基于非线性负光电导行为的自适应视觉传感器

IF 18.5 1区 材料科学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Chenxing Jin, Jingwen Wang, Wanrong Liu, Yunchao Xu, Xiaofang Shi, Ruihan Li, Jia Sun, Junliang Yang
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引用次数: 0

摘要

传感器内自适应视觉系统是一项前景广阔的技术,适用于各个领域。这种方法在降低系统复杂性的同时还能大大提高图像质量,因此具有重要的科学意义和实际应用价值。本研究利用配备离子凝胶门控的 In2O3/C8-BTBT 异质结晶体管器件,模拟光触发去极化神经形态响应。当异质结器件暴露在紫外线下时,In2O3 层中的电子会与 C8-BTBT 层中的空穴重新结合,导致光电流迅速下降,从而产生显著的负光反应。该器件能够模拟尖峰抑制电流和多级存储能力。此外,该器件还可用于构建紫外线自适应视网膜,利用其对紫外线强度和时间特性的独特依赖性,促进传感器内自适应计算成像,从而显著增强图像细节的可视化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Adaptive Vision Sensor Based on Nonlinear Negative Photoconductivity Behavior

Adaptive Vision Sensor Based on Nonlinear Negative Photoconductivity Behavior
In-sensor adaptive visual systems represent a promising technology applicable across various fields. This method significantly enhances image quality while reducing system complexity, thereby holding substantial scientific significance and practical applications. This study emulates a light-triggered depolarization neuromorphic response utilizing an In2O3/C8-BTBT heterojunction transistor device equipped with ion-gel gating. When the heterojunction device is exposed to UV light, electrons in the In2O3 layer recombine with holes in the C8-BTBT layer, leading to a rapid decrease in photocurrent and resulting in a significant negative photoresponse. The device is capable of simulating spike-dependent inhibitory currents and multilevel storage capabilities. Moreover, the proposed device is employed in constructing a UV-adaptive retina, facilitating in-sensor adaptive computational imaging by leveraging its unique dependence on UV intensity and temporal characteristics, thereby significantly enhancing the visualization of image details.
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来源期刊
Advanced Functional Materials
Advanced Functional Materials 工程技术-材料科学:综合
CiteScore
29.50
自引率
4.20%
发文量
2086
审稿时长
2.1 months
期刊介绍: Firmly established as a top-tier materials science journal, Advanced Functional Materials reports breakthrough research in all aspects of materials science, including nanotechnology, chemistry, physics, and biology every week. Advanced Functional Materials is known for its rapid and fair peer review, quality content, and high impact, making it the first choice of the international materials science community.
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