arXiv subjects

Giles Richardson

Publications and source records attributed to Giles Richardson.

7 recordsLinked to original sources

arXiv2026

Analysis of degradation in perovskite solar cells through physics-based machine learning

Degradation in lead halide perovskite solar cells is analysed by inverse modelling of published measurements of characteristics of a single solar cell at ages 0, 90, 280, 480 minutes. We employ machine learning to deduce distributions of material parameter values and hence the physics linked to measured changes. Bayesian parameter estimation is coupled with drift diffusion simulations using the IonMonger code combined with an optical model. We accurately replicated measured changes in device performance with age through variations in model input parameters. Our key result is that degradation is influenced by correlated changes in the concentrations and diffusion coefficients of mobile ions and by interface recombination at large mobile ion concentrations. This study demonstrates the power of machine learning combined with simulations to reliably interpret experimental results, a task which is problematic if using simulation models with only manual exploration of the input parameter space.

physics.comp-ph↗

arXiv2022

A Continuum of Physics-Based Lithium-Ion Battery Models Reviewed

Physics-based electrochemical battery models derived from porous electrode theory are a very powerful tool for understanding lithium-ion batteries, as well as for improving their design and management. Different model fidelity, and thus model complexity, is needed for different applications. For example, in battery design we can afford longer computational times and the use of powerful computers, while for real-time battery control (e.g. in electric vehicles) we need to perform very fast calculations using simple devices. For this reason, simplified models that retain most of the features at a lower computational cost are widely used. Even though in the literature we often find these simplified models posed independently, leading to inconsistencies between models, they can actually be derived from more complicated models using a unified and systematic framework. In this review, we showcase this reductive framework, starting from a high-fidelity microscale model and reducing it all the way down to the Single Particle Model (SPM), deriving in the process other common models, such as the Doyle-Fuller-Newman (DFN) model. We also provide a critical discussion on the advantages and shortcomings of each of the models, which can aid model selection for a particular application. Finally, we provide an overview of possible extensions to the models, with a special focus on thermal models. Any of these extensions could be incorporated into the microscale model and the reductive framework re-applied to lead to a new generation of simplified, multi-physics models.

physics.chem-ph↗

arXiv2021

A new ideality factor for perovskite solar cells and an analytical theory for their impedance spectroscopy response

Impedance spectroscopy (IS) is a relatively straightforward experimental technique that is commonly used to obtain information about the physical and chemical characteristics of photovoltaic devices. However, the non-standard physical behaviour of perovskite solar cells (PSC), which are heavily influenced by the motion of mobile ion vacancies, has hindered efforts to obtain a consistent theory to interpret PSC impedance data. This work rectifies this omission by deriving a simple analytic model of the impedance response of a PSC from the underlying drift-diffusion model of charge carrier dynamics and ion vacancy motion. Extremely good agreement is shown between the analytic model and the much more complex drift-diffusion model in regimes (including maximum power point) where the applied voltage is close to the open circuit voltage $V_{oc}$. Both models show good qualitative agreement to experimental IS data in the literature and predict many of the observed anomalous features found in impedance measurements on PSCs, such as `the giant low frequency capacitance` and `inductive arcs' in the Nyquist plots. Where the physical properties of the PSC are already known the analytic model can be used to predict the recombination current $j_{rec}$ and the high and low frequency resistances and capacitances of the cell, $R_{HF}$, $C_{HF}$, $R_{LF}$ and $C_{LF}$. In scenarios where the physical properties of the cell are unknown the analytic model can also used to extract physical parameters from experimental PSC impedance data. {A novel physical parameter of particular significance to PSC physics is identified. This is termed the electronic ideality factor, $n_{el}$, and (as opposed to the standard ideality factor) can be used to deduce the dominant source of recombination in a PSC, independent of its ionic properties.

physics.app-ph↗

arXiv2021

DandeLiion v1: An extremely fast solver for the Newman model of lithium-ion battery (dis)charge

DandeLiion (available at dandeliion.com) is a robust and extremely fast solver for the Doyle Fuller Newman (DFN) model, the standard electrochemical model for (dis)charge of a planar lithium-ion cell. DandeLiion conserves lithium, uses a second order spatial discretisation method (enabling accurate computations using relatively coarse discretisations) and is many times faster than its competitors. The code can be used `in the cloud' and does not require installation before use. The difference in compute time between DandeLiion and its commercial counterparts is roughly a factor of 100 for the moderately-sized test case of the discharge of a single cell. Its linear scaling property means that the disparity in performance is even more pronounced for bigger systems, making it particularly suitable for applications involving multiple coupled cells. The model is characterised by a number of phenomenological parameters and functions, which may either be provided by the user or chosen from DandeLiion's library. This library contains data for the most commonly used electrolyte (LiPF6) and a number of common active material chemistries including graphite, lithium iron phosphate (LFP), nickel cobalt aluminium (NCA), and a variant of nickel cobalt manganese (NMC).

physics.app-ph↗

arXiv2020

Deducing the key physical properties of a perovskite solar cell from its impedance response: insights from drift-diffusion modelling

Interpreting the impedance response of perovskite solar cells (PSC) is significantly more challenging than for most other photovoltaics. This is for a variety of reasons, of which the most significant are the mixed ionic-electronic conduction properties of metal halide perovskites and the difficulty in fabricating stable, and reproducible, devices. Experimental studies, conducted on a variety of PSCs, produce a variety of impedance spectra shapes. However, they all possess common features, the most noteworthy of which is that they have at least two signals, at high and low frequency, with different characteristic responses to temperature, illumination and electrical bias. It is shown, by a combination of experiment and drift-diffusion modelling of the ion and charge carrier transport and recombination within the cell, that these common features are well reproduced by the simulation. In addition, we show that the high frequency response contains all the key information relating to the steady-state performance of a PSC, i.e. it is a signature of the recombination mechanisms and provides a measure of charge collection efficiency. Moreover, steady-state performance is significantly affected by the distribution of mobile ionic charge within the perovskite layer. Comparison between the electrical properties of different devices should therefore be made using high frequency impedance measurements performed in the steady-state voltage regime in which the cell is expected to operate.

physics.app-ph↗

arXiv2018

A mathematical model for mechanically-induced deterioration of the binder in lithium-ion electrodes

This study is concerned with modeling detrimental deformations of the binder phase within lithium-ion batteries that occur during cell assembly and usage. A two-dimensional poroviscoelastic model for the mechanical behavior of porous electrodes is formulated and posed on a geometry corresponding to a thin rectangular electrode, with a regular square array of microscopic circular electrode particles, stuck to a rigid base formed by the current collector. Deformation is forced both by (i) electrolyte absorption driven binder swelling, and; (ii) cyclic growth and shrinkage of electrode particles as the battery is charged and discharged. The governing equations are upscaled in order to obtain macroscopic effective-medium equations. A solution to these equations is obtained, in the asymptotic limit that the height of the rectangular electrode is much smaller than its width, that shows the macroscopic deformation is one-dimensional. The confinement of macroscopic deformations to one dimension is used to obtain boundary conditions on the microscopic problem for the deformations in a 'unit cell' centered on a single electrode particle. The resulting microscale problem is solved using numerical (finite element) techniques. The two different forcing mechanisms are found to cause distinctly different patterns of deformation within the microstructure. Swelling of the binder induces stresses that tend to lead to binder delamination from the electrode particle surfaces in a direction parallel to the current collector, whilst cycling causes stresses that tend to lead to delamination orthogonal to that caused by swelling. The differences between the cycling-induced damage in both: (i) anodes and cathodes, and; (ii) fast and slow cycling are discussed. Finally, the model predictions are compared to microscopy images of nickel manganese cobalt oxide cathodes and a qualitative agreement is found.

physics.flu-dyn↗

arXiv2018

Binder migration during drying of lithium-ion battery electrodes: modelling and comparison to experiment

The drying process is a crucial step in electrode manufacture as it can affect the component distribution within the electrode. Phenomena such as binder migration can have negative effects in the form of poor cell performance (e.g. capacity fade) or mechanical failure (e.g. electrode delamination from the current collector). We present a mathematical model that tracks the evolution of the binder concentration in the electrode during drying. Solutions to the model predict that low drying rates lead to a favourable homogeneous binder profile across the electrode film, whereas high drying rates result in an unfavourable accumulation of binder near the evaporation surface. These results show strong qualitative agreement with experimental observations and provide a cogent explanation for why fast drying conditions result in poorly performing electrodes. Finally, we provide some guidelines on how the drying process could be optimised to offer relatively short drying times whilst simultaneously maintaining a roughly homogeneous binder distribution.

cond-mat.soft↗