A novel bubble rupture sensing methodology for sweat-driven disease diagnostics.

Sweat is a rich biofluid whose composition depends heavily on physiology and varies systematically across a range of systemic and dermatological conditions, making it an attractive medium for non-invasive diagnostics. However, existing diagnostic tools, which rely primarily on electrochemical ion-selective electrodes and optical microfluidic systems, require complex instrumentation and have significant limitations in ease of application and deployment. This poses a need for a low-cost, simple sensing approach using sweat as a sample for disease detection. Here we demonstrate a novel bubble sensing methodology that exploits the relationship between bubble film stability and electrolyte concentration in a reagent-free setup requiring no electrochemical transduction. A controlled-volume bubble was made using a sodium dodecyl sulphate-glycerol solution, which was then tested by adding potassium chloride (KCl) solutions at concentrations of 0.01-0.15 mol L-1, simulating sweat at variable ionic strengths. Two characteristic timescales were identified: the time to burst (tb), measured by the naked eye on a seconds timescale, and the film retraction time (τ), resolved at 100 000 frames per second using a high-speed camera. The time to burst exhibited a strong exponential decay with increasing KCl concentration (R2 = 0.934), with greatest sensitivity in the healthy resting sweat range (0.01-0.1 mol L-1) and a plateau at pathological concentrations above 0.1 mol L-1. High-speed imaging revealed distinct changes in rupture initiation location and film retraction behaviour upon analyte addition, with retraction time increasing from 250 µs in control bubbles to ∼1.5 ms. The observed trend was quantitatively reproduced using a coupled DLVO-Kramers nucleation model, identifying electrostatic double-layer screening as the primary mechanism driving faster rupture at higher ionic strength. This work establishes the proof of concept for bubble rupture dynamics as a functional sensing mechanism and provides the basis for further development of surfactant bubble-based biosensors.