 38(4): 22060027-10.
[6] 陈晓平, 楼玉民, 赵宁宁, 黄一君, 胡海龙, 岳建岭. 基于异质结构忆阻器的研究进展[J]. 材料导报, 2022, 36(10): 20070058-10.
[7] 陆骐峰,孙富钦,王子豪,张珽. 柔性人工突触:面向智能人机交互界面和高效率神经网络计算的基础器件[J]. 材料导报, 2020, 34(1): 1022-1049.
[1] Yanzhen WANG, Mingming CHEN, Chengyang WANG. Preparation and Electrochemical Properties Characterization of High-rate SiO2/C Composite Materials[J]. Materials Reports, 2018, 32(3): 357 -361 .
[2] Yimeng XIA, Shuai WU, Feng TAN, Wei LI, Qingmao WEI, Chungang MIN, Xikun YANG. Effect of Anionic Groups of Cobalt Salt on the Electrocatalytic Activity of Co-N-C Catalysts[J]. Materials Reports, 2018, 32(3): 362 -367 .
[3] Qingshun GUAN,Jian LI,Ruyuan SONG,Zhaoyang XU,Weibing WU,Yi JING,Hongqi DAI,Guigan FANG. A Survey on Preparation and Application of Aerogels Based on Nanomaterials[J]. Materials Reports, 2018, 32(3): 384 -390 .
[4] Wen XI,Zheng CHEN,Shi HU. Research Progress of Deformation Induced Localized Solid-state Amorphization in Nanocrystalline Materials[J]. Materials Reports, 2018, 32(1): 116 -121 .
[5] Laima LUO, Mengyao XU, Xiang ZAN, Xiaoyong ZHU, Ping LI, Jigui CHENG, Yucheng WU. Progress in Irradiation Damage of Tungsten and Tungsten AlloysUnder Different Irradiation Particles[J]. Materials Reports, 2018, 32(1): 41 -46 .
[6] Fengsen MA,Yan YU,Jie ZHANG,Haibo CHEN. A State-of-the-art Review of Cytotoxicity Evaluation of Biomaterials[J]. Materials Reports, 2018, 32(1): 76 -85 .
[7] Huimin PAN,Jun FU,Qingxin ZHAO. Sulfate Attack Resistance of Concrete Subjected to Disturbance in Hardening Stage[J]. Materials Reports, 2018, 32(2): 282 -287 .
[8] Acidifier at High Temperature SiO2Bearing, , , , . Research on Stabilization of Free CaO in Basic Oxygen Furnace Slag with[J]. Materials Reports, 2018, 32(2): 301 -306 .
[9] Ziming LIU,Huaxin CHEN,Rui XIONG,Yongdan WANG,Xiaowen WANG. Experimental Investigation on Properties of Steel Wool Fiber/Brucite Fiber Reinforced Asphalt Mortar[J]. Materials Reports, 2018, 32(2): 295 -300 .
[10] ZHANG Hehe, LI Fangfang, WANG Haiyan, PENG Zhiguang, TANG Yougen. Iron Electrode Derived from Fe/Co-MOF and Its Electrochemical Performance for Nickel-Iron Batteries[J]. Materials Reports, 2018, 32(5): 719 -724 .
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed