A New Method for Quantitation of Cyanuric Acid in Water Based on Image Analysis of Drying Patterns Using Computer Vision

Neta Caspin, Schulich Faculty of Chemistry, Technion – Israel Institute of Technology, Haifa , Israel (lili@bioforum.co.il)
Olga Mindlina, Schulich Faculty Of Chemistry, Technion – Israel Institute Of Technology, Haifa , Israel
Sharon Uriah-Hellay , Schulich Faculty Of Chemistry, Technion – Israel Institute Of Technology, Haifa , Israel
Vladimir V. Gridin, Schulich Faculty Of Chemistry, Technion – Israel Institute Of Technology, Haifa , Israel
Maor Manevich , Schulich Faculty Of Chemistry, Technion – Israel Institute Of Technology, Haifa , Israel
Israel Schechter, Schulich Faculty Of Chemistry, Technion – Israel Institute Of Technology, Haifa , Israel

We present a simple, reagent-free method to quantify cyanuric acid (CYA) in tap water by analyzing the drying patterns of CYA solution droplets. The analytical signature is a set of white dendritic columns that grow radially from the droplet perimeter toward the center, a pattern not observed for other common dissolved organic compounds in tap water. Patterns were recorded with a basic optical camera under dark-field illumination, and their morphology varied systematically with CYA concentration. The deposits consist mainly of CYA together with ions naturally present in tap water. Using a deep learning model with data augmentation and statistical analysis, we achieved accurate quantification over 0–120 ppm. The method performs best under neutral to slightly acidic conditions and is compatible with free-chlorine levels used in swimming pools, which makes it directly applicable to pool monitoring. To our knowledge, this is the first demonstration of drying-pattern analysis for quantitation of an analyte in a complex mixture. The approach is low cost and requires only imaging and data analysis, although it does require waiting for droplet drying.