Issue

Vol. 18 (2026)

Organic Phototransistor Photonic Synapses for Artificial Vision

https://doi.org/10.1007/s40820-025-02036-0
Feng Ding
State Key Laboratory of Bioinspired Interfacial Materials Science, Institute of Functional Nano and Soft Materials (FUNSOM), Soochow University, Suzhou 215123, People’s Republic of China
Di Xue
State Key Laboratory of Bioinspired Interfacial Materials Science, Institute of Functional Nano and Soft Materials (FUNSOM), Soochow University, Suzhou 215123, People’s Republic of China
Lifeng Chi
State Key Laboratory of Bioinspired Interfacial Materials Science, Institute of Functional Nano and Soft Materials (FUNSOM), Soochow University, Suzhou 215123, People’s Republic of China
Lizhen Huang
State Key Laboratory of Bioinspired Interfacial Materials Science, Institute of Functional Nano and Soft Materials (FUNSOM), Soochow University, Suzhou 215123, People’s Republic of China

Corresponding Author: Lizhen Huang

lzhuang@suda.edu.cn

Nano-Micro Letters, Vol. 18 (2026), Article Number: 203

Abstract

The von Neumann architecture faces significant limitations, including low transmission efficiency and high energy consumption, when handling large-scale data and unstructured problems. Benefiting from the inherent merits of optical signals including high bandwidth, near-zero Joule heating, fast transmission speed, and immunity to electromagnetic interference, photonics provides a powerful pathway for high-speed neuromorphic computing. Together with the mechanical flexibility and largearea manufacturability of organic semiconductors, organic phototransistor (OPT)-based photonic synapses have therefore attracted extensive attention in recent years. This review provides a comprehensive overview of recent advances in OPT-based photonic synapses, covering operational principles, active materials, advances in bidirectional photoresponse process, as well as cutting-edge applications. Finally, the current challenges and opportunities in this field are highlighted. Distinct from previous reviews, this review emphasizes an in-depth exploration of bidirectional photoresponse mechanisms, a systematic dissection of material–structure–function correlations enabling integrated sensing-memory technology, and emerging.


Highlights:
1 The latest progress in neuromorphic artificial synapses based on organic phototransistors is reviewed from three aspects: functional semiconductor materials, operating behaviors, and frontier applications/advancements.
2 The negative photoconductance behavior of novel phototransistors is discussed, along with their fascinating information-erasing capabilities demonstrated in organic photonic synapses.
3 Frontier applications and advancements in neuromorphic vision driven by organic photonic synapses, such as human visual adaptation, polarization-sensitive detection, high-dimensional reservoir computing, and multimodal neuromorphic encryption, are demonstrated.

Keywords

Transistor Organic semiconductors Negative photoconductance Photonic synapse Neuromorphic computing
Ding, Feng, Di Xue, Lifeng Chi, and Lizhen Huang. 2026. “Organic Phototransistor Photonic Synapses for Artificial Vision”. Nano-Micro Letters 18 (January):203. https://doi.org/10.1007/s40820-025-02036-0.
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References
  1. J. von Neumann, The principles of large-scale computing machines. IEEE Ann. Hist. Comput. 10(4), 243–256 (1988). https://doi.org/10.1109/MAHC.1988.10045
  2. P.A. Merolla, J.V. Arthur, R. Alvarez-Icaza, A.S. Cassidy, J. Sawada et al., Artificial brains. A million spiking-neuron integrated circuit with a scalable communication network and interface. Science 345(6197), 668–673 (2014). https://doi.org/10.1126/science.1254642
  3. K. Sun, J. Chen, X. Yan, The future of memristors: materials engineering and neural networks. Adv. Funct. Mater. 31(8), 2006773 (2021). https://doi.org/10.1002/adfm.202006773
  4. Y. Xiao, B. Jiang, Z. Zhang, S. Ke, Y. Jin et al., A review of memristor: material and structure design, device performance, applications and prospects. Sci. Technol. Adv. Mater. 24(1), 2162323 (2023). https://doi.org/10.1080/14686996.2022.2162323
  5. D. Attwell, S.B. Laughlin, An energy budget for signaling in the grey matter of the brain. J. Cereb. Blood Flow Metab. 21(10), 1133–1145 (2001). https://doi.org/10.1097/00004647-200110000-00001
  6. D.A. Drachman, Do we have brain to spare? Neurology 64(12), 2004–2005 (2005). https://doi.org/10.1212/01.wnl.0000166914.38327.bb
  7. G. Indiveri, S.-C. Liu, Memory and information processing in neuromorphic systems. Proc. IEEE 103(8), 1379–1397 (2015). https://doi.org/10.1109/JPROC.2015.2444094
  8. M. Prezioso, F. Merrikh-Bayat, B.D. Hoskins, G.C. Adam, K.K. Likharev et al., Training and operation of an integrated neuromorphic network based on metal-oxide memristors. Nature 521(7550), 61–64 (2015). https://doi.org/10.1038/nature14441
  9. Y. Li, Z. Wang, R. Midya, Q. Xia, J.J. Yang, Review of memristor devices in neuromorphic computing: materials sciences and device challenges. J. Phys. D Appl. Phys. 51(50), 503002 (2018). https://doi.org/10.1088/1361-6463/aade3f
  10. S.K. Esser, P.A. Merolla, J.V. Arthur, A.S. Cassidy, R. Appuswamy et al., Convolutional networks for fast, energy-efficient neuromorphic computing. Proc. Natl. Acad. Sci. U. S. A. 113(41), 11441–11446 (2016). https://doi.org/10.1073/pnas.1604850113
  11. Z. Cheng, C. Ríos, W.H.P. Pernice, C.D. Wright, H. Bhaskaran, On-chip photonic synapse. Sci. Adv. 3(9), e1700160 (2017). https://doi.org/10.1126/sciadv.1700160
  12. P. Gkoupidenis, D.A. Koutsouras, G.G. Malliaras, Neuromorphic device architectures with global connectivity through electrolyte gating. Nat. Commun. 8, 15448 (2017). https://doi.org/10.1038/ncomms15448
  13. G. Wang, R. Wang, W. Kong, J. Zhang, Simulation of retinal ganglion cell response using fast independent component analysis. Cogn. Neurodyn. 12(6), 615–624 (2018). https://doi.org/10.1007/s11571-018-9490-4
  14. C.S. Yang, D.S. Shang, N. Liu, G. Shi, X. Shen et al., A synaptic transistor based on quasi-2D molybdenum oxide. Adv. Mater. 29(27), 1700906 (2017). https://doi.org/10.1002/adma.201700906
  15. Q. Zhang, T. Jin, X. Ye, D. Geng, W. Chen et al., Organic field effect transistor-based photonic synapses: materials, devices, and applications. Adv. Funct. Mater. 31(49), 2106151 (2021). https://doi.org/10.1002/adfm.202106151
  16. S. Dai, Y. Zhao, Y. Wang, J. Zhang, L. Fang et al., Recent advances in transistor-based artificial synapses. Adv. Funct. Mater. 29(42), 1903700 (2019). https://doi.org/10.1002/adfm.201903700
  17. S. Lan, Y. Ke, H. Chen, Photonic synaptic transistor based on P-type organic semiconductor blending with N-type organic semiconductor. IEEE Electron Device Lett. 42(8), 1180–1183 (2021). https://doi.org/10.1109/LED.2021.3090906
  18. G. Lee, Y.E. Kim, H. Kim, H.-K. Lee, J.Y. Park et al., Organic synaptic transistors and printed circuit board defect inspection with photonic stimulation: a novel approach using oblique angle deposition. Small 21(25), 2501997 (2025). https://doi.org/10.1002/smll.202501997
  19. C. Xiang, D. Xue, H. Liu, Q. Wang, X. Jiang et al., Organic photonic synapses with UV–vis–NIR broadband perception based on organic electrochemical transistors. ACS Appl. Mater. Interfaces 17(24), 35822–35832 (2025). https://doi.org/10.1021/acsami.5c07976
  20. D. Dutta, S. Mukherjee, M. Uzhansky, E. Koren, Cross-field optoelectronic modulation via inter-coupled ferroelectricity in 2D In2Se3. NPJ 2D Mater. Appl. 5, 81 (2021). https://doi.org/10.1038/s41699-021-00261-w
  21. L. Fang, S. Dai, Y. Zhao, D. Liu, J. Huang, Light-stimulated artificial synapses based on 2D organic field-effect transistors. Adv. Electron. Mater. 6(1), 1901217 (2020). https://doi.org/10.1002/aelm.201901217
  22. W. Wang, S. Gao, Y. Li, W. Yue, H. Kan et al., Artificial optoelectronic synapses based on TiNxO2–x/MoS2 heterojunction for neuromorphic computing and visual system. Adv. Funct. Mater. 31(34), 2101201 (2021). https://doi.org/10.1002/adfm.202101201
  23. B. Pradhan, S. Das, J. Li, F. Chowdhury, J. Cherusseri et al., Ultrasensitive and ultrathin phototransistors and photonic synapses using perovskite quantum dots grown from graphene lattice. Sci. Adv. 6(7), eaay5225 (2020). https://doi.org/10.1126/sciadv.aay5225
  24. B. Gholipour, P. Bastock, C. Craig, K. Khan, D. Hewak et al., Amorphous metal-sulphide microfibers enable photonic synapses for brain-like computing. Adv. Opt. Mater. 3(5), 635–641 (2015). https://doi.org/10.1002/adom.201400472
  25. J.-Y. Wu, Y.T. Chun, S. Li, T. Zhang, J. Wang et al., Broadband MoS2 field-effect phototransistors: ultrasensitive visible-light photoresponse and negative infrared photoresponse. Adv. Mater. 30(7), 1705880 (2018). https://doi.org/10.1002/adma.201705880
  26. Q. Wu, J. Wang, J. Cao, C. Lu, G. Yang et al., Photoelectric plasticity in oxide thin film transistors with tunable synaptic functions. Adv. Electron. Mater. 4(12), 1800556 (2018). https://doi.org/10.1002/aelm.201800556
  27. R. Karimi Azari, L.P. Camargo, J.R.H. Garza, L. Collins, W. Yu Tsai et al., Emulation of synaptic plasticity in WO3-based ion-gated transistors. Adv. Electron. Mater. 11(8), 2400807 (2025). https://doi.org/10.1002/aelm.202400807
  28. Y. Lee, T.-W. Lee, Organic synapses for neuromorphic electronics: from brain-inspired computing to sensorimotor nervetronics. Acc. Chem. Res. 52(4), 964–974 (2019). https://doi.org/10.1021/acs.accounts.8b00553
  29. H. Dong, H. Zhu, Q. Meng, X. Gong, W. Hu, Organic photoresponse materials and devices. Chem. Soc. Rev. 41(5), 1754–1808 (2012). https://doi.org/10.1039/c1cs15205j
  30. H. Chen, Y. Cai, Y. Han, H. Huang, Towards artificial visual sensory system: organic optoelectronic synaptic materials and devices. Angew. Chem. Int. Ed. 63(1), e202313634 (2024). https://doi.org/10.1002/anie.202313634
  31. J. Stollberg, Synapse elimination, the size principle, and Hebbian synapses. J. Neurobiol. 26(2), 273–282 (1995). https://doi.org/10.1002/neu.480260211
  32. L. Wang, R.S.T. Lee, Excitatory and inhibitory neuronal synapse unit: a novel recurrent cell for time series prediction. Neurocomputing 594, 127858 (2024). https://doi.org/10.1016/j.neucom.2024.127858
  33. Y. Bai, T. Suzuki, Activity-dependent synaptic plasticity in Drosophila melanogaster. Front. Physiol. 11, 161 (2020). https://doi.org/10.3389/fphys.2020.00161
  34. M. DiNuzzo, F. Giove, Activity-dependent energy budget for neocortical signaling: effect of short-term synaptic plasticity on the energy expended by spiking and synaptic activity. J. Neurosci. Res. 90(11), 2094–2102 (2012). https://doi.org/10.1002/jnr.23098
  35. F. Gobbo, A. Cattaneo, Neuronal activity at synapse resolution: reporters and effectors for synaptic neuroscience. Front. Mol. Neurosci. 13, 572312 (2020). https://doi.org/10.3389/fnmol.2020.572312
  36. C. Wu, T. Ruan, Y. Yuan, C. Xu, L. Du et al., Alterations in synaptic connectivity and synaptic transmission in Alzheimer’s disease with high physical activity. J. Alzheimers Dis. 99(3), 1005–1022 (2024). https://doi.org/10.3233/JAD-240123
  37. Y. Ozaki, A. Soya, J. Nakamura, T. Matsumoto, Y. Ueta, Potentiation by angiotensin II of spontaneous excitatory postsynaptic currents in rat supraoptic magnocellular neurones. J. Neuroendocrinol. 16(11), 871–879 (2004). https://doi.org/10.1111/j.1365-2826.2004.01244.x
  38. J.-J. Zhang, X.-D. Liu, L.-C. Yu, Influences of morphine on the spontaneous and evoked excitatory postsynaptic currents in lateral amygdala of rats. Physiol. Res. 65(1), 165–169 (2016). https://doi.org/10.33549/physiolres.933027
  39. A. Dvorzhak, O. Myakhar, A. Kamkin, K. Kirmse, S. Kirischuk, Postsynaptically different inhibitory postsynaptic currents in Cajal-Retzius cells in the developing neocortex. NeuroReport 19(12), 1213–1216 (2008). https://doi.org/10.1097/WNR.0b013e328308daa0
  40. B. Szabo, L. Dörner, C. Pfreundtner, W. Nörenberg, K. Starke, Inhibition of GABAergic inhibitory postsynaptic currents by cannabinoids in rat corpus striatum. Neuroscience 85(2), 395–403 (1998). https://doi.org/10.1016/S0306-4522(97)00597-6
  41. K.C. Bittner, A.D. Milstein, C. Grienberger, S. Romani, J.C. Magee, Behavioral time scale synaptic plasticity underlies CA1 place fields. Science 357(6355), 1033–1036 (2017). https://doi.org/10.1126/science.aan3846
  42. J.C. Magee, C. Grienberger, Synaptic plasticity forms and functions. Annu. Rev. Neurosci. 43, 95–117 (2020). https://doi.org/10.1146/annurev-neuro-090919-022842
  43. S.L. Jackman, W.G. Regehr, The mechanisms and functions of synaptic facilitation. Neuron 94(3), 447–464 (2017). https://doi.org/10.1016/j.neuron.2017.02.047
  44. L.Q. Zhu, C.J. Wan, L.Q. Guo, Y. Shi, Q. Wan, Artificial synapse network on inorganic proton conductor for neuromorphic systems. Nat. Commun. 5, 3158 (2014). https://doi.org/10.1038/ncomms4158
  45. D.M. Bannerman, R. Sprengel, D.J. Sanderson, S.B. McHugh, J.N.P. Rawlins et al., Hippocampal synaptic plasticity, spatial memory and anxiety. Nat. Rev. Neurosci. 15(3), 181–192 (2014). https://doi.org/10.1038/nrn3677
  46. S. Grover, W. Wen, V. Viswanathan, C.T. Gill, R.M.G. Reinhart, Long-lasting, dissociable improvements in working memory and long-term memory in older adults with repetitive neuromodulation. Nat. Neurosci. 25(9), 1237–1246 (2022). https://doi.org/10.1038/s41593-022-01132-3
  47. M.-K. Kim, J.-S. Lee, Short-term plasticity and long-term potentiation in artificial biosynapses with diffusive dynamics. ACS Nano 12(2), 1680–1687 (2018). https://doi.org/10.1021/acsnano.7b08331
  48. S. Gao, G. Liu, H. Yang, C. Hu, Q. Chen et al., An oxide Schottky junction artificial optoelectronic synapse. ACS Nano 13(2), 2634–2642 (2019). https://doi.org/10.1021/acsnano.9b00340
  49. C. Lu, J. Meng, J. Song, T. Wang, H. Zhu et al., Self-rectifying all-optical modulated optoelectronic multistates memristor crossbar array for neuromorphic computing. Nano Lett. 24(5), 1667–1672 (2024). https://doi.org/10.1021/acs.nanolett.3c04358
  50. N. Li, C. He, Q. Wang, J. Tang, Q. Zhang et al., Gate-tunable large-scale flexible monolayer MoS2 devices for photodetectors and optoelectronic synapses. Nano Res. 15(6), 5418–5424 (2022). https://doi.org/10.1007/s12274-022-4122-z
  51. J. Zhu, Y. Yang, R. Jia, Z. Liang, W. Zhu et al., Ion gated synaptic transistors based on 2D van der Waals crystals with tunable diffusive dynamics. Adv. Mater. 30(21), 1800195 (2018). https://doi.org/10.1002/adma.201800195
  52. R.S. Zucker, W.G. Regehr, Short-term synaptic plasticity. Annu. Rev. Physiol. 64, 355–405 (2002). https://doi.org/10.1146/annurev.physiol.64.092501.114547
  53. C. Tian, J. Ma, C. Zhang, P. Zhan, A deep neural network model for short-term load forecast based on long short-term memory network and convolutional neural network. Energies 11(12), 3493 (2018). https://doi.org/10.3390/en11123493
  54. H. Zhou, Y. Zhang, L. Yang, Q. Liu, K. Yan et al., Short-term photovoltaic power forecasting based on long short term memory neural network and attention mechanism. IEEE Access 7, 78063–78074 (2019). https://doi.org/10.21227/9hje-dz22
  55. H.-K. He, R. Yang, W. Zhou, H.-M. Huang, J. Xiong et al., Photonic potentiation and electric habituation in ultrathin memristive synapses based on monolayer MoS2. Small 14(15), 1800079 (2018). https://doi.org/10.1002/smll.201800079
  56. K. Pilarczyk, A. Podborska, M. Lis, M. Kawa, D. Migdal et al., Synaptic behavior in an optoelectronic device based on semiconductor-nanotube hybrid. Adv. Electron. Mater. 2(6), 1500471 (2016). https://doi.org/10.1002/aelm.201500471
  57. C.-S. Yang, D.-S. Shang, Y.-S. Chai, L.-Q. Yan, B.-G. Shen et al., Electrochemical-reaction-induced synaptic plasticity in MoOx-based solid state electrochemical cells. Phys. Chem. Chem. Phys. 19(6), 4190–4198 (2017). https://doi.org/10.1039/c6cp06004h
  58. S.W. Cho, S.M. Kwon, M. Lee, J.-W. Jo, J.S. Heo et al., Multi-spectral gate-triggered heterogeneous photonic neuro-transistors for power-efficient brain-inspired neuromorphic computing. Nano Energy 66, 104097 (2019). https://doi.org/10.1016/j.nanoen.2019.104097
  59. Y.B. Guo, L.Q. Zhu, W.T. Gao, Z.Y. Ren, H. Xiao et al., Low-voltage protonic/photonic synergic coupled oxide phototransistor. Org. Electron. 71, 31–35 (2019). https://doi.org/10.1016/j.orgel.2019.04.038
  60. M.L. Schneider, C.A. Donnelly, S.E. Russek, B. Baek, M.R. Pufall et al., Ultralow power artificial synapses using nanotextured magnetic Josephson junctions. Sci. Adv. 4(1), e1701329 (2018). https://doi.org/10.1126/sciadv.1701329
  61. G. Indiveri, E. Chicca, R. Douglas, A VLSI array of low-power spiking neurons and bistable synapses with spike-timing dependent plasticity. IEEE Trans. Neural Netw. 17(1), 211–221 (2006). https://doi.org/10.1109/TNN.2005.860850
  62. Y. van de Burgt, E. Lubberman, E.J. Fuller, S.T. Keene, G.C. Faria et al., A non-volatile organic electrochemical device as a low-voltage artificial synapse for neuromorphic computing. Nat. Mater. 16(4), 414–418 (2017). https://doi.org/10.1038/nmat4856
  63. F. Teng, K. Hu, W. Ouyang, X. Fang, Photoelectric detectors based on inorganic p-type semiconductor materials. Adv. Mater. 30(35), e1706262 (2018). https://doi.org/10.1002/adma.201706262
  64. W. Ouyang, F. Teng, J.-H. He, X. Fang, Enhancing the photoelectric performance of photodetectors based on metal oxide semiconductors by charge-carrier engineering. Adv. Funct. Mater. 29(9), 1807672 (2019). https://doi.org/10.1002/adfm.201807672
  65. S. Li, L. Zhan, C. Sun, H. Zhu, G. Zhou et al., Highly efficient fullerene-free organic solar cells operate at near zero highest occupied molecular orbital offsets. J. Am. Chem. Soc. 141(7), 3073–3082 (2019). https://doi.org/10.1021/jacs.8b12126
  66. C. Sun, S. Qin, R. Wang, S. Chen, F. Pan et al., High efficiency polymer solar cells with efficient hole transfer at zero highest occupied molecular orbital offset between methylated polymer donor and brominated acceptor. J. Am. Chem. Soc. 142(3), 1465–1474 (2020). https://doi.org/10.1021/jacs.9b09939
  67. Y. Yuan, G. Giri, A.L. Ayzner, A.P. Zoombelt, S.C.B. Mannsfeld et al., Ultra-high mobility transparent organic thin film transistors grown by an off-centre spin-coating method. Nat. Commun. 5, 3005 (2014). https://doi.org/10.1038/ncomms4005
  68. P.E. Shaw, A. Ruseckas, I.D.W. Samuel, Exciton diffusion measurements in poly(3-hexylthiophene). Adv. Mater. 20(18), 3516–3520 (2008). https://doi.org/10.1002/adma.200800982
  69. K.-J. Baeg, M. Binda, D. Natali, M. Caironi, Y.-Y. Noh, Organic light detectors: photodiodes and phototransistors. Adv. Mater. 25(31), 4267–4295 (2013). https://doi.org/10.1002/adma.201204979
  70. M.A. Brady, G.M. Su, M.L. Chabinyc, Recent progress in the morphology of bulk heterojunction photovoltaics. Soft Matter 7(23), 11065 (2011). https://doi.org/10.1039/c1sm06147j
  71. M.A. Ruderer, P. Müller-Buschbaum, Morphology of polymer-based bulk heterojunction films for organic photovoltaics. Soft Matter 7(12), 5482 (2011). https://doi.org/10.1039/c0sm01502d
  72. T. Sun, B. Feng, J. Huo, Y. Xiao, W. Wang et al., Artificial intelligence meets flexible sensors: emerging smart flexible sensing systems driven by machine learning and artificial synapses. Nano-Micro Lett. 16(1), 14 (2023). https://doi.org/10.1007/s40820-023-01235-x
  73. X. Bai, X. Zhang, Artificial intelligence-powered materials science. Nano-Micro Lett. 17(1), 135 (2025). https://doi.org/10.1007/s40820-024-01634-8
  74. K. He, C. Wang, Y. He, J. Su, X. Chen, Artificial neuron devices. Chem. Rev. 123(23), 13796–13865 (2023). https://doi.org/10.1021/acs.chemrev.3c00527
  75. S. Wang, X. Shi, J. Gong, W. Liu, C. Jin et al., Artificial retina based on organic heterojunction transistors for mobile recognition. Nano Lett. 24(10), 3204–3212 (2024). https://doi.org/10.1021/acs.nanolett.4c00087
  76. B. Mu, L. Guo, J. Liao, P. Xie, G. Ding et al., Near-infrared artificial synapses for artificial sensory neuron system. Small 17(38), e2103837 (2021). https://doi.org/10.1002/smll.202103837
  77. S. Kang, S. Sohn, H. Kim, H.J. Yun, B.C. Jang et al., Imitating synapse behavior: exploiting off-current in TPBi-doped small molecule phototransistors for broadband wavelength recognition. ACS Appl. Mater. Interfaces 16(9), 11758–11766 (2024). https://doi.org/10.1021/acsami.3c17855
  78. J. Anderson, B. Anderson, The myth of persistence of vision revisited. J. Film Video 45(1), 3–12 (1993)
  79. Y. Gu, Z. Guo, W. Yuan, M. Kong, Y. Liu et al., High-sensitivity imaging of time-domain near-infrared light transducer. Nat. Photonics 13(8), 525–531 (2019). https://doi.org/10.1038/s41566-019-0437-z
  80. L. Jiang, T. Chen, E. Song, Y. Fan, D. Min et al., High-performance near-infrared fluorescence probe for fast and specific visualization of harmful sulfite in food, living cells, and zebrafish. Chem. Eng. J. 427, 131563 (2022). https://doi.org/10.1016/j.cej.2021.131563
  81. Y. Yang, Y. Xie, F. Zhang, Second near-infrared window fluorescence nanoprobes for deep-tissue in vivo multiplexed bioimaging. Adv. Drug Deliv. Rev. 193, 114697 (2023). https://doi.org/10.1016/j.addr.2023.114697
  82. X. Zhao, C. Li, H. Qi, J. Huang, Y. Xu et al., Integrated near-infrared fiber-optic photoacoustic sensing demodulator for ultra-high sensitivity gas detection. Photoacoustics 33, 100560 (2023). https://doi.org/10.1016/j.pacs.2023.100560
  83. Z. Lv, Y. Wang, J. Chen, J. Wang, Y. Zhou et al., Semiconductor quantum dots for memories and neuromorphic computing systems. Chem. Rev. 120(9), 3941–4006 (2020). https://doi.org/10.1021/acs.chemrev.9b00730
  84. N.P. Dasgupta, J. Sun, C. Liu, S. Brittman, S.C. Andrews et al., 25th anniversary : semiconductor nanowires: synthesis, characterization, and applications. Adv. Mater. 26(14), 2137–2184 (2014). https://doi.org/10.1002/adma.201305929
  85. H. Zhang, Ö. Gül, S. Conesa-Boj, M.P. Nowak, M. Wimmer et al., Ballistic superconductivity in semiconductor nanowires. Nat. Commun. 8, 16025 (2017). https://doi.org/10.1038/ncomms16025
  86. Y. Tong, B.J. Bohn, E. Bladt, K. Wang, P. Müller-Buschbaum et al., From precursor powders to CsPbX3 perovskite nanowires: one-pot synthesis, growth mechanism, and oriented self-assembly. Angew. Chem. Int. Ed. 56(44), 13887–13892 (2017). https://doi.org/10.1002/anie.201707224
  87. G. Zhou, L. Xu, G. Hu, L. Mai, Y. Cui, Nanowires for electrochemical energy storage. Chem. Rev. 119(20), 11042–11109 (2019). https://doi.org/10.1021/acs.chemrev.9b00326
  88. Y.-J. Kim, C.-H. Cho, K. Paek, M. Jo, M.-K. Park et al., Precise control of quantum dot location within the P3HT-b-P2VP/QD nanowires formed by crystallization-driven 1D growth of hybrid dimeric seeds. J. Am. Chem. Soc. 136(7), 2767–2774 (2014). https://doi.org/10.1021/ja410165f
  89. S. Ren, L.-Y. Chang, S.-K. Lim, J. Zhao, M. Smith et al., Inorganic–organic hybrid solar cell: bridging quantum dots to conjugated polymer nanowires. Nano Lett. 11(9), 3998–4002 (2011). https://doi.org/10.1021/nl202435t
  90. Z. Zhang, S. Wang, Z. Wang, L. Ding, T. Pei et al., Almost perfectly symmetric SWCNT-based CMOS devices and scaling. ACS Nano 3(11), 3781–3787 (2009). https://doi.org/10.1021/nn901079p
  91. Q. Cao, H.-S. Kim, N. Pimparkar, J.P. Kulkarni, C. Wang et al., Medium-scale carbon nanotube thin-film integrated circuits on flexible plastic substrates. Nature 454(7203), 495–500 (2008). https://doi.org/10.1038/nature07110
  92. S.J. Tans, A.R.M. Verschueren, C. Dekker, Room-temperature transistor based on a single carbon nanotube. Nature 393(6680), 49–52 (1998). https://doi.org/10.1038/29954
  93. Z. Zhang, S. Wang, L. Ding, X. Liang, T. Pei et al., Self-aligned ballistic n-type single-walled carbon nanotube field-effect transistors with adjustable threshold voltage. Nano Lett. 8(11), 3696–3701 (2008). https://doi.org/10.1021/nl8018802
  94. X. Li, S. Chen, P.-F. Liu, Y. Zhang, Y. Chen et al., Evidence for ferroelectricity of all-inorganic perovskite CsPbBr3 quantum dots. J. Am. Chem. Soc. 142(7), 3316–3320 (2020). https://doi.org/10.1021/jacs.9b12254
  95. Y. Chen, Y. Chu, X. Wu, W. Ou-Yang, J. Huang, High-performance inorganic perovskite quantum dot-organic semiconductor hybrid phototransistors. Adv. Mater. 29(44), 1704062 (2017). https://doi.org/10.1002/adma.201704062
  96. K. Wang, S. Dai, Y. Zhao, Y. Wang, C. Liu et al., Light-stimulated synaptic transistors fabricated by a facile solution process based on inorganic perovskite quantum dots and organic semiconductors. Small 15(11), 1900010 (2019). https://doi.org/10.1002/smll.201900010
  97. D. Hao, J. Zhang, S. Dai, J. Zhang, J. Huang, Perovskite/organic semiconductor-based photonic synaptic transistor for artificial visual system. ACS Appl. Mater. Interfaces 12(35), 39487–39495 (2020). https://doi.org/10.1021/acsami.0c10851
  98. D. Hao, J. Zou, J. Huang, Recent developments in flexible photodetectors based on metal halide perovskite. InfoMat 2(1), 139–169 (2020). https://doi.org/10.1002/inf2.12053
  99. Q. Shi, D. Liu, D. Hao, J. Zhang, L. Tian et al., Printable, ultralow-power ternary synaptic transistors for multifunctional information processing system. Nano Energy 87, 106197 (2021). https://doi.org/10.1016/j.nanoen.2021.106197
  100. J. Kuang, K. Liu, M. Liu, M. Shao, M. Zhu et al., Interface defects tuning in polymer-perovskite phototransistors for visual synapse and adaptation functions. Adv. Funct. Mater. 33(5), 2209502 (2023). https://doi.org/10.1002/adfm.202209502
  101. Z. Zhao, Z. Hu, M. Deng, E. Hong, P. Wang et al., Bias-switchable photodetection and photosynapse dual-functional devices based on 2D perovskite/organic heterojunction for imaging-to-recognition conversion. Adv. Mater. 37(5), 2416033 (2025). https://doi.org/10.1002/adma.202416033
  102. S. Feng, J. Li, L. Feng, Z. Liu, J. Wang et al., Dual-mode conversion of photodetector and neuromorphic vision sensor via bias voltage regulation on a single device. Adv. Mater. 35(49), e2308090 (2023). https://doi.org/10.1002/adma.202308090
  103. C. Fu, J. Yang, J. Wang, S. Luo, L. Luo et al., Dual-mode semiconductor device enabling optoelectronic detection and neuromorphic processing with extended spectral responsivity. Adv. Mater. 36(49), e2409406 (2024). https://doi.org/10.1002/adma.202409406
  104. E. Ercan, Y.-C. Lin, W.-C. Yang, W.-C. Chen, Self-assembled nanostructures of quantum dot/conjugated polymer hybrids for photonic synaptic transistors with ultralow energy consumption and zero-gate bias. Adv. Funct. Mater. 32(6), 2107925 (2022). https://doi.org/10.1002/adfm.202107925
  105. X. Luo, W. Deng, F. Sheng, X. Ren, Z. Zhao et al., Bionic scotopic adaptation transistors for nighttime low illumination imaging. ACS Nano 18(21), 13726–13737 (2024). https://doi.org/10.1021/acsnano.4c01663
  106. Y. Wang, Z. Lv, J. Chen, Z. Wang, Y. Zhou et al., Photonic synapses based on inorganic perovskite quantum dots for neuromorphic computing. Adv. Mater. 30(38), 1802883 (2018). https://doi.org/10.1002/adma.201802883
  107. D. Uddin, B.G. Jeffrey, O. Flynn, W. Wong, H. Wiley et al., Repeatability of scotopic sensitivity and dark adaptation using a medmont dark-adapted chromatic perimeter in age-related macular degeneration. Transl. Vis. Sci. Technol. 9(7), 31 (2020). https://doi.org/10.1167/tvst.9.7.31
  108. G.R. Jackson, C. Owsley, E. Price Cordle, C.D. Finley, Aging and scotopic sensitivity. Vis. Res. 38(22), 3655–3662 (1998). https://doi.org/10.1016/S0042-6989(98)00044-3
  109. S. Hong, S.H. Choi, J. Park, H. Yoo, J.Y. Oh et al., Sensory adaptation and neuromorphic phototransistors based on CsPb(Br1–xIx)3 perovskite and MoS2 hybrid structure. ACS Nano 14(8), 9796–9806 (2020). https://doi.org/10.1021/acsnano.0c01689
  110. C. Jin, W. Liu, Y. Xu, Y. Huang, Y. Nie et al., Artificial vision adaption mimicked by an optoelectrical In2O3 transistor array. Nano Lett. 22(8), 3372–3379 (2022). https://doi.org/10.1021/acs.nanolett.2c00599
  111. X. Sha, Y. Cao, L. Meng, Z. Yao, Y. Gao et al., Near-infrared photonic artificial synapses based on organic heterojunction phototransistors. Appl. Phys. Lett. 120(15), 151103 (2022). https://doi.org/10.1063/5.0083925
  112. N. Sui, Y. Ji, M. Li, F. Zheng, S. Shao et al., Photoprogrammed multifunctional optoelectronic synaptic transistor arrays based on photosensitive polymer-sorted semiconducting single-walled carbon nanotubes for image recognition. Adv. Sci. 11(29), 2401794 (2024). https://doi.org/10.1002/advs.202401794
  113. Y.-B. Leng, Z. Lv, S. Huang, P. Xie, H.-X. Li et al., A near-infrared retinomorphic device with high dimensionality reservoir expression. Adv. Mater. 36(48), 2411225 (2024). https://doi.org/10.1002/adma.202411225
  114. X. Luo, C. Chen, Z. He, M. Wang, K. Pan et al., A bionic self-driven retinomorphic eye with ionogel photosynaptic retina. Nat. Commun. 15(1), 3086 (2024). https://doi.org/10.1038/s41467-024-47374-6
  115. C. Gallicchio, A. Micheli, Echo state property of deep reservoir computing networks. Cogn. Comput. 9(3), 337–350 (2017). https://doi.org/10.1007/s12559-017-9461-9
  116. L. Chen, X. Wang, C. Yang, Z. Chen, J. Zhang et al., Full-analog reservoir computing circuit based on memristor with a hybrid wide-deep architecture. IEEE Trans. Circuits Syst. I Regul. Pap. 71(2), 501–514 (2024). https://doi.org/10.1109/TCSI.2023.3334267
  117. L. Pedrelli, X. Hinaut, Hierarchical-task reservoir for online semantic analysis from continuous speech. IEEE Trans. Neural Netw. Learn. Syst. 33(6), 2654–2663 (2022). https://doi.org/10.1109/TNNLS.2021.3095140
  118. E.A. Antonelo, B. Schrauwen, On learning navigation behaviors for small mobile robots with reservoir computing architectures. IEEE Trans. Neural Netw. Learn. Syst. 26(4), 763–780 (2015). https://doi.org/10.1109/TNNLS.2014.2323247
  119. C. Gao, D. Liu, C. Xu, W. Xie, X. Zhang et al., Toward grouped-reservoir computing: organic neuromorphic vertical transistor with distributed reservoir states for efficient recognition and prediction. Nat. Commun. 15(1), 740 (2024). https://doi.org/10.1038/s41467-024-44942-8
  120. N. Kumar, M. Patel, T.T. Nguyen, P. Bhatnagar, J. Kim, All-oxide-based and metallic electrode-free artificial synapses for transparent neuromorphic computing. Mater. Today Chem. 23, 100681 (2022). https://doi.org/10.1016/j.mtchem.2021.100681
  121. C. Jiang, J. Liu, Y. Ni, S. Qu, L. Liu et al., Mammalian-brain-inspired neuromorphic motion-cognition nerve achieves cross-modal perceptual enhancement. Nat. Commun. 14(1), 1344 (2023). https://doi.org/10.1038/s41467-023-36935-w
  122. K. Yang, J.J. Yang, R. Huang, Y. Yang, Nonlinearity in memristors for neuromorphic dynamic systems. Small Sci. 2(1), 2100049 (2021). https://doi.org/10.1002/smsc.202100049
  123. J. Chen, Z. Zhou, B.J. Kim, Y. Zhou, Z. Wang et al., Optoelectronic graded neurons for bioinspired in-sensor motion perception. Nat. Nanotechnol. 18(8), 882–888 (2023). https://doi.org/10.1038/s41565-023-01379-2
  124. S. Liu, J. Zeng, Z. Wu, H. Hu, A. Xu et al., An ultrasmall organic synapse for neuromorphic computing. Nat. Commun. 14(1), 7655 (2023). https://doi.org/10.1038/s41467-023-43542-2
  125. T. Yan, Z. Li, F. Cao, J. Chen, L. Wu et al., An all-organic self-powered photodetector with ultraflexible dual-polarity output for biosignal detection. Adv. Mater. 34(30), 2201303 (2022). https://doi.org/10.1002/adma.202201303
  126. J. Lao, M. Yan, B. Tian, C. Jiang, C. Luo et al., Ultralow-power machine vision with self-powered sensor reservoir. Adv. Sci. 9(15), 2106092 (2022). https://doi.org/10.1002/advs.202106092
  127. L. Gu, S. Poddar, Y. Lin, Z. Long, D. Zhang et al., A biomimetic eye with a hemispherical perovskite nanowire array retina. Nature 581(7808), 278–282 (2020). https://doi.org/10.1038/s41586-020-2285-x
  128. T.Q. Trung, A. Bag, L.T.N. Huyen, M. Meeseepong, N.-E. Lee, Bio-inspired artificial retinas based on a fibrous inorganic–organic heterostructure for neuromorphic vision. Adv. Funct. Mater. 34(11), 2309378 (2024). https://doi.org/10.1002/adfm.202309378
  129. C. Gao, D. Liu, C. Xu, J. Bai, E. Li et al., Feedforward photoadaptive organic neuromorphic transistor with mixed-weight plasticity for augmenting perception. Adv. Funct. Mater. 34(18), 2313217 (2024). https://doi.org/10.1002/adfm.202313217
  130. J.S. Heo, J. Eom, Y.-H. Kim, S.K. Park, Recent progress of textile-based wearable electronics: a comprehensive review of materials, devices, and applications. Small 14(3), 1703034 (2018). https://doi.org/10.1002/smll.201703034
  131. W. Weng, J. Yang, Y. Zhang, Y. Li, S. Yang et al., A route toward smart system integration: from fiber design to device construction. Adv. Mater. 32(5), 1902301 (2020). https://doi.org/10.1002/adma.201902301
  132. Y. Zhang, H. Wang, H. Lu, S. Li, Y. Zhang, Electronic fibers and textiles: recent progress and perspective. iScience 24(7), 102716 (2021). https://doi.org/10.1016/j.isci.2021.102716
  133. S. Chen, Z. Lou, D. Chen, G. Shen, An artificial flexible visual memory system based on an UV-motivated memristor. Adv. Mater. 30(7), 1705400 (2018). https://doi.org/10.1002/adma.201705400
  134. S. Seo, S.-H. Jo, S. Kim, J. Shim, S. Oh et al., Artificial optic-neural synapse for colored and color-mixed pattern recognition. Nat. Commun. 9(1), 5106 (2018). https://doi.org/10.1038/s41467-018-07572-5
  135. H. Wang, Q. Zhao, Z. Ni, Q. Li, H. Liu et al., A ferroelectric/electrochemical modulated organic synapse for ultraflexible, artificial visual-perception system. Adv. Mater. 30(46), e1803961 (2018). https://doi.org/10.1002/adma.201803961
  136. S.M. Kwon, S.W. Cho, M. Kim, J.S. Heo, Y.-H. Kim et al., Environment-adaptable artificial visual perception behaviors using a light-adjustable optoelectronic neuromorphic device array. Adv. Mater. 31(52), 1906433 (2019). https://doi.org/10.1002/adma.201906433
  137. S.E. Ng, Y.B. Tay, T.Y.K. Ho, N.M. Ankit, Inorganic electrochromic transistors as environmentally adaptable photodetectors. Nano Energy 97, 107142 (2022). https://doi.org/10.1016/j.nanoen.2022.107142
  138. D. Xie, L. Wei, M. Xie, L. Jiang, J. Yang et al., Photoelectric visual adaptation based on 0D-CsPbBr3-quantum-dots/2D-MoS2 mixed-dimensional heterojunction transistor. Adv. Funct. Mater. 31(14), 2010655 (2021). https://doi.org/10.1002/adfm.202010655
  139. T.-J. Lee, K.-R. Yun, S.-K. Kim, J.-H. Kim, J. Jin et al., Realization of an artificial visual nervous system using an integrated optoelectronic device array. Adv. Mater. 33(51), 2105485 (2021). https://doi.org/10.1002/adma.202105485
  140. H. Shen, Z. He, W. Jin, L. Xiang, W. Zhao et al., Mimicking sensory adaptation with dielectric engineered organic transistors. Adv. Mater. 31(48), e1905018 (2019). https://doi.org/10.1002/adma.201905018
  141. V.A. Pieribone, O. Shupliakov, L. Brodin, S. Hilfiker-Rothenfluh, A.J. Czernik et al., Distinct pools of synaptic vesicles in neurotransmitter release. Nature 375(6531), 493–497 (1995). https://doi.org/10.1038/375493a0
  142. A. Panatier, D.T. Theodosis, J.-P. Mothet, B. Touquet, L. Pollegioni et al., Glia-derived D-serine controls NMDA receptor activity and synaptic memory. Cell 125(4), 775–784 (2006). https://doi.org/10.1016/j.cell.2006.02.051
  143. S.G. Sarwat, B. Kersting, T. Moraitis, V.P. Jonnalagadda, A. Sebastian, Phase-change memtransistive synapses for mixed-plasticity neural computations. Nat. Nanotechnol. 17(5), 507–513 (2022). https://doi.org/10.1038/s41565-022-01095-3
  144. Y. Kim, A. Chortos, W. Xu, Y. Liu, J.Y. Oh et al., A bioinspired flexible organic artificial afferent nerve. Science 360(6392), 998–1003 (2018). https://doi.org/10.1126/science.aao0098
  145. L. Tang, J. Shang, X. Jiang, Multilayered electronic transfer tattoo that can enable the crease amplification effect. Sci. Adv. 7(3), eabe3778 (2021). https://doi.org/10.1126/sciadv.abe3778
  146. M. Li, X. Ma, Y. Mu, G. Xie, H. Wan et al., A facile covalent strategy for ultrafast negative photoconductance hybrid graphene/porphyrin-based photodetector. Nanotechnology 34(8), 085201 (2022). https://doi.org/10.1088/1361-6528/aca598
  147. C. Biswas, F. Güneş, D.D. Loc, S.C. Lim, M.S. Jeong et al., Negative and positive persistent photoconductance in graphene. Nano Lett. 11(11), 4682–4687 (2011). https://doi.org/10.1021/nl202266h
  148. G. Zhou, B. Sun, X. Hu, L. Sun, Z. Zou et al., Negative photoconductance effect: an extension function of the TiOx-based memristor. Adv. Sci. 8(13), 2003765 (2021). https://doi.org/10.1002/advs.202003765
  149. E. Baek, T. Rim, J. Schütt, C.-K. Baek, K. Kim et al., Negative photoconductance in heavily doped Si nanowire field-effect transistors. Nano Lett. 17(11), 6727–6734 (2017). https://doi.org/10.1021/acs.nanolett.7b02788
  150. M.A. Haque, J.-L. Li, A.L. Abdelhady, M.I. Saidaminov, D. Baran et al., Transition from positive to negative photoconductance in doped hybrid perovskite semiconductors. Adv. Opt. Mater. 7(22), 1900865 (2019). https://doi.org/10.1002/adom.201900865
  151. D. Li, N. An, K. Tan, Y. Ren, H. Wang et al., Insulating electrets converted from organic semiconductor for high-performance transistors, memories, and artificial synapses. Adv. Funct. Mater. 33(45), 2305012 (2023). https://doi.org/10.1002/adfm.202305012
  152. Y. Ni, Y. Wang, W. Xu, Recent process of flexible transistor-structured memory. Small 17(9), 1905332 (2021). https://doi.org/10.1002/smll.201905332
  153. A. Sumanth, K.L. Ganapathi, M.S. Ramachandra Rao, T. Dixit, A review on realizing the modern optoelectronic applications through persistent photoconductivity. J. Phys. D Appl. Phys. 55(39), 393001 (2022). https://doi.org/10.1088/1361-6463/ac7f66
  154. Y. Kang, J. Jang, D. Cha, S. Lee, Synaptic weight evolution and charge trapping mechanisms in a synaptic pass-transistor operation with a direct potential output. IEEE Trans. Neural Netw. Learn. Syst. 32(10), 4728–4741 (2021). https://doi.org/10.1109/TNNLS.2020.3047963
  155. Z. Gao, R. Jiang, M. Deng, C. Zhao, Z. Hong et al., Tunable negative and positive photoconductance in van der Waals heterostructure for image preprocessing. Adv. Mater. 36(29), 2401585 (2024). https://doi.org/10.1002/adma.202401585
  156. Y.-C. Mi, C.-H. Yang, L.-C. Shih, J.-S. Chen, All-optical-controlled excitatory and inhibitory synaptic signaling through bipolar photoresponse of an oxide-based phototransistor. Adv. Opt. Mater. 11(14), 2300089 (2023). https://doi.org/10.1002/adom.202300089
  157. B. Xu, D. Guo, W. Dong, H. Gao, P. Zhu et al., Gap state-modulated van der Waals short-term memory with broad band negative photoconductance. Small 20(21), e2309626 (2024). https://doi.org/10.1002/smll.202309626
  158. Y. Yang, X. Peng, H.-S. Kim, T. Kim, S. Jeon et al., Hot carrier trapping induced negative photoconductance in InAs nanowires toward novel nonvolatile memory. Nano Lett. 15(9), 5875–5882 (2015). https://doi.org/10.1021/acs.nanolett.5b01962
  159. Y. Ishijima, T. Ishiguro, Negative photoconductance in a single crystal of C60. J. Phys. Soc. Jpn. 65(6), 1574–1577 (1996). https://doi.org/10.1143/jpsj.65.1574
  160. Y. Zhu, M. Juhl, G. Coletti, Z. Hameiri, On the transient negative photoconductance in n-type czochralski silicon. IEEE J. Photovolt. 8(2), 421–427 (2018). https://doi.org/10.1109/JPHOTOV.2017.2784679
  161. W. He, D. Wu, L. Kong, P. Yu, G. Yang, Giant negative photoresponse in van der Waals graphene/AgBiP2Se6/graphene trilayer heterostructures. Adv. Mater. 36(16), e2312541 (2024). https://doi.org/10.1002/adma.202312541
  162. R. Wang, J.-L. Wang, T. Liu, Z. He, H. Wang et al., Controllable inverse photoconductance in semiconducting nanowire films. Adv. Mater. 34(36), e2204698 (2022). https://doi.org/10.1002/adma.202204698
  163. M.A. Mangold, M. Calame, M. Mayor, A.W. Holleitner, Negative differential photoconductance in gold nanop arrays in the coulomb blockade regime. ACS Nano 6(5), 4181–4189 (2012). https://doi.org/10.1021/nn300673t
  164. Y. Wang, E. Liu, A. Gao, T. Cao, M. Long et al., Negative photoconductance in van der Waals heterostructure-based floating gate phototransistor. ACS Nano 12(9), 9513–9520 (2018). https://doi.org/10.1021/acsnano.8b04885
  165. J.W. John, V. Dhyani, Y.M. Georgiev, A.S. Gangnaik, S. Biswas et al., Ultrahigh negative infrared photoconductance in highly As-doped germanium nanowires induced by hot electron trapping. ACS Appl. Electron. Mater. 2(7), 1934–1942 (2020). https://doi.org/10.1021/acsaelm.0c00245
  166. D. Xue, W. Gong, C. Yan, Y. Zhang, J. Lu et al., Boosting bidirectional photoresponse with wavelength selectivity through ambipolar transport modulation. Adv. Funct. Mater. 34(38), 2402884 (2024). https://doi.org/10.1002/adfm.202402884
  167. Y. Xu, X. Xu, Y. Huang, Y. Tian, M. Cheng et al., Gate-tunable positive and negative photoconductance in near-infrared organic heterostructures for in-sensor computing. Adv. Mater. 36(30), e2402903 (2024). https://doi.org/10.1002/adma.202402903
  168. H. Wei, Z. Xu, Y. Ni, L. Yang, L. Sun et al., Mixed-dimensional nanop–nanowire channels for flexible optoelectronic artificial synapse with enhanced photoelectric response and asymmetric bidirectional plasticity. Nano Lett. 23(18), 8743–8752 (2023). https://doi.org/10.1021/acs.nanolett.3c02836
  169. P. Xie, X. Chen, Z. Zeng, W. Wang, Y. Meng et al., Artificial visual systems with tunable photoconductivity based on organic molecule-nanowire heterojunctions. Adv. Funct. Mater. 33(4), 2209091 (2023). https://doi.org/10.1002/adfm.202209091
  170. X. Zhu, Y. Yan, L. Sun, Y. Ren, Y. Zhang et al., Negative phototransistors with ultrahigh sensitivity and weak-light detection based on 1D/2D molecular crystal p–n heterojunctions and their application in light encoders. Adv. Mater. 34(23), 2270174 (2022). https://doi.org/10.1002/adma.202270174
  171. Y.-C. Chiang, C.-C. Hung, Y.-C. Lin, Y.-C. Chiu, T. Isono et al., High-performance nonvolatile organic photonic transistor memory devices using conjugated rod–coil materials as a floating gate. Adv. Mater. 32(36), 2002638 (2020). https://doi.org/10.1002/adma.202002638
  172. Z. Lv, M. Chen, F. Qian, V.A.L. Roy, W. Ye et al., Mimicking neuroplasticity in a hybrid biopolymer transistor by dual modes modulation. Adv. Funct. Mater. 29(31), 1902374 (2019). https://doi.org/10.1002/adfm.201902374
  173. D. Berco, D. Shenp Ang, Recent progress in synaptic devices paving the way toward an artificial cogni-retina for bionic and machine vision. Adv. Intell. Syst. 1(1), 1900012 (2019). https://doi.org/10.1002/aisy.201900012
  174. X. Shi, Y. Xu, W. Liu, C. Jin, S. Wang et al., Organic heterojunction phototransistors with bi-directional photoresponse for vision biomimetics. Adv. Funct. Mater. 34(32), 2401534 (2024). https://doi.org/10.1002/adfm.202401534
  175. X. Wu, Y. Chu, R. Liu, H.E. Katz, J. Huang, Pursuing polymer dielectric interfacial effect in organic transistors for photosensing performance optimization. Adv. Sci. 4(12), 1700442 (2017). https://doi.org/10.1002/advs.201700442
  176. Y. Ren, J.-Q. Yang, L. Zhou, J.-Y. Mao, S.-R. Zhang et al., Gate-tunable synaptic plasticity through controlled polarity of charge trapping in fullerene composites. Adv. Funct. Mater. 28(50), 1805599 (2018). https://doi.org/10.1002/adfm.201805599
  177. N. Qiao, P. Wei, Y. Xing, X. Qin, X. Wang et al., Rapid charge storage and release at etching-assist electret in organic transistors for memories, photodetectors, and artificial synapses. Adv. Mater. Interfaces 9(19), 2200713 (2022). https://doi.org/10.1002/admi.202200713
  178. P. Moon, Y. Won, O. Hak, L. Kwang, Enhancement of synaptic behavior in organic electrochemical transistors via the introduction of layer-by-layer grown metal-organic framework. Adv. Mater. Technol. 10(6), 2401316 (2025). https://doi.org/10.1002/admt.202401316
  179. H.R. Lee, D. Lee, J.H. Oh, A hippocampus-inspired dual-gated organic artificial synapse for simultaneous sensing of a neurotransmitter and light. Adv. Mater. 33(17), 2100119 (2021). https://doi.org/10.1002/adma.202100119
  180. J. Li, Z. Feng, Y. Qian, W. Huang, W. Li et al., Organic semiconductor heterojunction-based photonic synaptic transistor with temperature stability and adaptive learning ability for neuromorphic computing systems. ACS Appl. Electron. Mater. 7(13), 6149–6157 (2025). https://doi.org/10.1021/acsaelm.5c00882
  181. Y. Liang, H. Li, H. Tang, C. Zhang, D. Men et al., Bioinspired electrolyte-gated organic synaptic transistors: from fundamental requirements to applications. Nano-Micro Lett. 17(1), 198 (2025). https://doi.org/10.1007/s40820-025-01708-1
  182. S. Zhong, L. Su, M. Xu, D. Loke, B. Yu et al., Recent advances in artificial sensory neurons: biological fundamentals, devices, applications, and challenges. Nano-Micro Lett. 17(1), 61 (2024). https://doi.org/10.1007/s40820-024-01550-x
  183. Y. Zhu, T. Nyberg, L. Nyholm, D. Primetzhofer, X. Shi et al., Wafer-scale Ag2S-based memristive crossbar arrays with ultra-low switching-energies reaching biological synapses. Nano-Micro Lett. 17(1), 69 (2024). https://doi.org/10.1007/s40820-024-01559-2
  184. J. Xia, C. Gao, C. Peng, Y. Liu, P.-A. Chen et al., Multidimensional deep ultraviolet (DUV) synapses based on organic/perovskite semiconductor heterojunction transistors for antispoofing facial recognition systems. Nano Lett. 24(22), 6673–6682 (2024). https://doi.org/10.1021/acs.nanolett.4c01356
  185. S. Kang, M. Kim, C. Yoo, B.M. Lim, B.C. Jang et al., Photogating-based organic synapse electronics modulated by dielectric. Org. Electron. 129, 107056 (2024). https://doi.org/10.1016/j.orgel.2024.107056
  186. J. Chen, X.-C. Zhao, Y.-Q. Zhu, Z.-H. Wang, Z. Zhang et al., Polarized tunneling transistor for ultralow-energy-consumption artificial synapse toward neuromorphic computing. ACS Nano 18(1), 581–591 (2024). https://doi.org/10.1021/acsnano.3c08632
  187. L. Sun, S. Qu, Y. Du, L. Yang, Y. Li et al., Bio-inspired vision and neuromorphic image processing using printable metal oxide photonic synapses. ACS Photonics 10(1), 242–252 (2023). https://doi.org/10.1021/acsphotonics.2c01583
  188. S.T. Keene, C. Lubrano, S. Kazemzadeh, A. Melianas, Y. Tuchman et al., A biohybrid synapse with neurotransmitter-mediated plasticity. Nat. Mater. 19(9), 969–973 (2020). https://doi.org/10.1038/s41563-020-0703-y
  189. F. Xu, C. Zhang, X. Zhao, H. Yu, G. Zhao et al., Intrinsically stretchable photonic synaptic transistors for retina-like visual image systems. J. Mater. Chem. C 10(29), 10586–10594 (2022). https://doi.org/10.1039/d2tc01775j
  190. A. Jones, A. Rush, C. Merkel, E. Herrmann, A.P. Jacob et al., A neuromorphic SLAM architecture using gated-memristive synapses. Neurocomputing 381, 89–104 (2020). https://doi.org/10.1016/j.neucom.2019.09.098
  191. M.M. Islam, D. Dev, A. Krishnaprasad, L. Tetard, T. Roy, Optoelectronic synapse using monolayer MoS2 field effect transistors. Sci. Rep. 10(1), 21870 (2020). https://doi.org/10.1038/s41598-020-78767-4
  192. J.-H. Choi, H.-M. An, H.-L. Park, Polarized light-sensitive optoelectronic synapses for expanding artificial vision systems. Flex. Print. Electron. 10(1), 013501 (2025). https://doi.org/10.1088/2058-8585/adb595
  193. H. Wurzer, C. Hoffmann, A. Al Absi, C. Thomas, Actin cytoskeleton straddling the immunological synapse between cytotoxic lymphocytes and cancer cells. Cells 8(5), 463 (2019). https://doi.org/10.3390/cells8050463
  194. C. Zhang, Y. Li, F. Yu, G. Wang, K. Wang et al., Visual growth of nano-HOFs for low‐power memristive spiking neuromorphic system. Nano Energy 109, 108274 (2023). https://doi.org/10.1016/j.nanoen.2023.108274
  195. M. Dong, Y. Zhang, J. Zhu, X. Zhu, J. Zhao et al., All-in-one 2D molecular crystal optoelectronic synapse for polarization-sensitive neuromorphic visual system. Adv. Mater. 36(40), 2409550 (2024). https://doi.org/10.1002/adma.202409550
  196. I.-K. Hwang, M.G. Lee, J.B. Jeon, S.H. Nam, D. Lee et al., Visible-light chiral photonic synapses based on hybrid organic-inorganic 2D perovskites. Adv. Electron. Mater. 11(3), 2400525 (2025). https://doi.org/10.1002/aelm.202400525
  197. P. Xie, Y. Xu, J. Wang, D. Li, Y. Zhang et al., Birdlike broadband neuromorphic visual sensor arrays for fusion imaging. Nat. Commun. 15(1), 8298 (2024). https://doi.org/10.1038/s41467-024-52563-4
  198. D. Li, Y. Chen, H. Ren, Y. Tang, S. Zhang et al., An active-matrix synaptic phototransistor array for in-sensor spectral processing. Adv. Sci. 11(39), 2406401 (2024). https://doi.org/10.1002/advs.202406401
  199. X. Liu, S. Dai, W. Zhao, J. Zhang, Z. Guo et al., All-photolithography fabrication of ion-gated flexible organic transistor array for multimode neuromorphic computing. Adv. Mater. 36(21), e2312473 (2024). https://doi.org/10.1002/adma.202312473
  200. S. Zhang, R. Chen, D. Kong, Y. Chen, W. Liu et al., Photovoltaic nanocells for high-performance large-scale-integrated organic phototransistors. Nat. Nanotechnol. 19(9), 1323–1332 (2024). https://doi.org/10.1038/s41565-024-01707-0
  201. H. Lee, J.H. Hwang, S.H. Song, H. Han, S.-J. Han et al., Chiroptical synaptic heterojunction phototransistors based on self-assembled nanohelix of π-conjugated molecules for direct noise-reduced detection of circularly polarized light. Adv. Sci. 10(27), 2304039 (2023). https://doi.org/10.1002/advs.202304039
  202. S.D. Namgung, R.M. Kim, Y.-C. Lim, J.W. Lee, N.H. Cho et al., Circularly polarized light-sensitive, hot electron transistor with chiral plasmonic nanops. Nat. Commun. 13(1), 5081 (2022). https://doi.org/10.1038/s41467-022-32721-2
  203. J.H. Kim, M. Stolte, F. Würthner, Wavelength and polarization sensitive synaptic phototransistor based on organic n-type semiconductor/supramolecular J-aggregate heterostructure. ACS Nano 16(11), 19523–19532 (2022). https://doi.org/10.1021/acsnano.2c09747
  204. C. Zhang, C. Xu, C. Chen, J. Cheng, H. Zhang et al., Optically programmable circularly polarized photodetector. ACS Nano 16(8), 12452–12461 (2022). https://doi.org/10.1021/acsnano.2c03746
  205. G. Vats, B. Hodges, A.J. Ferguson, L.M. Wheeler, J.L. Blackburn, Optical memory, switching, and neuromorphic functionality in metal halide perovskite materials and devices. Adv. Mater. 35(37), 2205459 (2023). https://doi.org/10.1002/adma.202205459
  206. J. Choi, J.S. Han, K. Hong, S.Y. Kim, H.W. Jang, Organic-inorganic hybrid halide perovskites for memories, transistors, and artificial synapses. Adv. Mater. 30(42), e1704002 (2018). https://doi.org/10.1002/adma.201704002
  207. D. Hao, Z. Yang, J. Huang, F. Shan, Recent developments of optoelectronic synaptic devices based on metal halide perovskites. Adv. Funct. Mater. 33(8), 2211467 (2023). https://doi.org/10.1002/adfm.202211467
  208. O. Yildiz, Z. Wang, M. Borkowski, G. Fytas, P.W.M. Blom et al., Optimized charge transport in molecular semiconductors by control of fluid dynamics and crystallization in Meniscus-guided coating. Adv. Funct. Mater. 32(2), 2107976 (2022). https://doi.org/10.1002/adfm.202107976
  209. H. Ma, H. Fang, X. Xie, Y. Liu, H. Tian et al., Optoelectronic synapses based on MXene/violet phosphorus van der Waals heterojunctions for visual-olfactory crossmodal perception. Nano-Micro Lett. 16(1), 104 (2024). https://doi.org/10.1007/s40820-024-01330-7
  210. C. Wang, X. Ren, C. Xu, B. Fu, R. Wang et al., N-type 2D organic single crystals for high-performance organic field-effect transistors and near-infrared phototransistors. Adv. Mater. 30(16), 1706260 (2018). https://doi.org/10.1002/adma.201706260
  211. F. Yang, S. Cheng, X. Zhang, X. Ren, R. Li et al., 2D organic materials for optoelectronic applications. Adv. Mater. 30(2), 1702415 (2018). https://doi.org/10.1002/adma.201702415
  212. S. Mafrica, S. Godiot, M. Menouni, M. Boyron, F. Expert et al., A bio-inspired analog silicon retina with Michaelis-Menten auto-adaptive pixels sensitive to small and large changes in light. Opt. Express 23(5), 5614–5635 (2015). https://doi.org/10.1364/OE.23.005614
  213. Z. He, H. Shen, D. Ye, L. Xiang, W. Zhao et al., An organic transistor with light intensity-dependent active photoadaptation. Nat. Electron. 4(7), 522–529 (2021). https://doi.org/10.1038/s41928-021-00615-8
  214. J. Marshall, T.W. Cronin, S. Kleinlogel, Stomatopod eye structure and function: a review. Arthropod Struct. Dev. 36(4), 420–448 (2007). https://doi.org/10.1016/j.asd.2007.01.006
  215. M.M. Islam, A. Krishnaprasad, D. Dev, R. Martinez-Martinez, V. Okonkwo et al., Multiwavelength optoelectronic synapse with 2D materials for mixed-color pattern recognition. ACS Nano 16(7), 10188–10198 (2022). https://doi.org/10.1021/acsnano.2c01035
  216. Y. Yang, R.C. da Costa, M.J. Fuchter, A.J. Campbell, Circularly polarized light detection by a chiral organic semiconductor transistor. Nat. Photonics 7(8), 634–638 (2013). https://doi.org/10.1038/nphoton.2013.176
  217. L. Zhang, I. Song, J. Ahn, M. Han, M. Linares et al., π-extended perylene diimide double-heterohelicenes as ambipolar organic semiconductors for broadband circularly polarized light detection. Nat. Commun. 12(1), 142 (2021). https://doi.org/10.1038/s41467-020-20390-y
  218. H. Han, Y.J. Lee, J. Kyhm, J.S. Jeong, J.-H. Han et al., High-performance circularly polarized light-sensing near-infrared organic phototransistors for optoelectronic cryptographic primitives. Adv. Funct. Mater. 30(52), 2006236 (2020). https://doi.org/10.1002/adfm.202006236
  219. W. Wen, G. Liu, X. Wei, H. Huang, C. Wang et al., Biomimetic nanocluster photoreceptors for adaptative circular polarization vision. Nat. Commun. 15(1), 2397 (2024). https://doi.org/10.1038/s41467-024-46646-5
  220. Y. Yang, C. Pan, Y. Li, X. Yangdong, P. Wang et al., In-sensor dynamic computing for intelligent machine vision. Nat. Electron. 7(3), 225–233 (2024). https://doi.org/10.1038/s41928-024-01124-0
  221. T. Qiu, Q. An, J. Wang, J. Wang, C.-W. Qiu et al., Vision-driven metasurfaces for perception enhancement. Nat. Commun. 15(1), 1631 (2024). https://doi.org/10.1038/s41467-024-45296-x
  222. G. Wu, J. Zhang, X. Wan, Y. Yang, S. Jiang, Chitosan-based biopolysaccharide proton conductors for synaptic transistors on paper substrates. J. Mater. Chem. C 2(31), 6249–6255 (2014). https://doi.org/10.1039/c4tc00652f
  223. G. Wu, C. Wan, J. Zhou, L. Zhu, Q. Wan, Low-voltage protonic/electronic hybrid indium zinc oxide synaptic transistors on paper substrates. Nanotechnology 25(9), 094001 (2014). https://doi.org/10.1088/0957-4484/25/9/094001
  224. Y. Jeon, G. Lee, Y.J. Kim, B.C. Jang, H. Yoo, Dual synapses and security devices from ternary C60-pentacene-TiO2-x nanorods heterostructures. Adv. Funct. Mater. 34(48), 2409578 (2024). https://doi.org/10.1002/adfm.202409578
  225. Y. Zhang, H. Chen, W. Sun, Y. Hou, Y. Cai et al., All-photonic synapses for biomimetic ocular system. Adv. Funct. Mater. 34(49), 2409419 (2024). https://doi.org/10.1002/adfm.202409419
  226. J. Gong, H. Wei, J. Liu, L. Sun, Z. Xu et al., An artificial visual nerve for mimicking pupil reflex. Matter 5(5), 1578–1589 (2022). https://doi.org/10.1016/j.matt.2022.02.020
  227. W. Li, S. Wu, H. Zhang, X. Zhang, J. Zhuang et al., Enhanced biological photosynthetic efficiency using light-harvesting engineering with dual-emissive carbon dots. Adv. Funct. Mater. 28(44), 1804004 (2018). https://doi.org/10.1002/adfm.201804004
  228. F. Liao, Z. Zhou, B.J. Kim, J. Chen, J. Wang et al., Bioinspired in-sensor visual adaptation for accurate perception. Nat. Electron. 5(2), 84–91 (2022). https://doi.org/10.1038/s41928-022-00713-1
  229. R.D. van Jansen- Vuuren, A. Armin, A.K. Pandey, P.L. Burn, P. Meredith, Organic photodiodes: the future of full color detection and image sensing. Adv. Mater. 28(24), 4766–4802 (2016). https://doi.org/10.1002/adma.201505405
  230. A. Reisman, Device, circuit, and technology scaling to micron and submicron dimensions. Proc. IEEE 71(5), 550–565 (1983). https://doi.org/10.1109/PROC.1983.12638
  231. Y.-Q. Zheng, Y. Liu, D. Zhong, S. Nikzad, S. Liu et al., Monolithic optical microlithography of high-density elastic circuits. Science 373(6550), 88–94 (2021). https://doi.org/10.1126/science.abh3551
  232. Y. Zheng, Z. Yu, S. Zhang, X. Kong, W. Michaels et al., A molecular design approach towards elastic and multifunctional polymer electronics. Nat. Commun. 12(1), 5701 (2021). https://doi.org/10.1038/s41467-021-25719-9
  233. IEEE transactions on circuits and systems for video technology publication information. IEEE Trans. Circuits Syst. Video Technol. 35(3), C2–C2 (2025). https://doi.org/10.1109/TCSVT.2025.3541359
  234. E.J. Fuller, S.T. Keene, A. Melianas, Z. Wang, S. Agarwal et al., Parallel programming of an ionic floating-gate memory array for scalable neuromorphic computing. Science 364(6440), 570–574 (2019). https://doi.org/10.1126/science.aaw5581
  235. S.H. Kim, G.W. Baek, J. Yoon, S. Seo, J. Park et al., A bioinspired stretchable sensory-neuromorphic system. Adv. Mater. 33(44), e2104690 (2021). https://doi.org/10.1002/adma.202104690
  236. Y. Wang, Y. Gong, S. Huang, X. Xing, Z. Lv et al., Memristor-based biomimetic compound eye for real-time collision detection. Nat. Commun. 12(1), 5979 (2021). https://doi.org/10.1038/s41467-021-26314-8
  237. C. Du, F. Cai, M.A. Zidan, W. Ma, S.H. Lee et al., Reservoir computing using dynamic memristors for temporal information processing. Nat. Commun. 8, 2204 (2017). https://doi.org/10.1038/s41467-017-02337-y
  238. Y. Choi, S. Oh, C. Qian, J.-H. Park, J.H. Cho, Vertical organic synapse expandable to 3D crossbar array. Nat. Commun. 11(1), 4595 (2020). https://doi.org/10.1038/s41467-020-17850-w
  239. Z. Wang, S. Joshi, S.E. Savel’ev, H. Jiang, R. Midya et al., Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing. Nat. Mater. 16(1), 101–108 (2017). https://doi.org/10.1038/nmat4756
  240. H. Chen, L. Lv, Y. Wei, T. Liu, S. Wang et al., Self-powered flexible artificial synapse for near-infrared light detection. Cell Rep. Phys. Sci. 2(7), 100507 (2021). https://doi.org/10.1016/j.xcrp.2021.100507
  241. G. Liu, W. Wen, Z. Zhao, X. Huang, Y. Li et al., Bionic tactile-gustatory receptor for object identification based on all-polymer electrochemical transistor. Adv. Mater. 35(24), 2300242 (2023). https://doi.org/10.1002/adma.202300242
  242. J. Shi, J. Jie, W. Deng, G. Luo, X. Fang et al., A fully solution-printed photosynaptic transistor array with ultralow energy consumption for artificial-vision neural networks. Adv. Mater. 34(18), 2200380 (2022). https://doi.org/10.1002/adma.202200380
  243. H. Jo, J. Jang, H.J. Park, H. Lee, S.J. An et al., Physical reservoir computing using tellurium-based gate-tunable artificial photonic synapses. ACS Nano 18(44), 30761–30773 (2024). https://doi.org/10.1021/acsnano.4c10489
  244. A. Moazzeni, H. Riyahi Madvar, S. Hamedi, Z. Kordrostami, Fabrication of graphene oxide-based resistive switching memory by the spray pyrolysis technique for neuromorphic computing. ACS Appl. Nano Mater. 6(3), 2236–2248 (2023). https://doi.org/10.1021/acsanm.2c05497
  245. Z. Chen, J. He, Y. Zheng, T. Song, Z. Deng, An optimized feedforward decoupling PD register control method of roll-to-roll web printing systems. IEEE Trans. Autom. Sci. Eng. 13(1), 274–283 (2016). https://doi.org/10.1109/TASE.2015.2489687
  246. B. Grant, Y. Bandera, S.H. Foulger, J. Vilčáková, P. Sáha et al., Boolean and elementary algebra with a roll-to-roll printed electrochemical memristor. Adv. Mater. Technol. 7(5), 2101108 (2022). https://doi.org/10.1002/admt.202101108
  247. W. Choi, J.S. Yoon, W.W. Lee, G.H. Hong, H. Kim et al., DPP-DTT nanowire phototransistors for optoelectronic synapses in EMG and ECG signal classification. Small (2025). https://doi.org/10.1002/smll.202506440
  248. W. Xu, S.-Y. Min, H. Hwang, T.-W. Lee, Organic core-sheath nanowire artificial synapses with femtojoule energy consumption. Sci. Adv. 2(6), e1501326 (2016). https://doi.org/10.1126/sciadv.1501326
  249. X. Zhang, X. Yu, J. Chen, Solution-processed organic nanostructure arrays: from nanofabrication to applications. Surf. Interfaces 72, 106981 (2025). https://doi.org/10.1016/j.surfin.2025.106981
  250. S.-X. Li, G.-Y. Huang, H. Xia, T. Fu, X.-J. Wang et al., Nanoimprint crystalithography for organic semiconductors. Nat. Commun. 16(1), 3636 (2025). https://doi.org/10.1038/s41467-025-58934-9
  251. X. Liu, D. Wang, W. Chen, Y. Kang, S. Fang et al., Optoelectronic synapses with chemical-electric behaviors in gallium nitride semiconductors for biorealistic neuromorphic functionality. Nat. Commun. 15, 7671 (2024). https://doi.org/10.1038/s41467-024-51194-z
  252. L. Lu, X. Liu, P. Gu, Z. Hu, X. Liang et al., Stretchable all-gel organic electrochemical transistors. Nat. Commun. 16(1), 3831 (2025). https://doi.org/10.1038/s41467-025-59240-0
  253. S. Woo, D. Moon, Y. Won, C. Kyung, J. Yoo et al., A pattern recognition artificial olfactory system based on human olfactory receptors and organic synaptic devices. Sci. Adv. 10(21), eadl2882 (2024). https://doi.org/10.1126/sciadv.adl2882
  254. X. Wu, S. Chen, L. Jiang, X. Wang, L. Qiu et al., Highly sensitive, low-energy-consumption biomimetic olfactory synaptic transistors based on the aggregation of the semiconductor films. ACS Sens. 9(5), 2673–2683 (2024). https://doi.org/10.1021/acssensors.4c00616
  255. P. Li, H.P. Anwar Ali, W. Cheng, J. Yang, B.C.K. Tee, Bioinspired prosthetic interfaces. Adv. Mater. Technol. 5(3), 1900856 (2020). https://doi.org/10.1002/admt.201900856
  256. K. Liang, R. Wang, H. Ren, D. Li, Y. Tang et al., Printable coffee-ring structures for highly uniform all-oxide optoelectronic synaptic transistors. Adv. Opt. Mater. 10(24), 2201754 (2022). https://doi.org/10.1002/adom.202201754
  257. L. Yu, Y. Li, Y. Lv, B. Gu, J. Cai et al., Treadmill exercise facilitates synaptic plasticity in APP/PS1 mice by regulating hippocampal AMPAR activity. Cells 13(19), 1608 (2024). https://doi.org/10.3390/cells13191608
  258. M. Deodato, D. Melcher, Continuous temporal integration in the human visual system. J. Vis. 24(13), 5 (2024). https://doi.org/10.1167/jov.24.13.5
  259. A. Bartels, S. Zeki, The theory of multistage integration in the visual brain. Proc. R. Soc. Lond. B 265(1412), 2327–2332 (1998). https://doi.org/10.1098/rspb.1998.0579
  260. A. Pérez-Bellido, M.O. Ernst, S. Soto-Faraco, J. López-Moliner, Visual limitations shape audio-visual integration. J. Vis. 15(14), 5 (2015). https://doi.org/10.1167/15.14.5
  261. Z. Zhao, A. Abdelsamie, R. Guo, S. Shi, J. Zhao et al., Flexible artificial synapse based on single-crystalline BiFeO3 thin film. Nano Res. 15(3), 2682–2688 (2022). https://doi.org/10.1007/s12274-021-3782-4
  262. X. Yan, Z. Zhou, J. Zhao, Q. Liu, H. Wang et al., Flexible memristors as electronic synapses for neuro-inspired computation based on Scotch tape-exfoliated Mica substrates. Nano Res. 11(3), 1183–1192 (2018). https://doi.org/10.1007/s12274-017-1781-2
  263. Y. Lin, T. Zeng, H. Xu, Z. Wang, X. Zhao et al., Transferable and flexible artificial memristive synapse based on WOx Schottky junction on arbitrary substrates. Adv. Electron. Mater. 4(12), 1800373 (2018). https://doi.org/10.1002/aelm.201800373
  264. X. Huang, K. Zhang, B. Peng, G. Wang, M. Muhler et al., Ceria-based materials for thermocatalytic and photocatalytic organic synthesis. ACS Catal. 11(15), 9618–9678 (2021). https://doi.org/10.1021/acscatal.1c02443
  265. L. Cui, J. Wu, H. Ju, Electrochemical sensing of heavy metal ions with inorganic, organic and bio-materials. Biosens. Bioelectron. 63, 276–286 (2015). https://doi.org/10.1016/j.bios.2014.07.052
  266. D. Liu, K. Lu, C. Poon, W. Lin, Metal–organic frameworks as sensory materials and imaging agents. Inorg. Chem. 53(4), 1916–1924 (2014). https://doi.org/10.1021/ic402194c
  267. R. Xue, Y.-S. Liu, S.-L. Huang, G.-Y. Yang, Recent progress of covalent organic frameworks applied in electrochemical sensors. ACS Sens. 8(6), 2124–2148 (2023). https://doi.org/10.1021/acssensors.3c00269
  268. B. Salonikidou, A. Mehonic, Y. Takeda, S. Tokito, J. England et al., Inkjet-printed Ag/a-TiO2/Ag neuromorphic nanodevice based on functionalized ink. Adv. Eng. Mater. 24(11), 2200439 (2022). https://doi.org/10.1002/adem.202200439
  269. G. Zhu, X. Chen, J. Ma, G. Dai, Z. Liu, Inkjet-printed niobium tungsten oxide thin-film memristors for neuromorphic computing. Mater. Today Commun. 44, 112088 (2025). https://doi.org/10.1016/j.mtcomm.2025.112088
  270. H. Hu, A. Scholz, C. Dolle, A. Zintler, A. Quintilla et al., Inkjet-printed tungsten oxide memristor displaying non-volatile memory and neuromorphic properties. Adv. Funct. Mater. 34(20), 2302290 (2024). https://doi.org/10.1002/adfm.202302290
  271. C. Bao, S.K. Seol, W.S. Kim, A 3D integrated neuromorphic chemical sensing system. Sens. Actuat. B Chem. 332, 129527 (2021). https://doi.org/10.1016/j.snb.2021.129527
  272. Q. Cao, M. Shin, N.V. Lavrik, B.J. Venton, 3D-printed carbon nanoelectrodes for in vivo neurotransmitter sensing. Nano Lett. 20(9), 6831–6836 (2020). https://doi.org/10.1021/acs.nanolett.0c02844
  273. X. Li, R. Bi, X. Ou, S. Han, Y. Sheng et al., 3D-printed intrinsically stretchable organic electrochemical synaptic transistor array. ACS Appl. Mater. Interfaces 15(35), 41656–41665 (2023). https://doi.org/10.1021/acsami.3c07169
  274. Q. Chen, R. Yang, D. Hu, Z. Ye, J. Lu, Artificial neurosynaptic device based on amorphous oxides for artificial neural network constructing. J. Mater. Chem. C 12(25), 9165–9174 (2024). https://doi.org/10.1039/D4TC01244E
  275. D.-H. Kim, S.-M. Yoon, Improvement in energy consumption and operational stability of electrolyte-gated synapse transistors using atomic-layer-deposited HfO2 thin films. Mater. Sci. Semicond. Process. 153, 107182 (2023). https://doi.org/10.1016/j.mssp.2022.107182
  276. C. Liu, L. Zhu, J.-K. Weng, Y.-C. Li, Z. Chen et al., Ultraflexible and energy-efficient artificial synapses based on molecular/atomic layer deposited organic–inorganic hybrid thin films. Adv. Electron. Mater. 9(2), 2200821 (2023). https://doi.org/10.1002/aelm.202200821
  277. K.-X. Guo, H.-Y. Yu, H. Han, H.-H. Wei, J.-D. Gong et al., Artificial synapse based on MoO3 nanosheets prepared by hydrothermal synthesis. Acta Phys. Sin. 69(23), 238501 (2020). https://doi.org/10.7498/aps.69.20200928
  278. Z. Guo, J. Liu, X. Han, F. Ma, D. Rong et al., High-performance artificial synapse based on CVD-grown WSe2 flakes with intrinsic defects. ACS Appl. Mater. Interfaces 15(15), 19152–19162 (2023). https://doi.org/10.1021/acsami.3c00417
  279. D.-P. Yang, R.-H. Li, X.-G. Tang, D.-L. Li, Q.-J. Sun, Photoelectric dual mode sensing system based on one-step fabricated heterojunction artificial synapses device. Mater. Sci. Eng. R. Rep. 165, 101021 (2025). https://doi.org/10.1016/j.mser.2025.101021
  280. Y.H. Kim, G.H. Kim, A.Y. Kim, N.S. Baek, J.I. Jeong et al., Optimisation of bi-layer resist overhang structure formation and SiO2 sputter-deposition process for fabrication of gold multi-electrode array. RSC Adv. 5(9), 6675–6681 (2015). https://doi.org/10.1039/c4ra11746h
  281. W. Luo, Z. Yang, J. Zheng, Z. Cai, X. Li et al., Small molecule hydrogels loading small molecule drugs from Chinese medicine for the enhanced treatment of traumatic brain injury. ACS Nano 18(42), 28894–28909 (2024). https://doi.org/10.1021/acsnano.4c09097
  282. J. Li, S.J. Bandekar, D. Araç, The structure of fly Teneurin-m reveals an asymmetric self-assembly that allows expansion into zippers. EMBO Rep. 24(6), e56728 (2023). https://doi.org/10.15252/embr.202256728
  283. Y. Shen, Z. Jiang, H. Huang, S. Wang, S. Wu et al., Advances in textile-based triboelectric sensors for physiological signal monitoring. Adv. Funct. Mater. 35(37), 2426081 (2025). https://doi.org/10.1002/adfm.202426081
  284. J. Zeng, J. Zhao, C. Li, Y. Qi, G. Liu et al., Triboelectric nanogenerators as active tactile stimulators for multifunctional sensing and artificial synapses. Sensors 22(3), 975 (2022). https://doi.org/10.3390/s22030975
  285. W.-S. Khwa, T.-H. Wen, H.-H. Hsu, W.-H. Huang, Y.-C. Chang et al., A mixed-precision memristor and SRAM compute-in-memory AI processor. Nature 639(8055), 617–623 (2025). https://doi.org/10.1038/s41586-025-08639-2
  286. A. Renner, L. Supic, A. Danielescu, G. Indiveri, B.A. Olshausen et al., Neuromorphic visual scene understanding with resonator networks. Nat. Mach. Intell. 6(6), 641–652 (2024). https://doi.org/10.1038/s42256-024-00848-0
  287. C.-Y. Wang, S.-J. Liang, S. Wang, P. Wang, Z.-A. Li et al., Gate-tunable van der Waals heterostructure for reconfigurable neural network vision sensor. Sci. Adv. 6(26), eaba6173 (2020). https://doi.org/10.1126/sciadv.aba6173
  288. A. Natarajan, A. Sudha, D. Dean, V.M. Vijayan, 3D surface-patterned hyaluronic acid hydrogels: customizable platforms for enhanced chondrogenic differentiation and organized production of a specific hyaline cartilage extracellular matrix. ACS Appl. Mater. Interfaces 17(38), 53343–53364 (2025). https://doi.org/10.1021/acsami.5c16374
  289. Y. Yang, Y. Liu, R. Yin, Fiber-shaped fluidic pumps for wearable applications. Adv. Fiber Mater. 5(5), 1552–1554 (2023). https://doi.org/10.1007/s42765-023-00319-y
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