Selective-Attention Neuromorphic Vision Classifications Based on ɑ-In<sub>2</sub>Se<sub>3</sub>Bi<sub>2</sub>O<sub>2</sub>Se Ferroelectric-Semiconductor Heterotransistors

Herein, we present multifunctional neuromorphic vision device based on the ɑ-In<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>Se<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</inf>Bi<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>O<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>Se ferroelectricsemiconductor heterojunction. Central to this innovation is the in-plane voltage that drives out-of-plane polarization coupling within the ferroelectric heterojunction, which facilitates non-volatile conductance alterations through modulating the interface charge configuration with the robust stability demonstrated over 10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sup> cycles. Furthermore, the device exploits a photo-induced ferroelectric polarization reversal mechanism, resulting in a nonvolatile light response that persists for over 10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> s, accompanied with an impressive photoresponsivity of up to 10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">5</sup> A/W in the broad-spectrum range of 400-980 nm. We demonstrate the in-sensor pattern classification by the optoelectronic-ferroelectric driven spectrum-selective attention.

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Published
2025-03-09
DOI
https://doi.org/10.1109/edtm61175.2025.11040245
Primary Topic
Advanced Memory and Neural Computing
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article
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article

Selective-Attention Neuromorphic Vision Classifications Based on ɑ-In2Se3Bi2O2Se Ferroelectric-Semiconductor Heterotransistors

Xinrui Guo, Yu Zhu, Shuo Liu, Ming He et al.
Advanced Memory and Neural Computing
article

Selective-Attention Neuromorphic Vision Classifications Based on ɑ-In2Se3Bi2O2Se Ferroelectric-Semiconductor Heterotransistors

Xinrui Guo, Yu Zhu, Shuo Liu, Ming He, Junling Liu, Ru Huang
article en

Abstract

Herein, we present multifunctional neuromorphic vision device based on the ɑ-In<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>Se<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</inf>Bi<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>O<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>Se ferroelectricsemiconductor heterojunction. Central to this innovation is the in-plane voltage that drives out-of-plane polarization coupling within the ferroelectric heterojunction, which facilitates non-volatile conductance alterations through modulating the interface charge configuration with the robust stability demonstrated over 10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sup> cycles. Furthermore, the device exploits a photo-induced ferroelectric polarization reversal mechanism, resulting in a nonvolatile light response that persists for over 10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> s, accompanied with an impressive photoresponsivity of up to 10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">5</sup> A/W in the broad-spectrum range of 400-980 nm. We demonstrate the in-sensor pattern classification by the optoelectronic-ferroelectric driven spectrum-selective attention.

Peking University (CN)
Openalex Percentile: Top 87%
Advanced Memory and Neural Computing
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Selective-Attention Neuromorphic Vision Classifications Based on ɑ-In<sub>2</sub>Se<sub>3</sub>Bi<sub>2</sub>O<sub>2</sub>Se Ferroelectric-Semiconductor Heterotransistors — Xinrui Guo, Yu Zhu, et al. · (2025) | TGRS Research Map | TGRS