Application of Raman Spectroscopy for the Simultaneous Estimation of pH and Sulfate Concentrations in Highly Concentrated Sulfuric Acid

Herein contains a preliminary study with the goal of measuring pH and sulfate concentration of sulfuric acid electrolyte in situ, of a lead-acid battery. A series of solutions with varying pH and sulfate concentration were analysed using Raman spectroscopy. A model based on principal component analysis (PCA) and an artificial neural network (ANN) was trained to accurately predict the concentration and pH of these solutions. A custom-designed lead-acid battery was created to facilitate Raman microscopic measurements of the electrolyte adjacent to the electrode during operation. These measurements were processed based on a trained PCA-ANN model. The results demonstrate the effectiveness of this approach to estimate both the pH and sulfate concentration in the solution adjacent to the electrode interface. Based on the obtained outcomes, application of this method to the interior of a negative porous electrode should be able to independently estimate the pH and sulfate ion concentrations that can become decoupled during battery cycling.