Boosting Performance of Ga <sub>2</sub> O <sub>3</sub> Thin-Film Transistors via Defect Passivation toward Solar-Blind Ultraviolet In-Sensor Reservoir Computing
Ga<sub>2</sub>O<sub>3</sub> thin-film transistors (TFTs) are resilient to high temperatures and voltages and are suitable for demanding display and sensing applications. Nevertheless, the performance of current Ga<sub>2</sub>O<sub>3</sub> TFTs is constrained by defect-induced impediments to free carrier transport. This work introduces a strategy comprising nitrogen annealing followed by Al<sub>2</sub>O<sub>3</sub> encapsulation via atomic layer deposition, which boosts the mobility and solar-blind UV responsivity of Ga<sub>2</sub>O<sub>3</sub> TFTs by more than 27-fold and 94-fold, respectively. The combined results of high-resolution transmission electron microscopy characterization and computer-aided design simulation ascribe these enhancements to the effective passivation of deep-level defects at the interface, in the bulk, and on the surface of Ga<sub>2</sub>O<sub>3</sub>. Furthermore, the competition and synergy between photoconduction and gating in Ga<sub>2</sub>O<sub>3</sub> TFTs yield a gate-voltage-programmable photoresponse, allowing for the control of both the responsivity and response time. Leveraging this, a solar-blind UV in-sensor reservoir computing system based on Ga<sub>2</sub>O<sub>3</sub> TFTs is demonstrated, which achieves over 91.8% accuracy in fingerprint image recognition even under 40% noise. This work integrates an effective defect passivation strategy with a clarified modulation mechanism and further demonstrates its application in neuromorphic computing. The approach presented here shows a broad potential for extension to other wide-bandgap semiconductor systems.
Authors
- Jiajuan Shi
- P. Li
- Zhuangzhuang Li (ORCID: https://orcid.org/0000-0001-8359-1317)
- Haiyan Li (ORCID: https://orcid.org/0000-0003-3654-7000)
- Y. Liu
- Ya Lin
- Zhongqiang Wang
- Xiaoning Zhao
- Jiangang Ma
- Haiyang Xu
Institutions
- Northeast Normal University (CN)
Publication Details
- Journal
- ACS Nano
- Published
- 2025-12-25
- DOI
- https://doi.org/10.1021/acsnano.5c18136
- Citations
- 1
- Primary Topic
- Ga2O3 and related materials
- Type
- article
- Field-Weighted Citation Impact
- 0.43