journal article·2023-01

A Hemispherical Image Sensor Array Fabricated with Organic Photomemory Transistors

Yeongin Kim, Chenxin Zhu, Wen‐Ya Lee, Anna Smith, Haowen Ma, Xiang Li, Donghee Son, Naoji Matsuhisa, Jaemin Kim, Won‐Gyu Bae, Sung Ho Cho, Myung‐Gil Kim, Tadanori Kurosawa, Toru Katsumata, John W. F. To, Jin Young Oh, Seonghyun Paik, Soo Jin Kim, Lihua Jin, Feng Yan, Jeffrey B.‐H. Tok, Zhenan Bao

Advanced Materials· Volume 35· Issue 1
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Abstract

Abstract Hemispherical image sensors simplify lens designs, reduce optical aberrations, and improve image resolution for compact wide‐field‐of‐view cameras. To achieve hemispherical image sensors, organic materials are promising candidates due to the following advantages: tunability of optoelectronic/spectral response and low‐temperature low‐cost processes. Here, a photolithographic process is developed to prepare a hemispherical image sensor array using organic thin film photomemory transistors with a density of 308 pixels per square centimeter. This design includes only one photomemory transistor as a single active pixel, in contrast to the conventional pixel architecture, consisting of select/readout/reset transistors and a photodiode. The organic photomemory transistor, comprising light‐sensitive organic semiconductor and charge‐trapping dielectric, is able to achieve a linear photoresponse (light intensity range, from 1 to 50 W m−2), along with a responsivity as high as 1.6 A W−1 (wavelength = 465 nm) for a dark current of 0.24 A m−2 (drain voltage = −1.5 V). These observed values represent the best responsivity for similar dark currents among all the reported hemispherical image sensor arrays to date. A transfer method was further developed that does not damage organic materials for hemispherical organic photomemory transistor arrays. These developed techniques are scalable and are amenable for other high‐resolution 3D organic semiconductor devices.
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Research context

OpenAlex topics: CCD and CMOS Imaging Sensors · Organic Electronics and Photovoltaics · Advanced Memory and Neural Computing

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Electrical Engineering Stanford University Stanford CA 94305 USA

Department of Chemical Engineering Stanford University Stanford CA 94305 USA

School of Electronic Science and Engineering Nanjing University Nanjing 210093 China

Department of Chemical and Biological Engineering University at Buffalo Buffalo NY 14260 USA

Department of Electrical and Computer Engineering Sungkyunkwan University 16419 Suwon South Korea

Samsung Display Suwon 17113 South Korea

Asahi Kasei Tokyo 100‐0006 Japan

Department of Chemical Engineering (Integrated Engineering Program) Kyung Hee University Yongin 17104 South Korea

Department of Mechanical and Aerospace Engineering University of California Los Angeles Los Angeles CA 90095 USA

Funding

National Science Foundation

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