Austin Carlson / Mathematics / Faculty Mentor: Hristo Kojouharov
Polydiacetylene (PDA)-based spray-on sensors undergo distinct color transitions in response to ultraviolet (UV) exposure, which induces polymerization, and temperature increases, which disrupt backbone conjugation. To quantify these responses, we analyzed video data of sensor transitions, processing color changes in the CIE Lab color space. Curve fitting of individual color channels enabled accurate modeling of both polymerization and backbone disruption dynamics. To predict sensor behavior across varying concentrations, we further modeled how response parameters evolved with concentration. This revealed logarithmic and double-logarithmic trends for color change, with simple polynomial relationships describing parameter variation. The resulting models accurately predicted sensor responses under different conditions, providing a framework for designing tunable, concentration-dependent sensing systems. These findings enhance the reliability and applicability of PDA-based sensors for environmental monitoring and biomedical diagnostics.
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