Abstract
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 bacteriaderived
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.
