Spectral modeling for accelerated pH spectroscopy using EPR

A data modeling and processing method for electron paramagnetic resonance (EPR)-based pH spectroscopy is presented. The proposed method models the EPR spectrum of a pH-sensitive probe in both protonated and unprotonated forms. Under slow-exchange conditions, the EPR spectrum of a sample with an unknown pH value can be accurately represented by a weighted sum of the two models, with the pH value completely determined by their relative weights. Unlike traditional pH spectroscopy, which relies on locating resonance peaks, the proposed modeling-based approach utilizes the information from the entire scan and hence leads to more accurate estimation of pH for a given acquisition time. By employing the proposed methodology, we expect a reduction in the pH estimation error by more than a factor of three, which represents an order of magnitude reduction in acquisition time compared to the traditional method.