activity
20182026
most citedBayesian Uncertainty Quantification in Inverse Modelling of Electrochemical Systems

20 citations · 25 across the 4 of their papers we have counts for

collaborators

4 papers

cond-mat.mtrl-sci2026

Unveiling the origin of the capacity fade in MnO zinc-ion battery cathodes through an analysis of the Mn vacancy formation

Caio M. Miliante, Kevin J. Sanders, Liam J. McGoldrick +5

Currently explored rechargeable aqueous zinc-ion battery (RAZIB) cathode materials, such as -MnO, suffer from severe capacity fade when cycling at rates appropriate for gr…

physics.chem-ph2024

Data-Driven Approach to Learning Optimal Forms of Constitutive Relations in Models Describing Lithium Plating in Battery Cells

Avesta Ahmadi, Kevin J. Sanders, Gillian R. Goward +1

In this study we construct a data-driven model describing Lithium plating in a battery cell, which is a key process contributing to degradation of such cells. Starting from the fun…

physics.chem-ph2023★ 5 cited

Learning Optimal Forms of Constitutive Relations Characterizing Ion Intercalation from Data in Mathematical Models of Lithium-ion Batteries

Lindsey Daniels, Smita Sahu, Kevin J. Sanders +3

Most mathematical models of the transport of charged species in battery electrodes require a constitutive relation describing intercalation of Lithium, which is a reversible proces…

physics.chem-ph2018★ 20 cited

Bayesian Uncertainty Quantification in Inverse Modelling of Electrochemical Systems

Athinthra Sethurajan, Sergey Krachkovskiy, Gillian Goward +1

This study proposes a novel approach to quantifying uncertainties of constitutive relations inferred from noisy experimental data using inverse modelling. We focus on electrochemic…