Frontiers in gas sensing with semiconducting metal oxide array electronic noses

Abstract

The growing demand for rapid and selective detection of hazardous gases drives the development of electronic nose (e-nose) systems. By combining partially selective sensor arrays with pattern recognition algorithms, e-noses effectively identify and quantify complex gas mixtures. Semiconducting metal oxides (SMO_x) are widely used due to their high sensitivity, fast response, and cost-effectiveness. This review highlights recent advances in SMO_x-based e-noses for detecting formaldehyde, ammonia, NO_x, etc., focusing on innovative material strategies such as micro-nano engineering, noble metal modification, rare-earth doping, μLED photoactivation, and rGO composites. Advanced machine learning, particularly deep learning, significantly enhances selectivity and prediction accuracy. Future efforts will focus on miniaturization, energy efficiency, and intelligent system development.