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

Stretchable organic electrochemical transistors via three-dimensional porous elastic semiconducting films for artificial synaptic applications

Yujie Peng1, Lin Gao1, Changjian Liu1, Jinyi Deng1, Miao Xie2, Libing Bai2, Gang Wang3, Yuhua Cheng2, Wei Huang2( ), Junsheng Yu1 ( )
State Key Laboratory of Electronic Thin Films and Integrated Devices, School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China
School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Shanghai Key Laboratory of Lightweight Structural Composites, Key Laboratory of High Performance fibers & products, Ministry of Education, Donghua University, Shanghai 201620, China
Show Author Information

Graphical Abstract

All-solid-state stretchable organic electrochemical transistor (OECT) synaptic transistors based on a three-dimensional porous semiconductor blend and ion gel electrolyte were proposed and used for neuromorphic computing. The nonvolatile memory states of such transistors could be effectively modulated by varying pulse amplitudes, widths, frequencies, and numbers, as well as the number of stacked porous blend film layers, and lead to a series of vital synaptic functions.

Abstract

Neuromorphic computing targets realizing biomimetic or intelligence systems capable of processing abundant tasks in parallel analogously to our brain, and organic electrochemical transistors (OECTs) that rely on the mixed ionic–electronic synergistic couple possess significant similarity to biological systems for implementing synaptic functions. However, the lack of reliable stretchability for synaptic OECTs, where mechanical deformation occurs, leads to consequent degradation of electrical performance. Herein, we demonstrate stretchable synaptic OECTs by adopting a three-dimensional poly(3-hexylthiophene) (P3HT)/styrene-ethylene-butylene-styrene (SEBS) blend porous elastic film for neuromorphic computing. Such architecture shows the full capability to emulate biological synaptic behaviors. Adjusting the accumulated layer numbers of porous film enables tunable OECT output and hysteresis, resulting in transition in plasticity. Especially, with a trilayer porous film, large-scale conductance and hysteresis are endorsed for efficient mimicking of memory-dependent synapse behavior. Benefitted from the interconnected three-dimensional porous structures, corresponding stretchable synaptic OECTs exhibit excellent mechanical robustness when stretched at a 30% strain, and maintain reliable electrical characteristics after 500 stretching cycles. Furthermore, near-ideal weight updates with near-zero nonlinearities, symmetricity in long-term potentiation (LTP) and depression, and applications for image simulation are validated. This work paves a universal design strategy toward high-performance stretchable neuromorphic computing architecture and could be extended to other flexible/stretchable electronics.

Keywords

organic electrochemical transistors (OECTs)artificial synapsesporous filmsflexible electronicsneuromorphic computing

Electronic Supplementary Material

Download File(s)
12274_2023_5633_MOESM1_ESM.pdf (6.2 MB)

References

[1]

Südhof, T. C. Towards an understanding of synapse formation. Neuron 2018, 100, 276–293.
Crossref Google Scholar
[2]

Ho, V. M.; Lee, J. A.; Martin, K. C. The cell biology of synaptic plasticity. Science 2011, 334, 623–628.
Crossref Google Scholar
[3]

Mead, C. Neuromorphic electronic systems. Proc. IEEE 1990, 78, 1629–1636.
Crossref Google Scholar
[4]
Yang, Y. S.; Kim, Y. Recent trend of neuromorphic computing hardware: Intel's neuromorphic system perspective. In 2020 International SoC Design Conference (ISOCC), Yeosu, Korea (South), 2020, pp 218–219.
[5]

Davies, M.; Srinivasa, N.; Lin, T. H.; Chinya, G.; Cao, Y. Q.; Choday, S. H.; Dimou, G.; Joshi, P.; Imam, N.; Jain, S. et al. Loihi: A neuromorphic manycore processor with on-chip learning. IEEE Micro 2018, 38, 82–99.
Crossref Google Scholar
[6]

Prezioso, M.; Merrikh-Bayat, F.; Hoskins, B. D.; Adam, G. C.; Likharev, K. K.; Strukov, D. B. Training and operation of an integrated neuromorphic network based on metal-oxide memristors. Nature 2015, 521, 61–64.
Crossref Google Scholar
[7]

Zidan, M. A.; Strachan, J. P.; Lu, W. D. The future of electronics based on memristive systems. Nat. Electron. 2018, 1, 22–29.
Crossref Google Scholar
[8]

Indiveri, G.; Chicca, E.; Douglas, R. A VLSI array of low-power spiking neurons and bistable synapses with spike-timing dependent plasticity. IEEE Trans. Neural Netw. 2006, 17, 211–221.
Crossref Google Scholar
[9]

Arthur, J. V.; Boahen, K. A. Silicon-neuron design: A dynamical systems approach. IEEE Trans. Circuits Syst. I Regul. Pap. 2011, 58, 1034–1043.
Crossref Google Scholar
[10]

Ielmini, D.; Wong, H. S. P. In-memory computing with resistive switching devices. Nat. Electron. 2018, 1, 333–343.
Crossref Google Scholar
[11]

van de Burgt, Y.; Melianas, A.; Keene, S. T.; Malliaras, G.; Salleo, A. Organic electronics for neuromorphic computing. Nat. Electron. 2018, 1, 386–397.
Crossref Google Scholar
[12]

Ling, H. F.; Koutsouras, D. A.; Kazemzadeh, S.; van de Burgt, Y.; Yan, F.; Gkoupidenis, P. Electrolyte-gated transistors for synaptic electronics, neuromorphic computing, and adaptable biointerfacing. Appl. Phys. Rev. 2020, 7, 011307.
Crossref Google Scholar
[13]

Merolla, P. A.; Arthur, J. V.; Alvarez-Icaza, R.; Cassidy, A. S.; Sawada, J.; Akopyan, F.; Jackson, B. L.; Imam, N.; Guo, C.; Nakamura, Y. et al. A million spiking-neuron integrated circuit with a scalable communication network and interface. Science 2014, 345, 668–673.
Crossref Google Scholar
[14]

Strukov, D. B.; Snider, G. S.; Stewart, D. R.; Williams, R. S. The missing memristor found. Nature 2008, 453, 80–83.
Crossref Google Scholar
[15]

Wang, Z. R.; Joshi, S.; Savel’ev, S. E.; Jiang, H.; Midya, R.; Lin, P.; Hu, M.; Ge, N.; Strachan, J. P.; Li, Z. Y. et al. Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing. Nat. Mater 2017, 16, 101–108.
Crossref Google Scholar
[16]

Sengupta, A.; Roy, K. Encoding neural and synaptic functionalities in electron spin: A pathway to efficient neuromorphic computing. Appl. Phys. Rev. 2017, 4, 041105.
Crossref Google Scholar
[17]
Luo, F. F.; Wu, Y. Z.; Tong, J. W.; Tian, F. B.; Zhang, X. M. Resistive switching and artificial synaptic performances of memristor based on low-dimensional bismuth halide perovskites. Nano Res., in press, https://doi.org.10.1007/s12274-023-5411-x.
[18]

van de Burgt, Y.; Lubberman, E.; Fuller, E. J.; Keene, S. T.; Faria, G. C.; Agarwal, S.; Marinella, M. J.; Alec Talin, A.; Salleo, A. A non-volatile organic electrochemical device as a low-voltage artificial synapse for neuromorphic computing. Nat. Mater. 2017, 16, 414–418.
Crossref Google Scholar
[19]

Dai, S. L.; Zhao, Y. W.; Wang, Y.; Zhang, J. Y.; Fang, L.; Jin, S.; Shao, Y. L.; Huang, J. Recent advances in transistor-based artificial synapses. Adv. Funct. Mater. 2019, 29, 1903700.
Crossref Google Scholar
[20]

Yi, W.; Savel’ev, S. E.; Medeiros-Ribeiro, G.; Miao, F.; Zhang, M. X.; Yang, J. J.; Bratkovsky, A. M.; Williams, R. S. Quantized conductance coincides with state instability and excess noise in tantalum oxide memristors. Nat. Commun. 2016, 7, 11142.
Crossref Google Scholar
[21]

Chen, R.; Canales, A.; Anikeeva, P. Neural recording and modulation technologies. Nat. Rev. Mater. 2017, 2, 16093.
Crossref Google Scholar
[22]

Gkoupidenis, P.; Koutsouras, D. A.; Malliaras, G. G. Neuromorphic device architectures with global connectivity through electrolyte gating. Nat. Commun. 2017, 8, 15448.
Crossref Google Scholar
[23]

Rivnay, J.; Inal, S.; Salleo, A.; Owens, R. M.; Berggren, M.; Malliaras, G. G. Organic electrochemical transistors. Nat. Rev. Mater. 2018, 3, 17086.
Crossref Google Scholar
[24]

Citri, A.; Malenka, R. C. Synaptic plasticity: Multiple forms, functions, and mechanisms. Neuropsychopharmacology 2008, 33, 18–41.
Crossref Google Scholar
[25]

Ji, X. D.; Paulsen, B. D.; Chik, G. K. K.; Wu, R. H.; Yin, Y. Y.; Chan, P. K. L.; Rivnay, J. Mimicking associative learning using an ion-trapping non-volatile synaptic organic electrochemical transistor. Nat. Commun. 2021, 12, 2480.
Crossref Google Scholar
[26]

Karbalaei Akbari, M.; Zhuiykov, S. A bioinspired optoelectronically engineered artificial neurorobotics device with sensorimotor functionalities. Nat. Commun. 2019, 10, 3873.
Crossref Google Scholar
[27]

Sim, K.; Rao, Z.; Ershad, F.; Yu, C. J. Rubbery electronics fully made of stretchable elastomeric electronic materials. Adv. Mater. 2020, 32, 1902417.
Crossref Google Scholar
[28]

Shim, H.; Sim, K.; Ershad, F.; Yang, P. Y.; Thukral, A.; Rao, Z.; Kim, H. J.; Liu, Y. H.; Wang, X.; Gu, G. Y. et al. Stretchable elastic synaptic transistors for neurologically integrated soft engineering systems. Sci. Adv. 2019, 5, eaax4961.
Crossref Google Scholar
[29]

Wang, L.; Yue, X. P.; Sun, Q. Z.; Zhang, L. R.; Ren, G. Z.; Lu, G.; Yu, H. D.; Huang, W. Flexible organic electrochemical transistors for chemical and biological sensing. Nano Res. 2021, 15, 2433–2464.
Google Scholar
[30]

Lee, Y.; Oh, J. Y.; Xu, W. T.; Kim, O.; Kim, T. R.; Kang, J.; Kim, Y.; Son, D.; Tok, J. B. H.; Park, M. J. et al. Stretchable organic optoelectronic sensorimotor synapse. Sci. Adv. 2018, 4, eaat7387.
Crossref Google Scholar
[31]

Chen, J. H.; Huang, W.; Zheng, D.; Xie, Z. Q.; Zhuang, X. M.; Zhao, D.; Chen, Y.; Su, N.; Chen, H. M.; Pankow, R. M. et al. Highly stretchable organic electrochemical transistors with strain-resistant performance. Nat. Mater. 2022, 21, 564–571.
Crossref Google Scholar
[32]

Shim, H.; Ershad, F.; Patel, S.; Zhang, Y. C.; Wang, B. H.; Chen, Z. H.; Marks, T. J.; Facchetti, A.; Yu, C. J. An elastic and reconfigurable synaptic transistor based on a stretchable bilayer semiconductor. Nat. Electron. 2022, 5, 660–671.
Crossref Google Scholar
[33]

Shin, M.; Oh, J. Y.; Byun, K. E.; Lee, Y. J.; Kim, B.; Baik, H. K.; Park, J. J.; Jeong, U. Polythiophene nanofibril bundles surface-embedded in elastomer: A route to a highly stretchable active channel layer. Adv. Mater. 2015, 27, 1255–1261.
Crossref Google Scholar
[34]

Guan, Y. S.; Ershad, F.; Rao, Z.; Ke, Z. F.; da Costa, E. C.; Xiang, Q.; Lu, Y. T.; Wang, X.; Mei, J. G.; Vanderslice, P. et al. Elastic electronics based on micromesh-structured rubbery semiconductor films. Nat. Electron. 2022, 5, 881–892.
Crossref Google Scholar
[35]

Shim, H.; Jang, S.; Thukral, A.; Jeong, S.; Jo, H.; Kan, B.; Patel, S.; Wei, G. D.; Lan, W.; Kim, H. J. et al. Artificial neuromorphic cognitive skins based on distributed biaxially stretchable elastomeric synaptic transistors. Proc. Natl. Acad. Sci. USA 2022, 119, e2204852119.
Crossref Google Scholar
[36]

Huang, L. Z.; Wang, Z.; Chen, J. H.; Wang, B. H.; Chen, Y.; Huang, W.; Chi, L. F.; Marks, T. J.; Facchetti, A. Porous semiconducting polymers enable high-performance electrochemical transistors. Adv. Mater. 2021, 33, e2007041.
Crossref Google Scholar
[37]

Zhang, A. J.; Bai, H.; Li, L. Breath figure: A nature-inspired preparation method for ordered porous films. Chem. Rev. 2015, 115, 9801–9868.
Crossref Google Scholar
[38]

Guan, Y. S.; Yu, C. J. Interfacial assembly of metallic nanomembranes for highly stretchable conductors. Matter 2022, 5, 15–17.
Crossref Google Scholar
[39]

Li, E. L.; Wu, X. M.; Chen, Q. Z.; Wu, S. Y.; He, L. H.; Yu, R. J.; Hu, Y. Y.; Chen, H. P.; Guo, T. L. Nanoscale channel organic ferroelectric synaptic transistor array for high recognition accuracy neuromorphic computing. Nano Energy 2021, 85, 106010.
Crossref Google Scholar
[40]

Wang, N. X.; Xie, L. P.; Ling, H. F.; Piradi, V.; Li, L.; Wang, X. Z.; Zhu, X. J.; Yan, F. Ethylenedioxythiophene incorporated diketopyrrolopyrrole conjugated polymers for high-performance organic electrochemical transistors. J. Mater. Chem. C 2021, 9, 4260–4266.
Crossref Google Scholar
[41]

Dai, S. L.; Dai, Y. H.; Zhao, Z. X.; Xia, F. F.; Li, Y.; Liu, Y. D.; Cheng, P.; Strzalka, J.; Li, S. S.; Li, N. et al. Intrinsically stretchable neuromorphic devices for on-body processing of health data with artificial intelligence. Matter 2022, 5, 3375–3390.
Crossref Google Scholar
[42]

Zucker, R. S.; Regehr, W. G. Short-term synaptic plasticity. Annu. Rev. Physiol. 2002, 64, 355–405.
Crossref Google Scholar
[43]

Abbott, L. F.; Regehr, W. G. Synaptic computation. Nature 2004, 431, 796–803.
Crossref Google Scholar
[44]

Li, S. Z.; Zeng, F.; Chen, C.; Liu, H. Y.; Tang, G. S.; Gao, S.; Song, C.; Lin, Y. S.; Pan, F.; Guo, D. Synaptic plasticity and learning behaviours mimicked through Ag interface movement in an Ag/conducting polymer/Ta memristive system. J. Mater. Chem. C 2013, 1, 5292–5298.
Crossref Google Scholar
[45]

Oh, J. Y.; Son, D.; Katsumata, T.; Lee, Y.; Kim, Y.; Lopez, J.; Wu, H. C.; Kang, J.; Park, J.; Gu, X. D. et al. Stretchable self-healable semiconducting polymer film for active-matrix strain-sensing array. Sci. Adv. 2019, 5, eaav3097.
Crossref Google Scholar
[46]

Yang, C. S.; Shang, D. S.; Liu, N.; Shi, G.; Shen, X.; Yu, R. C.; Li, Y. Q.; Sun, Y. N. A synaptic transistor based on quasi-2D molybdenum oxide. Adv. Mater. 2017, 29, 1700906.
Crossref Google Scholar
[47]

Wang, J. X.; Chen, Y.; Kong, L. A.; Fu, Y.; Gao, Y. L.; Sun, J. Deep-ultraviolet-triggered neuromorphic functions in In-Zn-O phototransistors. Appl. Phys. Lett. 2018, 113, 151101.
Crossref Google Scholar
[48]

Jin, C. X.; Liu, W. R.; Huang, Y. L.; Xu, Y. C.; Nie, Y. L.; Zhang, G. M.; He, P.; Sun, J.; Yang, J. L. Printable ion-gel-gated In2O3 synaptic transistor array for neuro-inspired memory. Appl. Phys. Lett. 2022, 120, 233701.
Crossref Google Scholar
[49]

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
Nano Research
Volume 16 Issue 7,
July 2023
Pages 10206-10214
DOI: 10.1007/s12274-023-5633-y
Cite this article:
Peng Y, Gao L, Liu C, et al. Stretchable organic electrochemical transistors via three-dimensional porous elastic semiconducting films for artificial synaptic applications. Nano Research, 2023, 16(7): 10206-10214. https://doi.org/10.1007/s12274-023-5633-y
Topics:
Devices

1354

Views

20

Crossref

22

Web of Science

22

Scopus

1

CSCD

Altmetrics
Received: 09 January 2023
Revised: 14 February 2023
Accepted: 01 March 2023
Published: 24 April 2023
© Tsinghua University Press 2023
Return