With the escalating demand for rapid and high-performance monitoring of toxic and hazardous gases in environmental and industrial settings, zinc oxide (ZnO) nanostructures have emerged as a prominent candidate for gas sensing. However, the sensing performance of metal oxide semiconductors in complex environments is subject to the synergistic interference of diverse variables. In this study, we propose a comprehensive multi-physics theoretical framework to systematically simulate and evaluate the sensing performance of ZnO-based sensors toward nitrogen dioxide (NO₂). Unlike traditional empirical models, this work couples multiple physical-chemical processes by solving a set of differential equations using the ODE45 numerical algorithm in MATLAB. The computational model integrates surface adsorption- desorption kinetics based on competitive Langmuir theory, Arrhenius temperature dependencies, charge transfer mechanisms that map surface coverage to electrical resistance, and a wavelength-dependent Gaussian photo-excitation model.

By quantitatively analyzing the sensor’s response under different environmental parameters, several critical physical insights are revealed as follows: 1) Selectivity and concentration-dependent kinetics: The sensor demonstrates exceptional selectivity to NO₂ (yielding a 594% resistance change rate at 10 ppm) driven by its high electron affinity. Evaluated over an ultra-wide dynamic range (10 ppb to 200 ppm), the response time exhibits a profound concentration dependence, drastically decreasing from ~430 s at 200 ppb to ~3 s at 200 ppm. This exponential decay reflects a kinetic transition from a "diffusion-collision limited" regime to a “surface site saturation limited” regime. 2) Thermo-optic synergistic tuning: The optimal operating temperature is identified between 200 and 300 ℃, which balances the thermal activation barrier for adsorption (E_a = 30 kJ/mol) and the accelerated desorption rate (E_d = 40 kJ/mol). Furthermore, the introduction of UV illumination at 375 nm (matching the ~3.2 eV bandgap of ZnO) maximizes the quantum efficiency. Increasing the light intensity (up to 1200 W/m²) significantly enhances the response amplitude and shortens the response time through the generation of photo-induced carriers and secondary defect-assisted photothermal effects. 3) Moisture-induced "saturation paradox": The model successfully quantifies the severe degradation of sensitivity under high humidity conditions (e.g., the response rate drops to ~4% at 40% RH) due to the competitive dissociation of water molecules on the ZnO surface. Notably, it elucidates a counter-intuitive dynamic phenomenon where the response time dramatically shortens as relative humidity increases. This is physically interpreted as a severe reduction in available adsorption capacity caused by the “site-blocking effect,” allowing the system to reach its new, albeit lower, equilibrium state much faster (pseudo-acceleration).

Finally, the reliability of the proposed multi-physics model is validated against classical experimental data, achieving a high goodness-of-fit (R² > 0.95) and accurately predicting key characteristic parameters (e.g., optimal wavelength and temperature). This research bridges the gap between theoretical gas-sensing kinetics and complex experimental phenomena, providing a robust quantitative foundation for the optimization and design of light-activated, interference-resistant ZnO gas sensors for future environmental monitoring and health diagnostics.