Surface Argon Plasma Treatment Enabled Broadband Optoelectronic Synapses Based on Large-Scale Epitaxial GaSe/GaN Heterojunctions

Creating and tuning charge trapping states by introducing atomic-scale defects are crucial for the optoelectronic synapses that parallelize sensing, processing, and memorizing of optical signals in a single device, which is essential for bioinspired neuromorphic computing. Herein, a mild Ar-plasma treatment approach to enable synaptic behavior in 2D semiconductor devices has been proposed and demonstrated in large-scale epitaxial GaSe/GaN heterostructures. The GaSe films were epitaxially grown on a GaN substrate by physical vapor deposition in an ultrahigh vacuum environment, while the devices were fabricated in situ using a shadow mask-assisted electrode deposition technique. A tailored mild Ar-plasma treatment on the GaSe films has been employed to create atomic-scale defects, which provide charge trapping states in the band gap without making morphological damage, as confirmed by the Raman spectra, scanning electron microscopy, and photoluminescence characterizations. Optoelectronic transport measurement under pulsed illumination of varying wavelengths reveals broadband photoresponse and significantly prolonged response time (×10<sup>3</sup>) that give rise to the superior performance of the synaptic devices. This has been proven by the simulation of classic synaptic behaviors of adaptive pain perception and associative learning. Our work provides an efficient approach to facilitate optoelectronic synaptic behaviors in 2D semiconductor devices.

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Publication Details

Journal
ACS Applied Materials & Interfaces
Published
2025-02-24
DOI
https://doi.org/10.1021/acsami.4c22477
Citations
2
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
1.46

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article

Surface Argon Plasma Treatment Enabled Broadband Optoelectronic Synapses Based on Large-Scale Epitaxial GaSe/GaN Heterojunctions

Jiaqi Yang, Yi Pan, Hong Lei, Yinuo Zhang et al.
2 citations
ACS Applied Materials & Interfaces
Advanced Memory and Neural Computing
1.46
article

Surface Argon Plasma Treatment Enabled Broadband Optoelectronic Synapses Based on Large-Scale Epitaxial GaSe/GaN Heterojunctions

Jiaqi Yang, Yi Pan, Hong Lei, Yinuo Zhang, Lan Li, Yunan Lin, Xuecen Miao
article en
2 citations

Abstract

Creating and tuning charge trapping states by introducing atomic-scale defects are crucial for the optoelectronic synapses that parallelize sensing, processing, and memorizing of optical signals in a single device, which is essential for bioinspired neuromorphic computing. Herein, a mild Ar-plasma treatment approach to enable synaptic behavior in 2D semiconductor devices has been proposed and demonstrated in large-scale epitaxial GaSe/GaN heterostructures. The GaSe films were epitaxially grown on a GaN substrate by physical vapor deposition in an ultrahigh vacuum environment, while the devices were fabricated in situ using a shadow mask-assisted electrode deposition technique. A tailored mild Ar-plasma treatment on the GaSe films has been employed to create atomic-scale defects, which provide charge trapping states in the band gap without making morphological damage, as confirmed by the Raman spectra, scanning electron microscopy, and photoluminescence characterizations. Optoelectronic transport measurement under pulsed illumination of varying wavelengths reveals broadband photoresponse and significantly prolonged response time (×10<sup>3</sup>) that give rise to the superior performance of the synaptic devices. This has been proven by the simulation of classic synaptic behaviors of adaptive pain perception and associative learning. Our work provides an efficient approach to facilitate optoelectronic synaptic behaviors in 2D semiconductor devices.

ACS Applied Materials & InterfacesVol. 17(9)
Spintronics Research Network of Japan (JP), Xi’an Children’s Hospital (CN), Xi'an Jiaotong University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Affordable and clean energy
Openalex Percentile: Top 19%
Advanced Memory and Neural Computing
1.46
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