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dc.contributor.author | Kumar, Mohit | - |
dc.contributor.author | Lim, Jaeseong | - |
dc.contributor.author | Seo, Hyungtak | - |
dc.date.issued | 2021-11-01 | - |
dc.identifier.issn | 2211-2855 | - |
dc.identifier.uri | https://dspace.ajou.ac.kr/dev/handle/2018.oak/32235 | - |
dc.description.abstract | Photonic image sensors with programmable non-volatile manifold memory can offer an essential breakthrough for the advancement of optoelectronic memory, smart machine vision, and optical neuromorphic computing. Here, we developed a two-terminal, nickel oxide and titanium dioxide-based, highly transparent (> 65%), non-volatile, programmable, self-powered ultraviolet photodetector. The self-powered photoresponse was customized at various levels by fine-tuning an electric pulse, even without changing illumination intensity. Moreover, the photodetector mimics the optical-electrical-coupled versatile features of a bio-synapse, such as manifold memory capability, paired-pulse facilitation, and excitation or depression. The observed results are quantitatively explained by the dynamics of oxygen vacancy migration-induced junction width modulation. Furthermore, photoconductive atomic force microscopy revealed a tunable and scalable (over the desired area) photocurrent even at the nanoscale (~30 nm), providing high-density integration, with a pixel density of ~716 GB/in2. Moreover, an array was developed and integrated with the well-developed camera, which was trained dynamically to memorize and classify the desired input optical patterns, demonstrating self-adaptive human-like visual perception. Our programmable photodetector represents a unique possibility to develop a trainable photoresponse that collects information for the desired shape, offering profound implications for building a complex, trainable, and energy‐efficient neuromorphic imaging system. | - |
dc.description.sponsorship | This study was supported through the National Research Foundation of Korea [ NRF-2018R1D1A1B07049871 and NRF-2019R1A2C2003804 ] of the Ministry of Science and ICT, Republic of Korea . This work was also supported by Ajou University . | - |
dc.language.iso | eng | - |
dc.publisher | Elsevier Ltd | - |
dc.subject.mesh | Highly transparent | - |
dc.subject.mesh | Integrated cameras | - |
dc.subject.mesh | Multilevels | - |
dc.subject.mesh | Neuromorphic photodetector | - |
dc.subject.mesh | Non-volatile | - |
dc.subject.mesh | Optical- | - |
dc.subject.mesh | Photoresponses | - |
dc.subject.mesh | Reconfigurable | - |
dc.subject.mesh | Self-powered | - |
dc.subject.mesh | Visual perception | - |
dc.title | Highly transparent reconfigurable non-volatile multilevel optoelectronic memory for integrated self-powered brain-inspired perception | - |
dc.type | Article | - |
dc.citation.title | Nano Energy | - |
dc.citation.volume | 89 | - |
dc.identifier.bibliographicCitation | Nano Energy, Vol.89 | - |
dc.identifier.doi | 10.1016/j.nanoen.2021.106471 | - |
dc.identifier.scopusid | 2-s2.0-85114044284 | - |
dc.identifier.url | http://www.journals.elsevier.com/nano-energy/ | - |
dc.subject.keyword | Highly transparent | - |
dc.subject.keyword | Integrated camera | - |
dc.subject.keyword | Neuromorphic photodetector | - |
dc.subject.keyword | Non-volatile | - |
dc.subject.keyword | Visual perception | - |
dc.description.isoa | false | - |
dc.subject.subarea | Renewable Energy, Sustainability and the Environment | - |
dc.subject.subarea | Materials Science (all) | - |
dc.subject.subarea | Electrical and Electronic Engineering | - |
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