Self-Powered Wearable Sweat Monitoring using 2D WS2 Textile Integrated Triboelectric Nanogenerators for Future Personalized Healthcare

Abstract

The growing global burden of chronic diseases such as diabetes, cardiovascular disorders, and neurological conditions highlight the urgent need for continuous, non-invasive health monitoring solutions. Sweat-based sensing has emerged as a promising alternative to traditional diagnostic approaches, offering a rich source of biomarkers including electrolytes, metabolites, and stress-related molecules such as cortisol. However, conventional laboratory-based methods are unsuitable for real-time monitoring, prompting the development of wearable biosensors. This PhD thesis explores a novel class of self-powered wearable biosensors using two-dimensional tungsten disulfide (2D WS2) integrated into textile-based self-powered triboelectric nanogenerators (TENGs) devices. The research introduces a novel fabrication approach for creating selfpowered biosensors by integrating 2D WS2 into textile substrates. 2D WS2 was produced via liquid-phase exfoliation and deposited onto fabrics using three methods: ultrasonic spray coating, drop casting, and immersion. Among these, spray coating emerged as the optimal technique due to its superior film uniformity, reproducibility, and mechanical robustness under flexural strain. This approach enabled the creation of TENGs tailored for sweat sensing applications while preserving the textile’s flexibility and wearability. The concept of "electronic dyeing" was also introduced, wherein 2D WS2 imparts functional electronic characteristics to textiles in a similar manner to how traditional dyes impart colour, allowing scalable integration of sensing functionalities directly onto wearable fabrics. The 2D WS2-coated textiles were first evaluated for sweat sensing performance using phosphate-buffered saline (PBS) to simulate physiological sweat conditions. Devices were subjected to triboelectric testing under varying humidity conditions and volumes of PBS to assess stability, output consistency, and the impact of fluid exposure. The results revealed that polyester fabrics coated with 2D WS2 and paired with polyethylene terephthalate (PET) as the counter layer showed the most stable and reproducible performance. Building upon the successful platform for model sweat sensing, the research progressed to selectively detect uric acid, a key biomarker of metabolic function and oxidative stress, using 2D WS2 -based TENGs. Uric acid concentrations ranging from 10 µM to 20 mM were tested, encompassing both physiologically normal and pathologically elevated levels. The biosensor, composed of a 2D WS2-coated textile paired with a PET counter layer, demonstrated consistent, linear changes in triboelectric outputs including opencircuit voltage, short-circuit current, and transferred charge across this range. This work marks the first demonstration of a textile-based, energy-autonomous device capable of detecting uric acid without requiring external power, offering a low-maintenance, wearable solution for real-time metabolic health monitoring. The final phase of the work addressed the detection of cortisol, a critical biomarker for stress and fatigue. The biosensor was tested across cortisol concentrations from 100 ng/mL to 1 mg/mL, capturing both normal and elevated physiological levels. Output signals were recorded under controlled mechanical actuation and simulated biomechanical motion to reflect realistic use scenarios. The device demonstrated a peak response at 200 ng/mL, consistent with typical human stress-induced cortisol levels, and maintained reliable performance even at ultra-high concentrations. Collectively, these findings establish a robust, wearable platform capable of detecting multiple sweat biomarkers through scalable fabrication and selfpowered operation, aligning with the future vision of personalized, preventive healthcare.