Li-Ion Synaptic Transistor-Based Nociceptive Afferent Neural Sensing Platform for Fire Scenarios

In this study, a photothermal pain sensing neural platform for fire scenarios was implemented based on the integration of a multigate Li-ion electrolyte-gated transistor device with a thermoelectric generator and a photoresistor. Peripheral sensitization, desensitization, pain threshold, and other basic nociceptive behaviors of nociceptive afferents were successfully emulated. This photothermal pain sensing platform realized the judgment of the distance of the fire from the incident light of the photothermal source. The secondary injury process and the composite injury sensing process were also mimicked. This work extends the applications of Li-ion synaptic transistors in artificial nervous systems and provides new ideas for the development of practical and feasible pain sensing systems.

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Publication Details

Journal
ACS Applied Materials & Interfaces
Published
2025-10-18
DOI
https://doi.org/10.1021/acsami.5c15588
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
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article

Li-Ion Synaptic Transistor-Based Nociceptive Afferent Neural Sensing Platform for Fire Scenarios

Zhi-Wei Zheng, Yuefei Cai, Lei Zhu, Kun-Wen Huang
ACS Applied Materials & Interfaces
EEG and Brain-Computer Interfaces
article

Li-Ion Synaptic Transistor-Based Nociceptive Afferent Neural Sensing Platform for Fire Scenarios

Zhi-Wei Zheng, Yuefei Cai, Lei Zhu, Kun-Wen Huang
article en

Abstract

In this study, a photothermal pain sensing neural platform for fire scenarios was implemented based on the integration of a multigate Li-ion electrolyte-gated transistor device with a thermoelectric generator and a photoresistor. Peripheral sensitization, desensitization, pain threshold, and other basic nociceptive behaviors of nociceptive afferents were successfully emulated. This photothermal pain sensing platform realized the judgment of the distance of the fire from the incident light of the photothermal source. The secondary injury process and the composite injury sensing process were also mimicked. This work extends the applications of Li-ion synaptic transistors in artificial nervous systems and provides new ideas for the development of practical and feasible pain sensing systems.

ACS Applied Materials & InterfacesVol. 17(43)
Xiamen University (CN), Xiamen University of Technology (CN)
Openalex Percentile: Top 70%
EEG and Brain-Computer Interfaces
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Li-Ion Synaptic Transistor-Based Nociceptive Afferent Neural Sensing Platform for Fire Scenarios — Zhi-Wei Zheng, Yuefei Cai, et al. · ACS Applied Materials & Interfaces (2025) | TGRS Research Map | TGRS