Mixed‐Dimensional Floating Gate Phototransistors for Mixed‐Modal In‐Sensor Reservoir Computing

Novel neuromorphic devices constructed from low-dimensional materials have demonstrated significant potential in visual perception and information processing. Colloidal quantum dots (QDs) exhibit strong light absorption and tunable band gaps, while 2D materials provide smooth interfaces and channels with superior charge carrier mobility. However, the potential of devices utilizing QDs as floating gates and 2D materials as channels remains largely underexplored. Herein, a floating-gate phototransistor based on the mixed-dimensional heterostructure of 0D-CsPbBr<sub>3</sub> QDs and 2D-MoS<sub>2</sub> few layer is introduced. By leveraging the optical advantages of 0D-QDs and the electrical properties of 2D materials, mixed-modal in-sensor reservoir computing (RC) is realized. Upon electrical/optical stimulation, the device demonstrates an on/off ratio of 10<sup>7</sup>, over 7-bit multistates, nonlinear memory decay behavior, and dynamics with tunable time scales. Building upon these characteristics, the device enables mixed-modal RC using mixed-inputs of optical and electrical signals. Furthermore, accurate recognition of endangered species under extreme weather conditions is also demonstrated through audio-visual fusion. This study presents a compelling paradigm for utilizing the properties of different-dimensional materials to achieve mixed-modal information fusion and opens new pathways for mimicking biological multisensory fusion.

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Publication Details

Journal
Advanced Science
Published
2025-05-08
DOI
https://doi.org/10.1002/advs.202502694
Citations
3
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
2.19

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article

Mixed‐Dimensional Floating Gate Phototransistors for Mixed‐Modal In‐Sensor Reservoir Computing

Xiao Luo, Fan Yang, Fucai Liu, Yingying Chen et al.
3 citations
Advanced Science
Advanced Memory and Neural Computing
2.19
article

Mixed‐Dimensional Floating Gate Phototransistors for Mixed‐Modal In‐Sensor Reservoir Computing

Xiao Luo, Fan Yang, Fucai Liu, Yingying Chen, Qirui Zhang, Jiangang Chen, Wei-Lun Ouyang, Xuemei Wang, Qi Nie
article en
3 citations

Abstract

Novel neuromorphic devices constructed from low-dimensional materials have demonstrated significant potential in visual perception and information processing. Colloidal quantum dots (QDs) exhibit strong light absorption and tunable band gaps, while 2D materials provide smooth interfaces and channels with superior charge carrier mobility. However, the potential of devices utilizing QDs as floating gates and 2D materials as channels remains largely underexplored. Herein, a floating-gate phototransistor based on the mixed-dimensional heterostructure of 0D-CsPbBr<sub>3</sub> QDs and 2D-MoS<sub>2</sub> few layer is introduced. By leveraging the optical advantages of 0D-QDs and the electrical properties of 2D materials, mixed-modal in-sensor reservoir computing (RC) is realized. Upon electrical/optical stimulation, the device demonstrates an on/off ratio of 10<sup>7</sup>, over 7-bit multistates, nonlinear memory decay behavior, and dynamics with tunable time scales. Building upon these characteristics, the device enables mixed-modal RC using mixed-inputs of optical and electrical signals. Furthermore, accurate recognition of endangered species under extreme weather conditions is also demonstrated through audio-visual fusion. This study presents a compelling paradigm for utilizing the properties of different-dimensional materials to achieve mixed-modal information fusion and opens new pathways for mimicking biological multisensory fusion.

Advanced ScienceVol. 12(29)
University of Electronic Science and Technology of China (CN), National Engineering Research Center of Electromagnetic Radiation Control Materials (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 12%
Advanced Memory and Neural Computing
2.19
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