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HydroHue: Passive Optical Mold-Risk Indicator Using Structural Color and Humidity-Responsive Hydrogels

CSEF · 2026 Environmental Engineering (Senior Division)

Andrew He

Overview

Mold exposure is a significant public health concern associated with asthma and allergic disease, particularly in low-income households and schools where moisture control is limited. Existing mold detection methods rely on chemical reagents, biological sampling, or powered sensors, which can be costly, hazardous, or inaccessible. This project presents HydroHue, a low-cost, passive, and chemical-free optical patch designed to visually indicate environmental conditions associated with elevated mold-growth risk. HydroHue functions by monitoring prolonged high relative humidity, a primary environmental factor correlated with mold development. The device consists of a biocompatible, humidity-responsive hydrogel layered onto a micro-structured substrate that produces color through structural light interference rather than pigments or dyes. As ambient humidity increases, the hydrogel absorbs moisture and swells, altering the microstructure spacing and producing a measurable shift in reflected color. This color change provides an intuitive, real-time visual indicator without electronics, reagents, or biological agents. Patches were fabricated using food-safe polymer hydrogels cast onto micro-patterned substrates and exposed to controlled relative humidity levels ranging from approximately 30% to 90% for 24–72 hours. Color changes were documented using a smartphone camera and analyzed quantitatively through RGB and HSV color space extraction. Swelling ratios, response times, reversibility, and reproducibility were evaluated across multiple trials. Results demonstrated consistent, reversible color shifts proportional to humidity level and exposure duration, with stable performance across repeated humidification cycles. HydroHue integrates principles of biomedical materials science, optical physics, and environmental health to create a safe, scalable early-warning system for mold-risk environments, particularly suited for resource-limited settings.

Competition history

  • CSEF 2026 Environmental Engineering (Senior Division) · Entry S-11-05

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