Adlayer chemistry has been a significant subject of interest in physical chemistry over the past decades. Considerable attention has been paid to the development of high-performance film-based gas sensors, and tremendous progress has been achieved. Among the different analytical techniques, fluorescence provides a highly sensitive and selective method for detecting a wide variety of analytes. Film-based fluorescent sensors have emerged as one of the most promising candidates for chemical sensing and are being further developed into portable devices. Theoretically, relative signal changes including static and dynamic characteristics are significantly used to determine the sensing process; these characteristics are associated with surface absorption, the interaction between the analytes and sensing adlayer, as well as desorption kinetics in the absence and presence of the targeted gaseous analytes. As revealed earlier, there are a number of factors that determine the sensing behavior of a film, and the most important factors have been identified. Firstly, the suitability of the employed sensing fluorophore, which is important as it ultimately determines the effectiveness of a sensing process. Secondly, the structure of the fluorescent adlayer of the film; this is another important factor as it significantly determines the efficiency of mass transfer, which is necessary for efficient and reversible sensing. Finally, the chemical nature and surface structure of the substrate as these could affect the sensing performance of the film via the screening or enriching of analyte molecules. However, in situ, online, fast, and sensitive detection and discrimination of toxic and hazardous species via vapor sampling is a challenge that will persist for many years. By using the simultaneous interaction of multiple analytes with different sensing materials, the sensor array-based approach can recognize the overall change in the composition of complex mixtures, rather than just identifying their specific elements. The data-rich outputs of array-based sensing methods have recently been widely adopted by the analytical community due to their improved capabilities with statistical and cheminformatic approaches during analysis. Moreover, the community has recognized that numerous complex sensing challenges cannot be solved with conventional analytical tools.
