2D Reconfigurable Memory for Integrated Optical Sensing and Multifunctional Image Processing

Recently, the growing demand for data-centric applications has significantly accelerated progress to overcome the "memory wall" caused by the separation of image sensing, memory, and computing units. However, despite advancements in novel devices driving the development of the in-sensor computing paradigm, achieving seamless integration of optical sensing, storage, and image processing within a single device remains challenging. This study demonstrates an in-sensor computing architecture using a ferroelectric-defined reconfigurable α-In<sub>2</sub>Se<sub>3</sub> phototransistor. The three polarization states of the device exhibit a linear and distinguishable photoresponse, with a maximum photoresponse current difference of 2.17 × 10<sup>-6</sup> A and a retention time exceeding 500 s. The nonvolatile weight and synaptic properties are programmed by external electrical stimulation, enabling 112 distinct conductance states with a nonlinearity of 0.12. Additionally, the device supports efficient optical writing, electrical erasing, optoelectronic logic, and decoding via combined optoelectronic control. In-sensor computation for image edge detection is simulated by embedding a nonvolatile Prewitt convolution kernel into a 3 × 3 device array. The integrated structure and array design highlight the strong potential of 2D ferroelectric semiconductors for in-sensor computing, providing a promising platform for next-generation multifunctional artificial vision systems.

Authors

Institutions

Publication Details

Journal
ACS Applied Materials & Interfaces
Published
2025-04-16
DOI
https://doi.org/10.1021/acsami.5c01496
Citations
3
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
2.19
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

2D Reconfigurable Memory for Integrated Optical Sensing and Multifunctional Image Processing

Yu Zheng, Jie Cheng, Bing Song, Shu Liu et al.
3 citations
ACS Applied Materials & Interfaces
Advanced Memory and Neural Computing
2.19
article

2D Reconfigurable Memory for Integrated Optical Sensing and Multifunctional Image Processing

Yu Zheng, Jie Cheng, Bing Song, Shu Liu, Xin Tang, Long‐Qing Chen, Bingdong Qin, Xinyu Ouyang
article en
3 citations

Abstract

Recently, the growing demand for data-centric applications has significantly accelerated progress to overcome the "memory wall" caused by the separation of image sensing, memory, and computing units. However, despite advancements in novel devices driving the development of the in-sensor computing paradigm, achieving seamless integration of optical sensing, storage, and image processing within a single device remains challenging. This study demonstrates an in-sensor computing architecture using a ferroelectric-defined reconfigurable α-In<sub>2</sub>Se<sub>3</sub> phototransistor. The three polarization states of the device exhibit a linear and distinguishable photoresponse, with a maximum photoresponse current difference of 2.17 × 10<sup>-6</sup> A and a retention time exceeding 500 s. The nonvolatile weight and synaptic properties are programmed by external electrical stimulation, enabling 112 distinct conductance states with a nonlinearity of 0.12. Additionally, the device supports efficient optical writing, electrical erasing, optoelectronic logic, and decoding via combined optoelectronic control. In-sensor computation for image edge detection is simulated by embedding a nonvolatile Prewitt convolution kernel into a 3 × 3 device array. The integrated structure and array design highlight the strong potential of 2D ferroelectric semiconductors for in-sensor computing, providing a promising platform for next-generation multifunctional artificial vision systems.

ACS Applied Materials & InterfacesVol. 17(17)
Central South University (CN), National University of Defense Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 13%
Advanced Memory and Neural Computing
2.19
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

2D Reconfigurable Memory for Integrated Optical Sensing and Multifunctional Image Processing — Yu Zheng, Jie Cheng, et al. · ACS Applied Materials & Interfaces (2025) | TGRS Research Map | TGRS