Multistate resistive switching device emerges as a promising electronic unit for energy-efficient neuromorphic computing. Electric-field induced topotactic phase transition with ionic evolution represents an important pathway for this purpose, which, however, faces significant challenges in device scaling. This work demonstrates a convenient scanning-probe-induced proton evolution within WO₃, driving a reversible insulator-to-metal transition (IMT) at nanoscale. Specifically, the Pt-coated scanning probe serves as an efficient hydrogen catalysis probe, leading to a hydrogen spillover across the nano junction between the probe and sample surface. A positively biased voltage drives protons into the sample, while a negative voltage extracts protons out, giving rise to a reversible manipulation on hydrogenation-induced electron doping, accompanied by a dramatic resistive switching. The precise control of the scanning probe offers the opportunity to manipulate the local conductivity at nanoscale, which is further visualized through a printed portrait encoded by local conductivity. Notably, multistate resistive switching is successfully demonstrated via successive set and reset processes. Our work highlights the probe-induced hydrogen evolution as a new direction to engineer memristor at nanoscale.

Deep ultraviolet (DUV) has a wide range of applications in areas such as the monitoring and communication fields. However, the separation of sensor units and memory units in conventional DUV photodetectors will increase costs and reduce processing speed. In this paper, we report the development of DUV photoelectric memristors fabricated using gallium oxide (Ga2O3) to emulate the photoelectric synaptic functions of bionic visual system. The devices showcase nonvolatile resistance switching behavior, effectively mimicking neuromorphic processes such as short-term plasticity and long-term plasticity in both singular and repeated cycles under optical pulse modulation. Moreover, the fabrication of a 5 × 5 array configuration allowed us to simulate the learning, memory formation, and forgetting process, along with the ability to store and erase the image information. This work not only broadens the application scope of Ga2O3 as an ultra-wide bandgap semiconductor but also offers insight into the development of integrated sensing-storage devices for artificial intelligence systems, paving the way for future advancements in neuromorphic engineering and bio-inspired computing systems.