Electrochemical inference of reduced thermodynamic descriptors for electrolyte non-ideality

Electrochemical measurements in concentrated electrolytes are intrinsically sensitive to non-ideal chemical potentials, yet they are commonly interpreted using assumed activity models rather than exploited as thermodynamic constraints. In this work, we introduce an inverse electrochemical framework in which macroscopic electrical observables are used to infer a reduced set of thermodynamic descriptors governing electrolyte non-ideality. Using the open-circuit response of a reverse electrodialysis (RED) stack, the deviation from ideal-solution behavior is related to the ratio of mean ionic activity coefficients between concentrated and dilute streams. Instead of attempting full multi-ion compositional inversion, which is generally underdetermined, the electrolyte is parameterized by a reduced thermodynamic descriptor vector capturing the dominant effects of multivalent ions and specific short-range interactions within a Pitzer-consistent structure. The descriptors are identified by minimizing the mismatch between the activity-coefficient ratio implied by the electrochemical response and that predicted by the thermodynamic model. This formulation reframes RED observables as constraints on effective interaction descriptors that shape non-ideal chemical potentials, enabling thermodynamically interpretable inference from electrical measurements without full electrolyte speciation.

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