摘要：We demonstrate that UV-light activation of polycrystalline ZnO films on flexible polyimide (Kapton) substrates can be used to detect and differentiate between environmental changes in oxygen and water vapor. The in-plane resistive and impedance properties of ZnO films, fabricated from bacteria-derived ZnS nanoparticles, exhibit unique resistive and capacitive responses to changes in O2 and H2O. We propose that the distinctive responses to O2 and H2O adsorption on ZnO could be utilized to statistically discriminate between the two analytes. Molecular dynamic simulations (MD) of O2 and H2O adsorption energy on ZnO surfaces were performed using the large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) with a reactive force-field (ReaxFF). These simulations suggest that the adsorption mechanisms differ for O2 and H2O adsorption on ZnO, and are governed by the surface termination and the extent of surface hydroxylation. Electrical response measurements, using DC resistance, AC impedance spectroscopy, and Kelvin Probe Force Microscopy (KPFM), demonstrate differences in response to O2 and H2O, confirming that different adsorption mechanisms are involved. Statistical and machine learning approaches were applied to demonstrate that by integrating the electrical and kinetic responses the flexible ZnO sensor can be used for detection and discrimination between O2 and H2O at low temperature.
