Enhancing selectivity and sensitivity in gas sensors through noble metal-decorated ZnO and machine learning

Abstract

The growing need for highly sensitive and selective gas sensors has spurred extensive research on enhancing metal-oxide-semiconductor-based sensors. In this study, we explored the gas-sensing performance of ZnO thin films functionalized with noble metals (Ir, Ru, and IrRu alloys) via atomic layer deposition for the detection of hazardous gases. The incorporation of noble metals led to significant improvements in the gas-sensing behavior driven by both electronic and chemical sensitization mechanisms. To further enhance gas selectivity, machine learning-based data analysis was employed, enabling precise classification of various gases with 100 % accuracy. These findings underscore the potential of noble metal-functionalized ZnO sensors for advanced gas detection, illustrating the effective combination of material engineering and cutting-edge data analysis techniques for the development of intelligent, selective, and stable gas sensor platforms.