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Kevin J. Sanders

Publications and source records attributed to Kevin J. Sanders.

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Unveiling the origin of the capacity fade in MnO$_{2}$ zinc-ion battery cathodes through an analysis of the Mn vacancy formation

Currently explored rechargeable aqueous zinc-ion battery (RAZIB) cathode materials, such as $\alpha$-MnO$_{2}$, suffer from severe capacity fade when cycling at rates appropriate for grid-scale operation. Mn dissolution has been previously identified as the cause of $\alpha$-MnO$_{2}$ cathode degradation during RAZIB cycling, with conflicting evidence being found in support of the proposed Jahn-Teller effect-assisted charge disproportionation reaction as the mechanism behind Mn dissolution. In order to unveil the Mn dissolution mechanism in MnO$_{2}$ cathode cells under RAZIB operation conditions, the energetic feasibility for Mn vacancy formation was probed in both charged (MnO$_{2}$) and discharged (ZnMn$_{2}$O$_{4}$) phases of $\alpha$ and $\lambda$ polymorphs of MnO$_{2}$ using density functional theory. The formation of a Mn vacancy, and consequently the dissolution of Mn as Mn$^{2+}_{(aq)}$, was found to be thermodynamically feasible for the $\alpha$-ZnMn$_{2}$O$_{4}$ phase due to the energetically unfavourable Zn bent coordination formed during the Zn$^{2+}$ intercalation process, indicating that Mn dissolution is promoted by an unstable Zn coordination environment. The theoretical calculations were then corroborated by operando $^{1}$H nuclear magnetic resonance experiments which captured the Mn dissolution occurring throughout the RAZIB discharge, with subsequent electrochemical deposition of the Mn atoms on the electrode during charge. The combined computational and experimental analysis reveals the critical role of defect energetics and coordination environment in driving active material dissolution, and consequently capacity fade, with the proposed mechanism also relevant for understanding cathode degradation in other intercalating ion battery chemistries.

cond-mat.mtrl-sci

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

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 fundamental Doyle-Fuller-Newman (DFN) model, we use asymptotic reduction and spatial averaging techniques to derive a simplified representation to track the temporal evolution of two key concentrations in the system, namely, the total intercalated Lithium on the negative electrode particles and total plated Lithium. This model depends on an a priori unknown constitutive relations of the cell as a function of thestate variables. An optimal form of this constitutive relation is then deduced from experimental measurements of the time dependent concentrations of different Lithium phases acquired through Nuclear Magnetic Resonance spectroscopy. This is done by solving an inverse problem in which this constitutive relation is found subject to minimum assumptions as a minimizer of a suitable constrained optimization problem where the discrepancy between the model predictions and experimental data is minimized. This optimization problem is solved using a state-of-the-art adjoint-based technique. In contrast to some of the earlier approaches to modelling Lithium plating, the proposed model is able to predict non-trivial evolution of the concentrations in the relaxation regime when no current isapplied to the cell. When equipped with an optimal constitutive relation, the model provides accurate predictions of the time evolution of both intercalated and plated Lithium across a wide range of charging/discharging rates. It can therefore serve as a useful tool for prediction and control of degradation mechanism in battery cells.

physics.chem-ph

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

Most mathematical models of the transport of charged species in battery electrodes require a constitutive relation describing intercalation of Lithium, which is a reversible process taking place on the interface between the electrolyte and active particle. The most commonly used model is the Butler-Volmer relation, which gives the current density as a product of two expressions: one, the exchange current, depends on Lithium concentration only whereas the other expression depends on both Lithium concentration and on the overpotential. We consider an inverse problem where an optimal form of the exchange current density is inferred, subject to minimum assumptions, from experimental voltage curves. This inverse problem is recast as an optimization problem in which the least-squares error functional is minimized with a suitable Sobolev gradient approach. The proposed method is thoroughly validated and we also quantify the reconstruction uncertainty. Finally, we identify the universal features in the constitutive relations inferred from data obtained during charging and discharging at different C-rates and discuss how these features differ from the behaviour predicted by the standard Butler-Volmer relation. We also identify possible limitations of the proposed approach, mostly related to uncertainties inherent in the material properties assumed known in the inverse problem. Our approach can be used to systematically improve the accuracy of mathematical models employed to describe Li-ion batteries as well as other systems relying on the Butler-Volmer relation.

physics.chem-ph