Boosting Performance of Ga₂O₃ Thin-Film Transistors via Defect Passivation toward Solar-Blind Ultraviolet In-Sensor Reservoir Computing.

Abstract

Ga₂O₃ 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 Ga₂O₃ TFTs is constrained by defect-induced impediments to free carrier transport. This work introduces a strategy comprising nitrogen annealing followed by Al₂O₃ encapsulation via atomic layer deposition, which boosts the mobility and solar-blind UV responsivity of Ga₂O₃ 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 Ga₂O₃. Furthermore, the competition and synergy between photoconduction and gating in Ga₂O₃ 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 Ga₂O₃ 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.