Room‐Temperature Magneto‐Photoresponse in All‐2D Optoelectronic Devices for In‐Sensor Vision Systems

Interplay between magnetism and photoelectric properties introduces the effective control of photoresponse in optoelectronic devices via magnetic field, termed as magneto-photoresponse. It enriches the application scenarios and shows potential to construct in-sensor vision systems for artificial intelligence with gate-free architecture. However, achieving a simultaneous existence of room-temperature magnetism and notable photoelectric properties in semiconductors is a great challenge. Here, the room-temperature magneto-photoresponse is accomplished in all-2D optoelectronic devices, employing 2D ferromagnet Fe<sub>3</sub>GaTe<sub>2</sub> as the source and drain, with WSe<sub>2</sub> forming the channel. The interplay between room-temperature magnetism and photoelectric properties is realized by introducing the unique magneto-band structure effect from 2D interface, resulting in magneto-tunable charge transfer between Fe<sub>3</sub>GaTe<sub>2</sub> and WSe<sub>2</sub>. The photocurrent in this 2D optoelectronic device exhibits robust response to both the direction and amplitude of external magnetic fields. Utilizing constructed 2D optoelectronic devices with magneto-photoresponse, traditional gate-controlled phototransistors are replaced and a prototype in-sensor vision system with visual adaptation, significantly improving the recognition accuracy to over four times in low-contrast environments is established. These findings pave a way for achieving high-temperature magneto-photoresponse, thereby guiding the construction of robust in-sensor vision systems toward high performance and broad applications.

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Publication Details

Journal
Advanced Materials
Published
2024-08-11
DOI
https://doi.org/10.1002/adma.202403624
Citations
12
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
2.50

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article

Room‐Temperature Magneto‐Photoresponse in All‐2D Optoelectronic Devices for In‐Sensor Vision Systems

Feng Pan, Cheng Song, Yuankun Li, Qingtian Zhang et al.
12 citations
Advanced Materials
Advanced Memory and Neural Computing
2.50
article

Room‐Temperature Magneto‐Photoresponse in All‐2D Optoelectronic Devices for In‐Sensor Vision Systems

Feng Pan, Cheng Song, Yuankun Li, Qingtian Zhang, Hua Bai, Huaqiang Wu, Yuyan Wang, Lei Han, Qian Wang, Wenxuan Zhu, Jiacheng Sun
article en
12 citations

Abstract

Interplay between magnetism and photoelectric properties introduces the effective control of photoresponse in optoelectronic devices via magnetic field, termed as magneto-photoresponse. It enriches the application scenarios and shows potential to construct in-sensor vision systems for artificial intelligence with gate-free architecture. However, achieving a simultaneous existence of room-temperature magnetism and notable photoelectric properties in semiconductors is a great challenge. Here, the room-temperature magneto-photoresponse is accomplished in all-2D optoelectronic devices, employing 2D ferromagnet Fe<sub>3</sub>GaTe<sub>2</sub> as the source and drain, with WSe<sub>2</sub> forming the channel. The interplay between room-temperature magnetism and photoelectric properties is realized by introducing the unique magneto-band structure effect from 2D interface, resulting in magneto-tunable charge transfer between Fe<sub>3</sub>GaTe<sub>2</sub> and WSe<sub>2</sub>. The photocurrent in this 2D optoelectronic device exhibits robust response to both the direction and amplitude of external magnetic fields. Utilizing constructed 2D optoelectronic devices with magneto-photoresponse, traditional gate-controlled phototransistors are replaced and a prototype in-sensor vision system with visual adaptation, significantly improving the recognition accuracy to over four times in low-contrast environments is established. These findings pave a way for achieving high-temperature magneto-photoresponse, thereby guiding the construction of robust in-sensor vision systems toward high performance and broad applications.

Advanced MaterialsVol. 36(47)
Tsinghua University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 10%
Advanced Memory and Neural Computing
2.50
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