The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
An Artificial Flexible Visual Memory System Based on an UV‐Motivated Memristor
Abstract
For the mimicry of human visual memory, a prominent challenge is how to detect and store the image information by electronic devices, which demands a multifunctional integration to sense light like eyes and to memorize image information like the brain by transforming optical signals to electrical signals that can be recognized by electronic devices. Although current image sensors can perceive simple images in real time, the image information fades away when the external image stimuli are removed. The deficiency between the state‐of‐the‐art image sensors and visual memory system inspires the logical integration of image sensors and memory devices to realize the sensing and memory process toward light information for the bionic design of human visual memory. Hence, a facile architecture is designed to construct artificial flexible visual memory system by employing an UV‐motivated memristor. The visual memory arrays can realize the detection and memory process of UV light distribution with a patterned image for a long‐term retention and the stored image information can be reset by a negative voltage sweep and reprogrammed to the same or an other image distribution, which proves the effective reusability. These results provide new opportunities for the mimicry of human visual memory and enable the flexible visual memory device to be applied in future wearable electronics, electronic eyes, multifunctional robotics, and auxiliary equipment for visual handicapped.
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Cites
Redox‐Based Resistive Switching Memories – Nanoionic Mechanisms, Prospects, and Challenges
Waser, R., Dittmann, R., Staikov, G., & Szot, K. (2009) · Advanced Materials · doi:10.1002/adma.200900375 · Cited by 5,080
Nanoscale Memristor Device as Synapse in Neuromorphic Systems
Jo, S. H., Chang, T., Ebong, I., Bhadviya, B. B., Mazumder, P., & Lu, W. (2010) · Nano Letters · doi:10.1021/nl904092h · Cited by 4,174
Memristive devices for computing
Yang, J. J., Strukov, D. B., & Stewart, D. R. (2013) · Nature Nanotechnology · doi:10.1038/nnano.2012.240 · Cited by 3,885
Memristive switching mechanism for metal/oxide/metal nanodevices
Yang, J. J., Pickett, M. D., Li, X., Ohlberg, D. A. A., Stewart, D. R., & Williams, R. S. (2008) · Nature Nanotechnology · doi:10.1038/nnano.2008.160 · Cited by 2,987
Invariant visual representation by single neurons in the human brain
Quiroga, R. Q., Reddy, L., Kreiman, G., Koch, C., & Fried, I. (2005) · Nature · doi:10.1038/nature03687 · Cited by 1,988
‘Memristive’ switches enable ‘stateful’ logic operations via material implication
Borghetti, J., Snider, G. S., Kuekes, P. J., Yang, J. J., Stewart, D. R., & Williams, R. S. (2010) · Nature · doi:10.1038/nature08940 · Cited by 1,929
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
Resistance switching memories are memristors
Chua, L. (2011) · Applied Physics A · doi:10.1007/s00339-011-6264-9 · Cited by 1,434
Nanoelectronic programmable synapses based on phase change materials for brain-inspired computing
Kuzum, D., Jeyasingh, R. G. D., Lee, B., & Wong, H.-S. P. (2012) · Nano Letters · doi:10.1021/nl201040y · Cited by 1,267
Deng, W., Zhang, X., Huang, L., Xu, X., Wang, L., Wang, J., Shang, Q., Lee, S., & Jie, J. (2016) · Advanced Materials · doi:10.1002/adma.201505126 · Cited by 432
Cited by
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
An Oxide Schottky Junction Artificial Optoelectronic Synapse
Gao, S., Liu, G., Yang, H., Hu, C., Chen, Q., Gong, G., Xue, W., Yi, X., Shang, J., & Li, R.-W. (2019) · ACS Nano · doi:10.1021/acsnano.9b00340 · Cited by 494
The Future of Memristors: Materials Engineering and Neural Networks
Sun, K., Chen, J., & Yan, X. (2021) · Advanced Functional Materials · doi:10.1002/adfm.202006773 · Cited by 482
Materials and Designs for Wearable Photodetectors
Cai, S., Xu, X., Yang, W., Chen, J., & Fang, X. (2019) · Advanced Materials · doi:10.1002/adma.201808138 · Cited by 445
Metadata
- Authors
- Chen, S., Lou, Z., Chen, D., & Shen, G.
- Venue
- Advanced Materials
- Publisher
- Wiley
- Published
- 2018-01-08
- Volume
- 30
- Issue
- 7
- ISSN
- 0935-9648 (ISSN-L)
- 1521-4095
- OpenAlex
- W2783527453
- Cited by
- 437
- References
- 10
- FWCI
- 15.24
- Type
- journal article
- Language
- en
- Open access
- closed
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