Electrochemical multi-analyte point-of-care perspiration sensors using on-chip three-dimensional graphene electrodes

Abstract

AbstractMulti-analyte sensing using exclusively laser-induced graphene (LIG)-based planar electrode systems was developed for sweat analysis. LIG provides 3D structures of graphene, can be manufactured easier than any other carbon electrode also on large scale, and in form of electrodes: hence, it is predestinated for affordable, wearable point-of-care sensors. Here, it is demonstrated that LIG facilitates all three electrochemical sensing strategies (voltammetry, potentiometry, impedance) in a multi-analyte system for sweat analysis. A potentiometric potassium-ion-selective electrode in combination with an electrodeposited Ag/AgCl reference electrode (RE) enabled the detection of potassium ions in the entire physiologically relevant range (1 to 500 mM) with a fast response time, unaffected by the presence of main interfering ions and sweat-collecting materials. A kidney-shaped interdigitated LIG electrode enabled the determination of the overall electrolyte concentration by electrochemical impedance spectroscopy at a fixed frequency. Enzyme-based strategies with amperometric detection share a common RE and were realized with Prussian blue as electron mediator and biocompatible chitosan for enzyme immobilization and protection of the electrode. Using glucose and lactate oxidases, lower limits of detection of 13.7 ± 0.5 μM for glucose and 28 ± 3 μM for lactate were obtained, respectively. The sensor showed a good performance at different pH, with sweat-collecting tissues, on a model skin system and furthermore in synthetic sweat as well as in artificial tear fluid. Response time for each analytical cycle totals 75 s, and hence allows a quasi-continuous and simultaneous monitoring of all analytes. This multi-analyte all-LIG system is therefore a practical, versatile, and most simple strategy for point-of-care applications and has the potential to outcompete standard screen-printed electrodes.