Next-Generation Phosgene Detection: Convolutional Neural Network with Triphenylamine and N-Salicylaldehyde Probes for Enhanced Sensitivity and Bioimaging

Phosgene is a highly toxic gas that is widely used in various industries, making its rapid detection essential for safety. To address this need, we developed a smartphone-based technique using convolutional neural networks (CNNs) for real-time, portable phosgene detection. Unlike traditional fluorescence spectroscopy, which requires specialized equipment and expertise, this CNN-based approach is accessible and affordable and offers quick analysis, making it ideal for on-the-spot detection. We employed this method to identify phosgene toxicity in solutions ranging from 0 to 10 ppm by analyzing images of the solutions. Specifically, we used intramolecular charge transfer (ICT)-based TPAOD and SAHY probes to detect phosgene through turn-off and turn-on fluorescence, with detection limits of 19.44 nM (0.00759 ppm) and 34.89 nM (0.00817 ppm), respectively. A lifetime study of TPAOD confirmed that the quenching mechanism operates through static quenching. The SAHY probe was utilized for the CNN model and was also tested for cell imaging studies in HeLa cells.