Enhanced conductance linearity in HfS2-based optoelectronic memristors via a defective h-BN interlayer for high-performance neuromorphic visual system

Two-dimensional materials offer potential for developing optoelectronic memristors and neuromorphic visual systems, benefitting from their atomically smooth surfaces and tailorable optoelectronic characteristics. However, the rapid recombination of photogenerated carriers within the two-dimensional materials-based optoelectronic memristors degrades the linearity of conductance updates, impairing the image recognition accuracy of neuromorphic visual systems. This work introduces a defective h-BN interlayer into HfS2-based optoelectronic memristors to improve nonvolatile conductance modulation. The fabricated HfS2/h-BN heterojunction optoelectronic memristor exhibits linear conductance tuning and emulates key synaptic functions, including excitatory postsynaptic current, paired-pulse facilitation, and transition from short-term to long-term plasticity. When used in an artificial neural network for image recognition, the device achieves an accuracy of 94%, higher than the 51% obtained with a pure HfS2 optoelectronic memristor. Mechanism studies reveal that the enhancement arises from efficient trapping and release of photogenerated carriers at the HfS2/h-BN interface. This work reveals that van der Waals heterojunction-interface defects-mediated carrier dynamics enable linear conductance modulation, offering a physical design principle for high-performance neuromorphic vision systems based on two-dimensional materials.

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Publication Details

Journal
Applied Physics Letters
Published
2026-01-12
DOI
https://doi.org/10.1063/5.0303804
Primary Topic
Advanced Memory and Neural Computing
Type
article
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article

Enhanced conductance linearity in HfS2-based optoelectronic memristors via a defective h-BN interlayer for high-performance neuromorphic visual system

Lingxin Meng, Y. Liu, Ya Lin, P. C. Li et al.
Applied Physics Letters
Advanced Memory and Neural Computing
article

Enhanced conductance linearity in HfS2-based optoelectronic memristors via a defective h-BN interlayer for high-performance neuromorphic visual system

Lingxin Meng, Y. Liu, Ya Lin, P. C. Li, Chunliang Wang, Xiaoning Zhao, Xuanyu Shan, Haiyang Xu, Jiaqi Han, Zhongqiang Wang, Ye Tao
article en

Abstract

Two-dimensional materials offer potential for developing optoelectronic memristors and neuromorphic visual systems, benefitting from their atomically smooth surfaces and tailorable optoelectronic characteristics. However, the rapid recombination of photogenerated carriers within the two-dimensional materials-based optoelectronic memristors degrades the linearity of conductance updates, impairing the image recognition accuracy of neuromorphic visual systems. This work introduces a defective h-BN interlayer into HfS2-based optoelectronic memristors to improve nonvolatile conductance modulation. The fabricated HfS2/h-BN heterojunction optoelectronic memristor exhibits linear conductance tuning and emulates key synaptic functions, including excitatory postsynaptic current, paired-pulse facilitation, and transition from short-term to long-term plasticity. When used in an artificial neural network for image recognition, the device achieves an accuracy of 94%, higher than the 51% obtained with a pure HfS2 optoelectronic memristor. Mechanism studies reveal that the enhancement arises from efficient trapping and release of photogenerated carriers at the HfS2/h-BN interface. This work reveals that van der Waals heterojunction-interface defects-mediated carrier dynamics enable linear conductance modulation, offering a physical design principle for high-performance neuromorphic vision systems based on two-dimensional materials.

Applied Physics LettersVol. 128(2)
Northeast Normal University (CN)
Openalex Percentile: Top 88%
Advanced Memory and Neural Computing
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Enhanced conductance linearity in HfS2-based optoelectronic memristors via a defective h-BN interlayer for high-performance neuromorphic visual system — Lingxin Meng, Y. Liu, et al. · Applied Physics Letters (2026) | TGRS Research Map | TGRS