Metal Oxide Nano-Interface Boosting the Deep Ultraviolet Adjustable Noise-Filtering In-Sensor Computing
Abstract
Long-afterglow light-emitting devices (LALEDs), which combine the capabilities of sensing, memory, processing, and display integration, allow for the simultaneous implementation of optical and electrical in-sensor computing. However, the inherently low conductivity of conventional deep-ultraviolet (DUV) responsive materials hinders their use in the DUV-responsive LALEDs (DUV-LALEDs). Herein, we demonstrate that sol-gel-fractured indium-magnesium oxide (InMgO) concurrently exhibits ideal nano-interface for DUV photon absorption and semiconductor crystal for efficient charge transport via hopping, enabling to reach high mobility (0.6 cm2 V−1 s−1), excellent memory dynamic range (70 dB), and responsivity (523.7 A/W). The InMgO-based DUV-LALEDs display an electrical and optical post-synaptic output when irradiated with DUV light. Moreover, hardware-level noise-filtering processes to the pre-synaptic weight are revealed in the DUV-LALEDs, emerging as the inhibition of light emission due to the insufficient post-synaptic charge injection from the channel layer. Consequently, an adjustable noise-filtering in-sensor computing is successfully achieved by modulating the channel length. By taking advantage of the DUV-LALED multifunctional nature, fusion-node reservoir computing networks are employed to accomplish multi-dimensional recognition tasks, displaying a high recognition accuracy of 99%. These findings demonstrate that the joint materials and devices optimization is a powerful strategy for fabricating cost-efficient DUV analytical chips.
Related
- Interface-Engineered ZIF-8-Derived ZnO@C/Bi/Bi2MoO6 Heterojunctions for Boosting Photo-Fenton-like Performance
- Pore suppression in adjustable ring-mode laser lap welding of dissimilar-thickness 1060 aluminum alloy
- Boosting Natural Rubber Performance by Backbone Rigid Functionalization
- Frozen sequence encoders with gradient boosting match the state of the art on drug–target affinity domain generalization, and a sequence defect in the Davis kinase benchmark
- Stepwise Condensation to Diversify Cyano-Substituted Vinylene-Linked COFs for Boosting H2O2 Photosynthesis
BibTeX
@article{ju2026metal,
title = {{Metal Oxide Nano-Interface Boosting the Deep Ultraviolet Adjustable Noise-Filtering In-Sensor Computing}},
author = {Zhongshi Ju and Peng Li and Jingsong Yuan and Boyuan Yu and Bin Han and Yusheng Chen and Jiangang Ma and Haiyang Xu and Yichun Liu and Paolo Samorì},
journal = {Advanced Materials},
year = {2026},
month = aug,
doi = {10.1002/adma.74481},
url = {https://univoak.hal.science/hal-05842257v1},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Metal Oxide Nano-Interface Boosting the Deep Ultraviolet Adjustable Noise-Filtering In-Sensor Computing
AU - Zhongshi Ju
AU - Peng Li
AU - Jingsong Yuan
AU - Boyuan Yu
AU - Bin Han
AU - Yusheng Chen
AU - Jiangang Ma
AU - Haiyang Xu
AU - Yichun Liu
AU - Paolo Samorì
PY - 2026
DA - 2026/08/06
JO - Advanced Materials
DO - 10.1002/adma.74481
UR - https://univoak.hal.science/hal-05842257v1
AB - Long-afterglow light-emitting devices (LALEDs), which combine the capabilities of sensing, memory, processing, and display integration, allow for the simultaneous implementation of optical and electrical in-sensor computing. However, the inherently low conductivity of conventional deep-ultraviolet (DUV) responsive materials hinders their use in the DUV-responsive LALEDs (DUV-LALEDs). Herein, we demonstrate that sol-gel-fractured indium-magnesium oxide (InMgO) concurrently exhibits ideal nano-interface for DUV photon absorption and semiconductor crystal for efficient charge transport via hopping, enabling to reach high mobility (0.6 cm2 V−1 s−1), excellent memory dynamic range (70 dB), and responsivity (523.7 A/W). The InMgO-based DUV-LALEDs display an electrical and optical post-synaptic output when irradiated with DUV light. Moreover, hardware-level noise-filtering processes to the pre-synaptic weight are revealed in the DUV-LALEDs, emerging as the inhibition of light emission due to the insufficient post-synaptic charge injection from the channel layer. Consequently, an adjustable noise-filtering in-sensor computing is successfully achieved by modulating the channel length. By taking advantage of the DUV-LALED multifunctional nature, fusion-node reservoir computing networks are employed to accomplish multi-dimensional recognition tasks, displaying a high recognition accuracy of 99%. These findings demonstrate that the joint materials and devices optimization is a powerful strategy for fabricating cost-efficient DUV analytical chips.
SN - 0935-9648
SN - 1521-4095
ER -