AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
Powered by AMiner. Clicking this button will take you away from SciOpen.
Home Nano Research Article
Article Link
Cite
EndNote(RIS) BibTeX
Collect
Submit Manuscript
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research Article

All optical artificial synapses based on long-afterglow material for optical neural network

Wenjie Lu1,§, Qizhen Chen1,§, Huaan Zeng1, Hui Wang1, Lujian Liu1, Tailiang Guo1, Huipeng Chen1,3 ( ), Rui Wang2( )
Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou 350002, China
Department of Neurosurgery, Fujian Medical University Union Hospital, Fuzhou 350001, China
Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China, Fuzhou 350100, China
Wenjie Lu and Qizhen Chen contributed equally this work.
Show Author Information

Graphical Abstract

An all-optical synaptic device simply based on a long-afterglow material is reported. Unique image displays and memory functions can be achieved by combining all-optical synaptic arrays with synaptic memory behavior.

Abstract

Artificial neural network with broad application prospect has attracted particular attention due to the promise of solving the memory wall bottleneck. The neural devices that mix light and electricity provide more degrees of freedom for the design of artificial neural network, but they still do not get rid of the shackles that the response signal needs circuit to transmission. The exploration of all-optical neural devices (optical signal input and output) is expected to solve this problem. Here, an all-optical synaptic device simply based on a long-afterglow material is reported. The optical properties of the all-optical synaptic device are similar to the responses in biological synapses. Unique image displays and memory functions can be achieved by combining all-optical synaptic arrays with synaptic memory behavior. Furthermore, the optical summation of all-optical synaptic array pixels can be completed by combining the focusing characteristics of convex lens, which realizes the photon transmission after preprocessing multiple input signals. Particularly, the simple single-layer structure of all-optical synapses with polydimethylsiloxane (PDMS) as the carrier has high plasticity and is expected to achieve large-scale preparation. This work enriches the diversity of artificial synapses and shows the huge development potential of photoelectric artificial neural networks.

Keywords

synaptic plasticityall opticaloptical computationoptical neural network

Electronic Supplementary Material

Download File(s)
12274_2023_5566_MOESM1_ESM.pdf (778.1 KB)

References

[1]

Agiwal, M.; Roy, A.; Saxena, N. Next generation 5G wireless networks: A comprehensive survey. IEEE Commun. Surv. Tutorials 2016, 18, 1617–1655.
Crossref Google Scholar
[2]

Wu, X. D.; Zhu, X. Q.; Wu, G. Q.; Ding, W. Data mining with big data. IEEE Trans. Knowl. Data Eng. 2014, 26, 97–107.
Crossref Google Scholar
[3]

Huh, W.; Lee, D.; Lee, C. H. Memristors based on 2D materials as an artificial synapse for neuromorphic electronics. Adv. Mater. 2020, 32, 2002092.
Crossref Google Scholar
[4]

LeCun, Y.; Bengio, Y.; Hinton, G. Deep learning. Nature 2015, 521, 436–444.
Crossref Google Scholar
[5]

Yang, J. T.; Ge, C.; Du, J. Y.; Huang, H. Y.; He, M.; Wang, C.; Lu, H. B.; Yang, G. Z.; Jin, K. J. Artificial synapses emulated by an electrolyte-gated tungsten-oxide transistor. Adv. Mater. 2018, 30, 1801548.
Crossref Google Scholar
[6]

Xu, W. T.; Min, S. Y.; Hwang, H.; Lee, T. W. Organic core–sheath nanowire artificial synapses with femtojoule energy consumption. Sci. Adv. 2016, 2, e1501326.
Crossref Google Scholar
[7]

Wang, Y.; Lv, Z. Y.; Chen, J. R.; Wang, Z. P.; Zhou, Y.; Zhou, L.; Chen, X. L.; Han, S. T. Photonic synapses based on inorganic perovskite quantum dots for neuromorphic computing. Adv. Mater. 2018, 30, 1802883.
Crossref Google Scholar
[8]

He, Y. L.; Nie, S.; Liu, R.; Jiang, S. S.; Shi, Y.; Wan, Q. Spatiotemporal information processing emulated by multiterminal neuro-transistor networks. Adv. Mater. 2019, 31, 1900903.
Crossref Google Scholar
[9]

Yan, X. B.; Zhang, L.; Chen, H. W.; Li, X. Y.; Wang, J. J.; Liu, Q.; Lu, C.; Chen, J. S.; Wu, H. Q.; Zhou, P. Graphene oxide quantum dots based memristors with progressive conduction tuning for artificial synaptic learning. Adv. Funct. Mater. 2018, 28, 1803728.
Crossref Google Scholar
[10]

Hasegawa, T.; Terabe, K.; Tsuruoka, T.; Aono, M. Atomic switch: Atom/ion movement controlled devices for beyond von-Neumann computers. Adv. Mater. 2012, 24, 252–267.
Crossref Google Scholar
[11]

Oh, S.; Huang, Z. S.; Shi, Y. H.; Kuzum, D. The impact of resistance drift of phase change memory (PCM) synaptic devices on artificial neural network performance. IEEE Electron Device Lett. 2019, 40, 1325–1328.
Crossref Google Scholar
[12]

Kuzum, D.; Jeyasingh, R. G. D.; Lee, B.; Wong, H. S. P. Nanoelectronic programmable synapses based on phase change materials for brain-inspired computing. Nano Lett. 2012, 12, 2179–2186.
Crossref Google Scholar
[13]

Huang, W. Y.; Chang, Y. C.; Sie, Y. F.; Yu, C. R.; Wu, C. Y.; Hsu, Y. L. Bio-cellulose substrate for fabricating fully biodegradable resistive random access devices. ACS Appl. Polym. Mater. 2021, 3, 4478–4484.
Crossref Google Scholar
[14]

Jo, S. H.; Chang, T.; Ebong, I.; Bhadviya, B. B.; Mazumder, P.; Lu, W. Nanoscale memristor device as synapse in neuromorphic systems. Nano Lett. 2010, 10, 1297–1301.
Crossref Google Scholar
[15]

Yan, X. B.; Wang, K. Y.; Zhao, J. H.; Zhou, Z. Y.; Wang, H.; Wang, J. J.; Zhang, L.; Li, X. Y.; Xiao, Z. A.; Zhao, Q. L. et al. A new memristor with 2D Ti3C2Tx MXene flakes as an artificial bio-synapse. Small 2019, 15, 1900107.
Crossref Google Scholar
[16]

Wang, F. D.; Yu, M. X.; Chen, X. D.; Li, J. Q.; Zhang, Z. C.; Li, Y.; Zhang, G. X.; Shi, K.; Shi, L.; Zhang, M. et al. Optically modulated dual-mode memristor arrays based on core–shell CsPbBr3@graphdiyne nanocrystals for fully memristive neuromorphic computing hardware. SmartMat 2023, 4, e1135.
Crossref Google Scholar
[17]

Yang, F. X.; Sun, L. J.; Duan, Q. X.; Dong, H. L.; Jing, Z. K.; Yang, Y. C.; Li, R. J.; Zhang, X. T.; Hu, W. P.; Chua, L. Vertical-organic-nanocrystal-arrays for crossbar memristors with tuning switching dynamics toward neuromorphic computing. SmartMat 2021, 2, 99–108.
Crossref Google Scholar
[18]

Kim, Y.; Lee, K.; Lee, J.; Jang, S.; Kim, H.; Lee, H.; Lee, S. W.; Wang, G.; Park, C. Bird-inspired self-navigating artificial synaptic compass. ACS Nano 2021, 15, 20116–20126.
Crossref Google Scholar
[19]

Shi, J. L.; Jie, J. S.; Deng, W.; Luo, G.; Fang, X. C.; Xiao, Y. L.; Zhang, Y. J.; Zhang, X. J.; Zhang, X. H. A fully solution-printed photosynaptic transistor array with ultralow energy consumption for artificial-vision neural networks. Adv. Mater. 2022, 34, 2200380.
Crossref Google Scholar
[20]

Gao, J.; Zheng, Y.; Yu, W.; Wang, Y. N.; Jin, T. Y.; Pan, X.; Loh, K. P.; Chen, W. Intrinsic polarization coupling in 2D α-In2Se3 toward artificial synapse with multimode operations. SmartMat 2021, 2, 88–98.
Crossref Google Scholar
[21]

Chen, Q. Z.; Zhang, X. H.; Liu, Y. Q.; Yan, Y. J.; Yu, R. J.; Wang, X. M.; Lin, Z. N.; Zeng, H. A.; Liu, L. J.; Chen, H. P. et al. Neuromorphic display system for intelligent display. Nano Energy 2022, 94, 106931.
Crossref Google Scholar
[22]

Liu, Y. Q.; Li, E. L.; Wang, X. M.; Chen, Q. Z.; Zhou, Y. L.; Hu, Y. Y.; Chen, G. X.; Chen, H. P.; Guo, T. L. Self-powered artificial auditory pathway for intelligent neuromorphic computing and sound detection. Nano Energy 2020, 78, 105403.
Crossref Google Scholar
[23]

Gao, H. K.; Miao, Z. G.; Hu, W. P.; Dong, H. L. Research on key materials and devices of organic light-emitting transistors. Acta Chim. Sin. 2022, 80, 327–339.
Crossref Google Scholar
[24]

Yan, X. B.; Zhao, J. H.; Liu, S.; Zhou, Z. Y.; Liu, Q.; Chen, J. S.; Liu, X. Y. Memristor with Ag-cluster-doped TiO2 films as artificial synapse for neuroinspired computing. Adv. Funct. Mater. 2018, 28, 1705320.
Crossref Google Scholar
[25]

Zheng, Q.; Ren, P. Y.; Peng, Y. H.; Zhou, W. C.; Yin, Y. L.; Wu, H.; Gong, W. T.; Wang, W. K.; Tang, D. S.; Zou, B. S. In-plane anisotropic Raman response and electrical conductivity with robust electron–photon and electron–phonon interactions of air stable MoO2 nanosheets. J. Phys. Chem. Lett. 2019, 10, 2182–2190.
Crossref Google Scholar
[26]

Siddiqui, S. A.; Dutta, S.; Tang, A.; Liu, L. Q.; Ross, C. A.; Baldo, M. A. Magnetic domain wall based synaptic and activation function generator for neuromorphic accelerators. Nano Lett. 2020, 20, 1033–1040.
Crossref Google Scholar
[27]

Wang, X. M.; Li, E. L.; Liu, Y. Q.; Lan, S. Q.; Yang, H. H.; Yan, Y. J.; Shan, L. T.; Lin, Z. X.; Chen, H. P.; Guo, T. L. Stretchable vertical organic transistors and their applications in neurologically systems. Nano Energy 2021, 90, 106497.
Crossref Google Scholar
[28]

Zhao, P. F.; Ji, R. X.; Lao, J.; Xu, W.; Jiang, C. L.; Luo, C. H.; Lin, H. C.; Peng, H.; Duan, C. G. Two-terminal organic optoelectronic synapse based on poly(3-hexylthiophene) for neuromorphic computing. Org. Electron. 2022, 100, 106390.
Crossref Google Scholar
[29]

Yu, R. J.; Li, E. L.; Wu, X. M.; Yan, Y. J.; He, W. X.; He, L. H.; Chen, J. W.; Chen, H. P.; Guo, T. L. Electret-based organic synaptic transistor for neuromorphic computing. ACS Appl. Mater. Interfaces 2020, 12, 15446–15455.
Crossref Google Scholar
[30]

Gao, C. S.; Yang, H. H.; Li, E. L.; Yan, Y. J.; He, L. H.; Chen, H. P.; Lin, Z. X.; Guo, T. L. Heterostructured vertical organic transistor for high-performance optoelectronic memory and artificial synapse. ACS Photonics 2021, 8, 3094–3103.
Crossref Google Scholar
[31]

Kim, S. G.; Kim, S. H.; Park, J.; Kim, G. S.; Park, J. H.; Saraswat, K. C.; Kim, J.; Yu, H. Y. Infrared detectable MoS2 phototransistor and its application to artificial multilevel optic-neural synapse. ACS Nano 2019, 13, 10294–10300.
Crossref Google Scholar
[32]

Tang, J.; He, C. L.; Tang, J. S.; Yue, K.; Zhang, Q. T.; Liu, Y. Z.; Wang, Q. Q.; Wang, S. P.; Li, N.; Shen, C. et al. A reliable all-2D materials artificial synapse for high energy-efficient neuromorphic computing. Adv. Funct. Mater. 2021, 31, 2011083.
Crossref Google Scholar
[33]

Jin, C. X.; Liu, W. R.; Xu, Y. C.; Huang, Y. L.; Nie, Y. L.; Shi, X. F.; Zhang, G. M.; He, P.; Zhang, J.; Cao, H. T. et al. Artificial vision adaption mimicked by an optoelectrical In2O3 transistor array. Nano Lett. 2022, 22, 3372–3379.
Crossref Google Scholar
[34]

Zhao, T. S.; Zhao, C.; Xu, W. Y.; Liu, Y. N.; Gao, H.; Mitrovic, I. Z.; Lim, E. G.; Yang, L.; Zhao, C. Z. Bio-inspired photoelectric artificial synapse based on two-dimensional Ti3C2Tx MXenes floating gate. Adv. Funct. Mater. 2021, 31, 2106000.
Crossref Google Scholar
[35]

Wang, S. Y.; Chen, C. S.; Yu, Z. H.; He, Y. L.; Chen, X. Y.; Wan, Q.; Shi, Y.; Zhang, D. W.; Zhou, H.; Wang, X. R. et al. A MoS2/PTCDA hybrid heterojunction synapse with efficient photoelectric dual modulation and versatility. Adv. Mater. 2019, 31, 1806227.
Crossref Google Scholar
[36]

Zhao, P. F.; Ji, R. X.; Lao, J.; Jiang, C. L.; Tian, B. B.; Luo, C. H.; Lin, H. C.; Peng, H.; Duan, C. G. Multifunctional two-terminal optoelectronic synapse based on zinc oxide/poly(3-hexylthiophene) heterojunction for neuromorphic computing. ACS Appl. Polym. Mater. 2022, 4, 5688–5695.
Crossref Google Scholar
[37]

Chen, C. S.; He, Y. L.; Mao, H. W.; Zhu, L.; Wang, X. J.; Zhu, Y.; Zhu, Y. X.; Shi, Y.; Wan, C. J.; Wan, Q. A photoelectric spiking neuron for visual depth perception. Adv. Mater. 2022, 34, 2201895.
Crossref Google Scholar
[38]

Xu, Y. C.; Zhang, G. M.; Liu, W. R.; Jin, C. X.; Nie, Y. L.; Sun, J.; Yang, J. L. Flexible multiterminal photoelectronic neurotransistors based on self-assembled rubber semiconductors for spatiotemporal information processing. SmartMat 2023, 4, e1162.
Crossref Google Scholar
[39]

Wan, C. J.; Cai, P. Q.; Guo, X. T.; Wang, M.; Matsuhisa, N.; Yang, L.; Lv, Z. S.; Luo, Y. F.; Loh, X. J.; Chen, X. D. An artificial sensory neuron with visual-haptic fusion. Nat. Commun. 2020, 11, 4602.
Crossref Google Scholar
[40]

Lee, T. J.; Yun, K. R.; Kim, S. K.; Kim, J. H.; Jin, J.; Sim, K. B.; Lee, D. H.; Hwang, G. W.; Seong, T. Y. Realization of an artificial visual nervous system using an integrated optoelectronic device array. Adv. Mater. 2021, 33, 2105485.
Crossref Google Scholar
[41]

Zeng, H. A.; Chen, Q. Z.; Shan, L. T.; Yan, Y. J.; Gao, C. S.; Lu, W. J.; Chen, H. P.; Guo, T. L. A light-emitting electrochemical artificial synapse with dual output of photoelectric signals. Sci. China Mater. 2022, 65, 2511–2520.
Crossref Google Scholar
[42]

Bian, H. Y.; Qin, X.; Wu, Y. M.; Yi, Z. G.; Liu, S. R.; Wang, Y.; Brites, C. D. S.; Carlos, L. D.; Liu, X. G. Multimodal tuning of synaptic plasticity using persistent luminescent memitters. Adv. Mater. 2022, 34, 2101895.
Crossref Google Scholar
[43]

Gao, H. K.; Miao, Z. G.; Qin, Z. S.; Yang, J. X.; Wang, T. Y.; Gao, C.; Dong, H. L.; Hu, W. P. Redistributed current density in lateral organic light-emitting transistors enabling uniform area emission with good stability and arbitrary tunability. Adv. Mater. 2022, 34, 2108795.
Crossref Google Scholar
[44]

Stelzer, F.; Röhm, A.; Vicente, R.; Fischer, I.; Yanchuk, S. Deep neural networks using a single neuron: Folded-in-time architecture using feedback-modulated delay loops. Nat. Commun. 2021, 12, 5164.
Crossref Google Scholar
[45]

Chen, Y. S.; Wang, H. L.; Luo, F.; Montes-García, V.; Liu, Z. Y.; Samorì, P. Nanofloating gate modulated synaptic organic light-emitting transistors for reconfigurable displays. Sci. Adv. 2022, 8, eabq4824.
Crossref Google Scholar
[46]

Liang, K.; Wang, R.; Huo, B. B.; Ren, H. H.; Li, D. W.; Wang, Y.; Tang, Y. J.; Chen, Y. T.; Song, C. Y.; Li, F. F. et al. Fully printed optoelectronic synaptic transistors based on quantum dot-metal oxide semiconductor heterojunctions. ACS Nano 2022, 16, 8651–8661.
Crossref Google Scholar
[47]

Zucker, R. S.; Regehr, W. G. Short-term synaptic plasticity. Annu. Rev. Physiol. 2002, 64, 355–405.
Crossref Google Scholar
[48]

John, R. A.; Liu, F. C.; Chien, N. A.; Kulkarni, M. R.; Zhu, C.; Fu, Q. D.; Basu, A.; Liu, Z.; Mathews, N. Synergistic gating of electro-iono-photoactive 2D chalcogenide neuristors: Coexistence of hebbian and homeostatic synaptic metaplasticity. Adv. Mater. 2018, 30, 1800220.
Crossref Google Scholar
[49]

Jha, P. Effect of UV irradiation on different types of luminescence of SrAl2O4:Eu,Dy phosphors. Luminescence 2016, 31, 1302–1305.
Crossref Google Scholar
[50]

Jha, P.; Chandra, B. P. Mechanoluminescence of SrAl2O4:Eu,Dy nanophosphors induced by low impact velocity. Luminescence 2017, 32, 171–176.
Crossref Google Scholar
[51]

Reese, W. M.; Burch, P.; Korpusik, A. B.; Liu, S. E.; Loskill, P.; Messersmith, P. B.; Healy, K. E. Facile macrocyclic polyphenol barrier coatings for PDMS microfluidic devices. Adv. Funct. Mater. 2020, 30, 2001274.
Crossref Google Scholar
[52]

Zhu, L. Q.; Wan, C. J.; Guo, L. Q.; Shi, Y.; Wan, Q. Artificial synapse network on inorganic proton conductor for neuromorphic systems. Nat. Commun. 2014, 5, 3158.
Crossref Google Scholar
[53]

Yu, F.; Zhu, L. Q.; Gao, W. T.; Fu, Y. M.; Xiao, H.; Tao, J.; Zhou, J. M. Chitosan-based polysaccharide-gated flexible indium tin oxide synaptic transistor with learning abilities. ACS Appl. Mater. Interfaces 2018, 10, 16881–16886.
Crossref Google Scholar
[54]

Lee, Y. R.; Trung, T. Q.; Hwang, B. U.; Lee, N. E. A flexible artificial intrinsic-synaptic tactile sensory organ. Nat. Commun. 2020, 11, 2753.
Crossref Google Scholar
Nano Research
Volume 16 Issue 7,
July 2023
Pages 10004-10010
DOI: 10.1007/s12274-023-5566-5
Cite this article:
Lu W, Chen Q, Zeng H, et al. All optical artificial synapses based on long-afterglow material for optical neural network. Nano Research, 2023, 16(7): 10004-10010. https://doi.org/10.1007/s12274-023-5566-5
Topics:
Photoluminescence

1106

Views

7

Crossref

8

Web of Science

8

Scopus

0

CSCD

Altmetrics
Received: 13 December 2022
Revised: 07 February 2023
Accepted: 09 February 2023
Published: 18 March 2023
© Tsinghua University Press 2023
Return