arXiv subjects

Jon Chapman

Publications and source records attributed to Jon Chapman.

6 recordsLinked to original sources

arXiv2026

Battery open-circuit voltage is not purely chemical

Open-circuit-voltage (OCV) curves are commonly treated as intrinsic chemical properties of electrode materials. However, this view is incomplete. In ion-insertion batteries, OCV also depends on mechanical state and microstructure. Using finite-element simulations and asymptotic analysis, we show that particle swelling and external loads promote particle--particle contact that generates compressive stresses, shifting the inserted-ion chemical potential. The OCV correction is nonlinear, follows Hertzian contact scaling, and depends on particle arrangement. Identical materials can therefore exhibit different OCV curves in different electrode microstructures. Furthermore, in full cells, electrodes are mechanically coupled through the common stack stress. Thus, cell OCV is a chemo-mechanical property of the entire battery architecture, not chemistry alone.

cond-mat.mtrl-sci↗

arXiv2026

Incorporating multiscale mechanics in lithium-ion battery models

Lithiation-induced swelling in lithium-ion batteries generates stresses not only within active particles, but also across the surrounding non-active matrix, electrodes, and cell stack. These stresses can modify the chemical potential of lithium and therefore influence transport, reaction kinetics, and terminal voltage. We derive a reduced-order electro-chemo-mechanical model that captures this multiscale coupling while retaining a complexity comparable to standard Doyle--Fuller--Newman models. The electrode is modelled as a periodic array of spherical active particles embedded in a homogenised elastic non-active matrix. Exploiting the small stiffness of the non-active matrix relative to the active material, together with scale separation between particles, electrodes, and the full cell, we obtain an effective mechanical correction to the active-particle chemical potential and overpotential. This correction depends on particle swelling, electrode-scale strain, and macroscopic boundary conditions such as clamping or applied pressure. The resulting formulation can be incorporated directly into DFN, SPMe, and SPM frameworks, providing a computationally efficient route to include battery-scale mechanical effects in electrochemical simulations.

physics.chem-ph↗

arXiv2025

SGL: A Structured Graphics Language

This paper introduces SGL, a graphics language that is aesthetically similar to SQL. As a graphical counterpart to SQL, SGL enables specification of statistical graphics within SQL query interfaces. SGL is based on a grammar of graphics that has been customized to support a SQL aesthetic. This paper presents the fundamental components of the SGL language alongside examples, and describes SGL's underlying grammar of graphics via comparison to its closest predecessor, the layered grammar of graphics.

cs.PL↗

arXiv2024

Gas-induced bulging in pouch-cell batteries: a mechanical model

Over the long timescale of many charge/discharge cycles, gas formation can result in large bulging deformations of a Lithium-ion pouch cell, which is a key failure mechanism in batteries. Guided by recent experimental X-ray tomography data of a bulging cell, we propose a homogenised mechanical model to predict the shape of the deformation and the stress distribution analytically. Our model can be included in battery simulation models to capture the effects of mechanical degradation. Furthermore, with knowledge of the bending stiffness of the cathode electrodes and current collectors, and by fitting our model to experimental data, we can predict the internal pressure and the amount of gas in the battery, thus assisting in monitoring the state of health (SOH) of the cell without breaking the sealed case.

cond-mat.soft↗

arXiv2024

Mechanical stresses in pouch cells: a reduced order model

In a pouch cell battery, the intercalation of lithium ions into the active particles means the electrodes want to expand. However, since the electrodes are attached to stiff current collectors, this expansion is constrained, leading to a macro-scale deformation and a residually stressed state. This stress state affects the electrochemistry and can also lead to mechanical degradation, causing a reduction in performance. We model the mechanical state of stress in the battery assuming a known compositional expansion of the electrodes, and use asymptotic techniques to generate reduced order models by exploiting the thin aspect ratio, as well as the large stiffness of the current collectors. We obtain analytic expressions for the stress in the bulk of the electrodes and at the interface between electrodes and current collectors, and a reduced-order equation whose solution describes the tension in the current collectors. We compare our results with full 3D finite element simulations with excellent agreement, and use our results with the battery simulation package PyBaMM to predict a realistic stress state in a discharging battery.

physics.app-ph↗

arXiv2013

Metastable behavior in Markov processes with internal states

A perturbation framework is developed to analyze metastable behavior in stochastic processes with random internal and external states. The process is assumed to be under weak noise conditions, and the case where the deterministic limit is bistable is considered. A general analytical approximation is derived for the stationary probability density and the mean switching time between metastable states, which includes the pre exponential factor. The results are illustrated with a model of gene expression that displays bistable switching. In this model, the external state represents the number of protein molecules produced by a hypothetical gene. Once produced, a protein is eventually degraded. The internal state represents the activated or unactivated state of the gene; in the activated state the gene produces protein more rapidly than the unactivated state. The gene is activated by a dimer of the protein it produces so that the activation rate depends on the current protein level. This is a well studied model, and several model reductions and diffusion approximation methods are available to analyze its behavior. However, it is unclear if these methods accurately approximate long-time metastable behavior (i.e., mean switching time between metastable states of the bistable system). Diffusion approximations are generally known to fail in this regard.

math.AP↗