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Retina-Inspired Structurally Tunable Synaptic Perovskite Nanocones

Authors
Lee, KyuhoHan, HyowonKim, YoungwooPark, JumiJang, SeonghoonLee, HyeokjungLee, Seung WonKim, HoYeonKim, YeeunKim, TaebinKim, DonghoWang, GunukPark, Cheolmin
Issue Date
12월-2021
Publisher
WILEY-V C H VERLAG GMBH
Keywords
artificial retina; density-tunable perovskite nanocrystals; perovskite nanocones; photonic synapses; self-assembled photoreceptors
Citation
ADVANCED FUNCTIONAL MATERIALS, v.31, no.52
Indexed
SCIE
SCOPUS
Journal Title
ADVANCED FUNCTIONAL MATERIALS
Volume
31
Number
52
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/135606
DOI
10.1002/adfm.202105596
ISSN
1616-301X
Abstract
Artificial photonic synapses with morphologically controlled photoreception, allowing for area-dependent tunable light reception as well as information storage and learning, have potential for application in emerging photo-interactive neuro-computing technologies. Herein, an artificially intelligent (AI) photonic synapse with area-density-tunable perovskite nano-cone arrays templated in a self-assembled block copolymer (BCP) is presented, which is based on a field effect transistor with a floating gate of photoreceptive perovskite crystal arrays preferentially synthesized in a micro-phase-segregated BCP film. These arrays are capable of electric charge (de)trapping and photo-excited charge generation, and they exhibit versatile synaptic functions of the nervous system, including paired-pulse facilitation and long-term potentiation, with excellent reliability. The area-density variable perovskite floating gate developed by off-centered spin coating process allows for emulating the human retina with a position-dependent spatial distribution of cones. 60 x 12 arrays of the developed synapse devices exhibit position-dependent dual functions of receptor and synapse. They are AI and exhibit a pattern recognition accuracy up to approximate to 90% when examined using the Modified National Institute of Standards and Technology handwritten digit pattern recognition test.
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