Light-modulated synaptic response of planar WS2–PVA hybrid memristors for artificial synapses and quantization-aware neural networks
Two-dimensional-material-based artificial synapses that combine stable electrical switching with optical tunability are promising for neuromorphic systems. Here, a planar Cr/WS 2 –PVA/Cr memristive device was fabricated using liquid-phase-exfoliated WS 2 sheets embedded in a PVA matrix. The device exhibited stable analog bipolar resistive switching with self-rectifying behavior over 300 cycles. Its switching characteristics were associated with defect-assisted charge trapping, Poole–Frenkel-type emission, and space-charge-assisted transport within the WS 2 –PVA hybrid active layer. Sulfur-vacancy-related states and polymer-assisted trapping centers contributed to the gradual modulation of conductance. Under 425 nm illumination, extending the exposure time from 30 to 120 s increased the conductance from 1.7 to 5.4 μS, facilitating light-assisted learning and relaxation-based forgetting behavior after light removal. Hardware-aware ResNet-20 simulations using the measured conductance states achieved a CIFAR-10 accuracy of 81.91 ± 0.29% after 120 s of illumination, averaged over five independent seeds. The device-aware models maintained classification accuracies above 81% under both dark and illuminated conditions, demonstrating the feasibility of integrating experimentally obtained WS 2 –PVA conductance states into neuromorphic inference. These findings highlight the potential of WS 2 –PVA hybrid memristors for electrically and optically tunable artificial synapses and neuromorphic inference.
Authors
- Thuat Nguyen-Tran (ORCID: https://orcid.org/0000-0002-3761-2794)
- Ngoc Kim Pham (ORCID: https://orcid.org/0000-0003-0449-1532)
- D. Son (ORCID: https://orcid.org/0000-0002-0610-1369)
- Phu‐Quan Pham (ORCID: https://orcid.org/0000-0001-9348-2763)
- Nhat Quang Minh Tran (ORCID: https://orcid.org/0000-0001-7143-0268)
- Thuy Thi Dieu Ung
- Quang Nguyen (ORCID: https://orcid.org/0000-0002-1188-3385)
- Trung Bao Ngoc Duong (ORCID: https://orcid.org/0009-0005-6077-6489)
- Duc Minh Nguyen
- Hoang-Tho Nguyen
- Hoang-Tuan Tong
- Masamichi Yoshimura
- Huong Ngoc Phan
- Truong Phi Le
Institutions
- Vietnam National University Ho Chi Minh City (VN)
- Vietnam National University, Hanoi (VN)
- Ho Chi Minh City University of Science (VN)
- Institute of Materials Science (VN)
- Ho Chi Minh City University of Technology (VN)
- Toyota Technological Institute (JP)
- VNU University of Science (VN)
- Vietnam Academy of Science and Technology (VN)
Publication Details
- Journal
- Materials Science in Semiconductor Processing
- Published
- 2026-09-29
- DOI
- https://doi.org/10.1016/j.mssp.2026.111223
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00