Bayesian uncertainty quantification in inverse modeling of electrochemical systems

This present study proposes a novel approach to quantifying uncertainties of constitutive relations inferred from noisy experimental data using inverse modeling. We focus on electrochemical systems in which charged species (e.g., Lithium ions) are transported in electrolyte solutions under an applied current. Such systems are typically described by the Planck‐Nernst equation in which the unknown material properties are the diffusion coefficient …