Al-Stoichiometry-Engineered Defect Profiles in InAlZnO Nanofibers for Balanced Charge Transport and Optical Plasticity
Xudong Zhang, Xiangze Wang, Xianglong Wang, Xiaoyang Song, Haiyang Yu, Hengzhen Zhang, Ruxin Xue, Zhen Liu, Yuanbin Qin, Fengyun WangAbstract
Metal oxide optoelectronic synapses are promising for neuromorphic vision, but combining a low dark current with sustained photoinduced plasticity remains challenging. Here, Al stoichiometry is engineered in electrospun In1AlxZn0.08O (x = 0.007, 0.011, and 0.015) nanofiber networks to tune sub-bandgap defects, carrier transport, and photocarrier relaxation. Optical, spectroscopic, electrical, and synaptic measurements identify 1.1 atomic % Al as optimal. Strong Al–O bonding suppresses excess oxygen-vacancy-related donor states while preserving the In 5s transport network. The optimized device shows an off-state current of 10–11 A, an on/off ratio of 107, a field-effect mobility of 14 cm2 V–1 s–1, and a paired-pulse facilitation index of 271%. Under pulsed UV light, defect-assisted trapping and slow relaxation retain 30% of the peak photocurrent after 2 h. Neural network simulations achieve 95.7% handwritten digit recognition accuracy, highlighting the value of cation stoichiometry control for low-power optoelectronic neuromorphic computing.