The DOI matches its Crossref record; 45 of the 45 references it cites were found in a registry or an index.
Light‐Stimulated Synaptic Transistors Fabricated by a Facile Solution Process Based on Inorganic Perovskite Quantum Dots and Organic Semiconductors
Abstract
Implementation of artificial intelligent systems with light‐stimulated synaptic emulators may enhance computational speed by providing devices with high bandwidth, low power computation requirements, and low crosstalk. One of the key challenges is to develop light‐stimulated devices that can response to light signals in a neuron‐/synapse‐like fashion. A simple and effective solution process to fabricate light‐stimulated synaptic transistors (LSSTs) based on inorganic halide perovskite quantum dots (IHP QDs) and organic semiconductors (OSCs) is reported. Blending IHP QDs and OSCs not only improves the charge separation efficiency of the photoexcited charges, but also induces delayed decay of the photocurrent in the IHP QDs/OSCs hybrid film. The enhanced charge separation efficiency results in high photoresponsivity, while the induced delayed decay of the photocurrent is critical to achieving light‐stimulating devices with a memory effect, which are important for achieving high synaptic performance. The LSSTs can respond to light signals in a highly neuron‐/synapse‐like fashion. Both short‐term and long‐term synaptic behaviors have been realized, which may lay the foundation for the future implementation of artificial intelligent systems that are enabled by light signals. More significantly, LSSTs are fabricated by a facile solution process which can be easily applied to large‐scale samples.
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Protesescu, L., Yakunin, S., Bodnarchuk, M. I., Krieg, F., Caputo, R., Hendon, C. H., Yang, R. X., Walsh, A., & Kovalenko, M. V. (2015) · Nano Letters · doi:10.1021/nl5048779 · Cited by 9,209
Human Memory: A Proposed System and its Control Processes
Atkinson, R. C., & Shiffrin, R. M. (1968) · Psychology of Learning and Motivation · doi:10.1016/s0079-7421(08)60422-3 · Cited by 7,216
Short-Term Synaptic Plasticity
Zucker, R. S., & Regehr, W. G. (2002) · Annual Review of Physiology · doi:10.1146/annurev.physiol.64.092501.114547 · Cited by 5,068
A million spiking-neuron integrated circuit with a scalable communication network and interface
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. (2014) · Science · doi:10.1126/science.1254642 · Cited by 4,147
Quantum dot–induced phase stabilization of α-CsPbI 3 perovskite for high-efficiency photovoltaics
Swarnkar, A., Marshall, A. R., Sanehira, E. M., Chernomordik, B. D., Moore, D. T., Christians, J. A., Chakrabarti, T., & Luther, J. M. (2016) · Science · doi:10.1126/science.aag2700 · Cited by 2,794
The future of electronics based on memristive systems
Zidan, M. A., Strachan, J. P., & Lu, W. D. (2018) · Nature Electronics · doi:10.1038/s41928-017-0006-8 · Cited by 2,138
Short-term plasticity and long-term potentiation mimicked in single inorganic synapses
Ohno, T., Hasegawa, T., Tsuruoka, T., Terabe, K., Gimzewski, J. K., & Aono, M. (2011) · Nature Materials · doi:10.1038/nmat3054 · Cited by 1,793
Abbott, L. F., & Regehr, W. G. (2004) · Nature · doi:10.1038/nature03010 · Cited by 1,684
A bioinspired flexible organic artificial afferent nerve
Kim, Y., Chortos, A., Xu, W., Liu, Y., Oh, J. Y., Son, D., Kang, J., Foudeh, A. M., Zhu, C., Lee, Y., et al. (2018) · Science · doi:10.1126/science.aao0098 · Cited by 1,466
Neuromorphic computing with nanoscale spintronic oscillators
Torrejon, J., Riou, M., Araujo, F. A., Tsunegi, S., Khalsa, G., Querlioz, D., Bortolotti, P., Cros, V., Yakushiji, K., Fukushima, A., et al. (2017) · Nature · doi:10.1038/nature23011 · Cited by 1,374
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A comprehensive review on emerging artificial neuromorphic devices
Zhu, J., Zhang, T., Yang, Y., & Huang, R. (2020) · Applied Physics Reviews · doi:10.1063/1.5118217 · Cited by 758
Hou, Y.-X., Li, Y., Zhang, Z.-C., Li, J.-Q., Qi, D.-H., Chen, X.-D., Wang, J.-J., Yao, B.-W., Yu, M.-X., Lu, T.-B., et al. (2021) · ACS Nano · doi:10.1021/acsnano.0c08921 · Cited by 438
Optoelectronic Synaptic Devices for Neuromorphic Computing
Wang, Y., Yin, L., Huang, W., Li, Y., Huang, S., Zhu, Y., Yang, D., & Pi, X. (2021) · Advanced Intelligent Systems · doi:10.1002/aisy.202000099 · Cited by 403
Self-citationOrganic optoelectronic synapse based on photon-modulated electrochemical doping
Chen, K., Hu, H., Song, I., Gobeze, H. B., Lee, W.-J., Abtahi, A., Schanze, K. S., & Mei, J. (2023) · Nature Photonics · doi:10.1038/s41566-023-01232-x · Cited by 298
Nanostructured perovskites for nonvolatile memory devices
Liu, Q., Gao, S., Xu, L., Yue, W., Zhang, C., Kan, H., Li, Y., & Shen, G. (2022) · Chemical Society Reviews · doi:10.1039/d1cs00886b · Cited by 163
Metadata
- Authors
- Wang, K., Dai, S., Zhao, Y., Wang, Y., Liu, C., & Huang, J.
- Venue
- Small
- Publisher
- Wiley
- Published
- 2019-02-10
- Volume
- 15
- Issue
- 11
- Pages
- e1900010-e1900010
- ISSN
- 1613-6810 (ISSN-L)
- 1613-6829
- OpenAlex
- W2914385201
- Cited by
- 285
- References
- 45
- FWCI
- 12.95
- Type
- journal article
- Language
- en
- Open access
- closed
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