Sulfur/oxygen vacancy synergistic engineering in MoS₂-based neuromorphic devices

Two-dimensional materials, especially transition metal dichalcogenides like MoS₂, show great promise for neuromorphic computing due to their highly tunable electronic properties. However, the role of defects such as sulfur vacancies (V_S), oxygen vacancies (V_O), and other in-plane defects in device operation mechanisms remains poorly understood, limiting performance and integration potential. In this work, we leverage a competitive-synergistic model of these defects to modulate resistive switching modes in MoS₂-based neuromorphic devices, transitioning from filamentary non-volatile to interface-dominated volatile and hybrid regimes. Our interface-type devices demonstrate exceptional endurance (> 10⁵ pulses) and large synaptic weight modulation range up to > 10³, while hybrid-type devices achieve stable multilevel states with a low variation of each state down to 10⁻⁴). The transition of switching mechanism is attributed to the relative concentration of defects in MoS₂ through defect engineering protocol, which changes the dominant type of vacancy for migration. More importantly, we integrate volatile and non-volatile MoS₂ devices into a spike-response model circuit that emulates different stimulation modes and more advanced neuronal functions. This work establishes a defect engineering strategy for designing both high-performance neuromorphic and memory devices, enabling homogeneous integration for complex neural network applications.