Retina‐Mimetic In‐Sensor Visual Processing via Bidirectional Photoconductivity in Encapsulated Tellurium Nanowire Devices

Abstract As demand for intelligent machine vision systems grows across diverse fields, neuromorphic computational approaches such as image preprocessing have become crucial for efficient visual processing. Inspired by the biological retina, in‐sensor computational systems offer intrinsic efficiency but have largely depended on multi‐wavelength strategies for optoelectronic contrast enhancement. Here, retina‐mimetic Al 2 O 3 ‐encapsulated tellurium nanowire in‐sensor neuromorphic transistors are introduced for image preprocessing. Interestingly, these devices exhibit gate‐tunable positive and negative photoconductivity under monochromatic illumination, closely resembling retinal visual processing, such as the bidirectional excitatory/inhibitory behavior. The trap‐assisted recombination model, governed by gate polarity, elucidates this gate‐bias tunability. Furthermore, bio‐inspired image preprocessing under varying noise levels resulted in substantial improvements in recognition, ≈93.01% for the weak‐noise and 69.01% strong‐noise case, highlighting the promise of chalcogenide nanowire devices for highly biomimetic artificial vision systems.

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Publication Details

Journal
Advanced Functional Materials
Published
2025-12-03
DOI
https://doi.org/10.1002/adfm.202525952
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
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article

Retina‐Mimetic In‐Sensor Visual Processing via Bidirectional Photoconductivity in Encapsulated Tellurium Nanowire Devices

Mose Park, Hoo‐Jeong Lee, Sung Kyu Park, Dong‐Won Kang et al.
Advanced Functional Materials
Advanced Memory and Neural Computing
article

Retina‐Mimetic In‐Sensor Visual Processing via Bidirectional Photoconductivity in Encapsulated Tellurium Nanowire Devices

Mose Park, Hoo‐Jeong Lee, Sung Kyu Park, Dong‐Won Kang, Jeehoon Kim, Seung‐Han Kang, Yong‐Hoon Kim
article en

Abstract

Abstract As demand for intelligent machine vision systems grows across diverse fields, neuromorphic computational approaches such as image preprocessing have become crucial for efficient visual processing. Inspired by the biological retina, in‐sensor computational systems offer intrinsic efficiency but have largely depended on multi‐wavelength strategies for optoelectronic contrast enhancement. Here, retina‐mimetic Al 2 O 3 ‐encapsulated tellurium nanowire in‐sensor neuromorphic transistors are introduced for image preprocessing. Interestingly, these devices exhibit gate‐tunable positive and negative photoconductivity under monochromatic illumination, closely resembling retinal visual processing, such as the bidirectional excitatory/inhibitory behavior. The trap‐assisted recombination model, governed by gate polarity, elucidates this gate‐bias tunability. Furthermore, bio‐inspired image preprocessing under varying noise levels resulted in substantial improvements in recognition, ≈93.01% for the weak‐noise and 69.01% strong‐noise case, highlighting the promise of chalcogenide nanowire devices for highly biomimetic artificial vision systems.

Advanced Functional Materials
Intelligent Energy (United Kingdom) (GB), Chung-Ang University (KR), Sungkyunkwan University (KR)
Openalex Percentile: Top 62%
Advanced Memory and Neural Computing
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Retina‐Mimetic In‐Sensor Visual Processing via Bidirectional Photoconductivity in Encapsulated Tellurium Nanowire Devices — Mose Park, Hoo‐Jeong Lee, et al. · Advanced Functional Materials (2025) | TGRS Research Map | TGRS