A Highly Stable Electrochemical Sensor Based on a Metal-Organic Framework/Reduced Graphene Oxide Composite for Monitoring the Ammonium in Sweat.

The demand for non-invasive, real-time health monitoring has driven advancements in wearable sensors for tracking biomarkers in sweat. Ammonium ions (NH) in sweat serve as indicators of metabolic function, muscle fatigue, and kidney health. Although current ion-selective all-solid-state printed sensors based on nanocomposites typically exhibit good sensitivity (~50 mV/log [NH]), low detection limits (LOD ranging from 10 to 10 M), and wide linearity ranges (from 10 to 10 M), few have reported the stability test results necessary for their integration into commercial products for future practical applications. This study presents a highly stable, wearable electrochemical sensor based on a composite of metal-organic frameworks (MOFs) and reduced graphene oxide (rGO) for monitoring NH in sweat. The synergistic properties of Ni-based MOFs and rGO enhance the sensor's electrochemical performance by improving charge transfer rates and expanding the electroactive surface area. The MOF/rGO sensor demonstrates high sensitivity, with a Nernstian response of 59.2 ± 1.5 mV/log [NH], an LOD of 10 M, and a linearity range of 10 to 10 M. Additionally, the hydrophobic nature of the MOF/rGO composite prevents water layer formation at the sensing interface, thereby enhancing long-term stability, while its high double-layer capacitance minimizes potential drift (7.2 µV/s (i = ±1 nA)) in short-term measurements. Extensive testing verified the sensor's exceptional stability, maintaining consistent performance and stable responses across varying NH concentrations over 7 days under ambient conditions. On-body tests further confirmed the sensor's suitability for the continuous monitoring of NH levels during physical activities. Further investigations are required to fully elucidate the impact of interference from other sweat components (such as K, Na, Ca, etc.) and the influence of environmental factors (including the subject's physical activity, posture, etc.). With a clearer understanding of these factors, the sensor has the potential to emerge as a promising tool for wearable health monitoring applications.