Enhanced Mobility and Stability in Solution-Processed Mo-Pr Co-Doped In₂O₃ TFTs Guided by Machine Learning Optimization

Abstract

In₂O₃-based TFTs have garnered widespread attention due to their higher mobilities than amorphous silicon. Previous studies have indicated that rare earth doping can enhance the NBIS stability of TFTs, but this often results in a decrease in mobility. To improve the mobility of TFTs while maintaining stability, we incorporated Mo and Pr into In₂O₃, fabricating InPrMoO TFTs. Mo doping is believed to positively affect In₂O₃ through reducing porosity and defects. Pr doping has been proposed as a potential strategy to enhance the NBIS stability of In₂O₃. A nondestructive μPCD detector was employed to characterize the local defect states of the film. X-ray photoelectron spectroscopy data demonstrate that the InPrMoO film with 0.8 mol% Mo doping has the lowest concentration of oxygen vacancies (Vo). TFTs fabricated using the InPrMoO film doped with an optimized concentration of 0.8 mol% Mo exhibit superior electrical properties (μ_sat = 12.2 cm²/V·s, V_th = 1.6 V, I_on/I_off = 2.17 × 10⁶, and SS = 0.47 V/dec) and the minimal ΔV_th under NBS/PBS/NBIS = −0.65 V/0.79 V/−0.70 V. The synergistic effect of Mo and Pr doping has led to enhanced film uniformity and density, consequently improving the mobility and stability of the TFTs. To tackle the challenge of predicting optimal process parameters, a multiobjective prediction model integrating physical models and machine learning was developed. The predicted optimal parameters (0.78 mol% Mo doping, 381°C annealing) were experimentally verified, yielding < 5% relative error in most film properties. The prepared TFT exhibits a mobility of 13.5 cm²/V·s (10.6% improvement), an on/off current ratio of 3.82 × 10⁶, and an SS of 0.40 V/dec, demonstrating superior efficiency over conventional trial-and-error methods.

Keywords

high NBIS stability / machine learning / metal oxide / molybdenum doping / oxygen vacancy suppressing

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