Dynamic resistance response modeling and simulation of major–minor hysteresis loops in VO2 using RK4 and LLP model for neuromorphic applications

This study presents a computational framework to simulate the dynamic resistance behavior of vanadium dioxide (VO2) under pulse-width modulation (PWM) voltage excitation. A central contribution of this study is the ability to model both major hysteresis loops, which correspond to complete phase transitions, and, importantly, minor hysteresis loops resulting from partial and cyclic thermal excitations, a phenomenon that remains largely unexplored in the literature. By integrating the Limiting Loop Proximity hysteresis model with a fourth-order Runge–Kutta solver, the approach accurately captures the history-dependent and directional behavior of VO2, dynamically tracking phase boundary evolution and reversal points with high numerical stability under rapid thermal fluctuations. Another key result is the demonstration that VO2 can sustain stable, persistent, and tunable resistive states under subthreshold PWM excitation, without requiring complete phase transitions. This behavior directly supports its application in non-volatile and multi-state memory devices, as well as neuromorphic computing architectures that leverage history-dependent plasticity. The PWM-driven voltage induces periodic thermal modulation in VO2, leading to reversible transitions between semiconducting and metallic states, governed by strong nonlinearity and hysteresis linked to thermal history. The model, calibrated against experimental data from thin (∼100 nm) VO2 films grown on semi-insulating substrates, employs smooth and adaptive voltage ramps during switching to realistically emulate thermal inertia, avoiding artificial discontinuities. These results advance the understanding of hysteretic behavior in VO2 under cyclic excitation and reinforce its potential for memristive devices, spiking neural networks, and energy-efficient in-memory computing.