Continuous Monitoring of Lithium Ions in Lithium-Rich Brine Using Ion Selective Electrode Sensors Modified with Polyelectrolyte Multilayers of Poly(allylamine hydrochloride)/Poly(sodium 4-styrenesulfonate)

Abstract

Monitoring lithium ions (Li + ) in lithium-rich brine (LrB) is critical for metal recovery, yet challenges such as high ionic strength and gypsum-induced surface deterioration hinder the performance of potentiometric ion-selective electrode (ISE) sensors. This study advances the functionality of Li + ISE sensors and enables continuous monitoring of Li + concentration in LrB by introducing apolyelectrolyte multilayer (PEM) of poly(allylamine hydrochloride)/poly(sodium 4-styrenesulfonate) (PAH/PSS) that serves as an antigypsum scaling material to minimize nucleation on the sensor surface. With 5.5 bilayers of PAH/PSS coating, the Li + ISE sensors possess a high Nernst slope (59.14 mV/dec), rapid response (<10 s), and superior selectivity against competitive ions (Na + , log K s = −2.35; K + , log K s = −2.47; Ca 2+ , log K s = −4.05; Mg 2+ , log K s = −4.18). The impedance (85.1 kΩ) of (PAH/PSS) 5.5 -coated sensors is 1 order of magnitude lower than that of electrospray ion-selective membrane (E-ISM) Li + sensors (830 kΩ), attributed to the ultrathin (45.3 nm) and highly dielectric PAH/PSS bilayers. During a 15-day continuous monitoring test in LrB, the (PAH/PSS) 5.5 -coated Li + ISE sensors with their superhydrophilic and smooth surface diminish nucleation sites for scaling agents (e.g., Ca 2+ and SO 4 2− ) and consequently mitigate gypsum scaling. Moreover, a brine-tailored denoising data processing algorithm (bt-DDPA), coupled with the salinity-adjusted mathematical model with Lagrange interpolation, effectively captures Li + fluctuation by filtering out anomalies and reducing sensor drift in brine. Bt-DDPA alleviates the discrepancy between the sensor readings and the lab-based validation results by 46.06%. This study demonstrates that the integration of material advancement (PAH/PSS coating) with sensor data processing (bt-DDPA) bolsters continuous and accurate Li + monitoring in LrB, crucial for brine water treatment and resource recovery.