Photonic Olfactory Sensors Enabling Efficient Recognition of Volatile Industrial Fragrances

Abstract The accurate recognition of volatile industrial fragrances, which are widely used in the food, chemical, and cosmetic industries, is crucial for product formulation and safety assurance. However, precisely identifying diverse odors still poses a significant challenge, falling short of replicating or surpassing human olfactory capabilities. Here an optical Tb‐based metal‐organic framework (TM) olfactory sensor is proposed using a one‐step synthetic hydrothermal method to perceive and classify floral scents among oily, sour, malodorous, peach‐like, grassy and orange scents. The demonstrated TM olfactory sensor is of high sensitivity and selectivity (classification accuracy rate 95.7%), exhibiting a strong linear response (R 2 = 0.999), and a low limit of detection (≈4.497 ppm). The density functional theory (DFT) calculations revealed that the hydroxyl groups of the selected floral scents reduced the adsorption energy and band gap of TMs, thereby promoting intramolecular charge transfer and triggering the fluorescence “turn‐on” effect. Furthermore, the corresponding portable odor perception optical system is designed for real‐time perception of floral scents. The system enables data transmission via Bluetooth or Wi‐Fi to a mobile app to achieve a response time of 3.9 s, which demonstrated its great potential for the construction of an artificial intelligence photonic nose system in industrial fragrance detection.