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
P. Li, Jiajuan Shi, Zhuangzhuang Li, Ya Lin, Haiyan Li, Zhongqiang Wang, Xiaoning Zhao, Jiangang Ma, Haiyang Xu, Y. Liu
Abstract
Ga 2 O 3 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 2 O 3 TFTs is constrained by defect-induced impediments to free carrier transport. This work introduces a strategy comprising nitrogen annealing followed by Al 2 O 3 encapsulation via atomic layer deposition, which boosts the mobility and solar-blind UV responsivity of Ga 2 O 3 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 2 O 3 . Furthermore, the competition and synergy between photoconduction and gating in Ga 2 O 3 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 2 O 3 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.