Polythioctic acid-driven biomemristor for efficient sweat pH monitoring

Memristors have attracted widespread attention in the fields of brain-like chips and neuromorphic computing due to their parallel computing capabilities and characteristics to simulate neural synapses. However, the application of memristor in healthcare monitoring and diagnosis has not yet been well developed, which may delay the progress of smart healthcare services empowered by artificial intelligence (AI). Herein, it was demonstrated a pH-responsive memristor with an Ag/Poly(diethylene glycol ester thioctic acid)-Li/FTO structure, which shows excellent resistance switching behaviors with self-rectifying characteristics. Further, it was found the device can achieve precise acid-base discrimination through synergistic mechanisms involving the cationic conduction properties of the C-S bond in Poly(diethylene glycol ester thioctic acid) and the uniqueness of the metal-oxygen coordination bond. Accurate solution pH determination can be accomplished within 3 min via analysis of the time-dependent ΔI F-R parameter, defined as the different between forward peak and reverse currents. Finally, the device was successfully applied to determine sweat pH levels, demonstrating the potential of the pH-responsive memristor in monitoring health status through sweat. Therefore, this work provides new insights for non-invasive preliminary diagnosis and early warning of metabolic diseases such as diabetes, which effectively promotes the rapid development of smart wearable medical devices.