The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Piezotronic Graphene Artificial Sensory Synapse
Abstract
The human somatosensory system, consisting of receptors, transmitters, and synapses, functions as the medium for external mechanical stimuli perception and sensing signal delivery/processing. Developing sophisticated artificial sensory synapses with a high performance, uncomplicated fabrication process, and low power consumption is still a great challenge. Here, a piezotronic graphene artificial sensory synapse developed by integrating piezoelectric nanogenerator (PENG) with an ion gel–gated transistor is demonstrated. The piezopotential originating from PENG can efficiently power the synaptic device due to the formation of electrical double layers at the interface of the ion gel/electrode and ion gel/graphene. Meanwhile, the piezopotential coupling is capable of linking the spatiotemporal strain information (strain amplitude and duration) with the postsynaptic current. The synaptic weights can be readily modulated by the strain pulses. Typical properties of a synapse including excitation/inhibition, synaptic plasticity, and paired pulse facilitation are successfully demonstrated. The dynamic modulation of a sensory synapse is also achieved based on dual perceptual presynaptic PENGs coupling to a single postsynaptic transistor. This work provides a new insight into developing piezotronic synaptic devices in neuromorphic computing, which is of great significance in future self‐powered electronic skin with artificial intelligence, a neuromorphic interface for neurorobotics, human–robot interaction, an intelligent piezotronic transistor, etc.
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Cites
Piezoelectricity of single-atomic-layer MoS2 for energy conversion and piezotronics
Wu, W., Wang, L., Li, Y., Zhang, F., Lin, L., Niu, S., Chenet, D., Zhang, X., Hao, Y., Heinz, T. F., et al. (2014) · Nature · doi:10.1038/nature13792 · Cited by 2,287
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
Wu, W., Wen, X., & Wang, Z. L. (2013) · Science · doi:10.1126/science.1234855 · Cited by 931
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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
Flexible Neuromorphic Electronics for Computing, Soft Robotics, and Neuroprosthetics
Park, H., Lee, Y., Kim, N., Seo, D., Go, G., & Lee, T. (2020) · Advanced Materials · doi:10.1002/adma.201903558 · Cited by 533
Mimicking Human and Biological Skins for Multifunctional Skin Electronics
Lee, Y., Park, J., Choe, A., Cho, S., Kim, J., & Ko, H. (2020) · Advanced Functional Materials · doi:10.1002/adfm.201904523 · Cited by 465
Bioinspired mechano-photonic artificial synapse based on graphene/MoS 2 heterostructure
Yu, J., Yang, X., Gao, G., Xiong, Y., Wang, Y., Han, J., Chen, Y., Zhang, H., Sun, Q., & Wang, Z. L. (2021) · Science Advances · doi:10.1126/sciadv.abd9117 · Cited by 389
Self-citation2D Material Based Synaptic Devices for Neuromorphic Computing
Cao, G., Meng, P., Chen, J., Liu, H., Bian, R., Zhu, C., Liu, F., & Liu, Z. (2021) · Advanced Functional Materials · doi:10.1002/adfm.202005443 · Cited by 382
Metadata
- Authors
- Chen, Y., Gao, G., Zhao, J., Zhang, H., Yu, J., Yang, X., Zhang, Q., Zhang, W., Xu, S., Sun, J., Meng, Y., & Sun, Q.
- Venue
- Advanced Functional Materials
- Publisher
- Wiley
- Published
- 2019-03-28
- Volume
- 29
- Issue
- 41
- ISSN
- 1616-301X (ISSN-L)
- 1616-3028
- OpenAlex
- W2934517403
- Cited by
- 220
- References
- 3
- FWCI
- 9.54
- Type
- journal article
- Language
- en
- Open access
- closed
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