近日，西安电子科技大学常晶晶团队研究了基于宽带隙Ga₂O₃的多功能光电忆阻器助力人工突触和神经形态计算。这一研究成果于2025年4月15日发表在《光：科学与应用》杂志上。

光电忆阻器具有数据存储和模拟人类视觉感知的能力。它们在神经形态视觉系统（NV）中具有巨大的前景。本研究介绍了非晶宽带隙Ga₂O₃光电突触忆阻器，该忆阻器通过调节电流顺应性（Icc）和利用可变紫外（UV-254 nm）光强度来实现3位数据存储。

忆阻器辅助逻辑（MAGIC）中的“AND”和“OR”逻辑门是通过利用电压极性和紫外光作为输入信号来实现的。该装置还表现出高度稳定的突触特征，如成对脉冲易化（PPF）、尖峰强度依赖性可塑性（SIDP）、尖峰数量依赖性塑性（SNDP）、尖峰时间依赖性可塑率（STDP）、高峰频率依赖性可塑度（SFDP）和学习体验行为。

最后，当集成到人工神经网络（ANN）中时，Ag/Ga₂O₃/Pt忆阻器件以高图案精度（90.7%）模拟了光脉冲增强和电脉冲抑制。具有多功能特征的单忆阻单元是光电存储、神经形态计算和人工视觉感知应用的有前景的候选者。

附：英文原文

Title: Versatile optoelectronic memristor based on wide-bandgap Ga2O3 for artificial synapses and neuromorphic computing

Author: Cui, Dongsheng, Pei, Mengjiao, Lin, Zhenhua, Zhang, Hong, Kang, Mengyang, Wang, Yifei, Gao, Xiangxiang, Su, Jie, Miao, Jinshui, Li, Yun, Zhang, Jincheng, Hao, Yue, Chang, Jingjing

Issue&Volume: 2025-04-15

Abstract: Optoelectronic memristors possess capabilities of data storage and mimicking human visual perception. They hold great promise in neuromorphic visual systems (NVs). This study introduces the amorphous wide-bandgap Ga2O3 photoelectric synaptic memristor, which achieves 3-bit data storage through the adjustment of current compliance (Icc) and the utilization of variable ultraviolet (UV-254 nm) light intensities. The “AND” and “OR” logic gates in memristor-aided logic (MAGIC) are implemented by utilizing voltage polarity and UV light as input signals. The device also exhibits highly stable synaptic characteristics such as paired-pulse facilitation (PPF), spike-intensity dependent plasticity (SIDP), spike-number dependent plasticity (SNDP), spike-time dependent plasticity (STDP), spike-frequency dependent plasticity (SFDP) and the learning experience behavior. Finally, when integrated into an artificial neural network (ANN), the Ag/Ga2O3/Pt memristive device mimicked optical pulse potentiation and electrical pulse depression with high pattern accuracy (90.7%). The single memristive cells with multifunctional features are promising candidates for optoelectronic memory storage, neuromorphic computing, and artificial visual perception applications.

DOI: 10.1038/s41377-025-01773-6

Source: https://www.nature.com/articles/s41377-025-01773-6