Related papers: Stochastic model for the 3D microstructure of pris…
Li-ion battery performance is strongly influenced by their cathodes' properties and consequently by the 3D microstructure of the particles the cathodes are comprised of. During calendaring and cycling, cracks develop within cathode…
We present a simulation workflow for efficient investigations of the interplay between 3D lithium-ion electrode microstructures and electrochemical performance, with emphasis on lithium plating. Our approach addresses several challenges.…
A stochastic 3D modeling approach for the nanoporous binder-conductive additive phase in hierarchically structured cathodes of lithium-ion batteries is presented. The binder-conductive additive phase of these electrodes consists of carbon…
The performance of all-solid-state battery (ASSB) cathodes strongly depends on their microstructure. Optimizing the cathode morphology can therefore enhance effective macroscopic properties such as ionic and electronic conductivity. The…
The 3D microstructure of solid oxide fuel cell anodes significantly influences their electrochemical performance, but conventional methods for acquiring high-resolution microstructural 3D data such as focused ion beam scanning electron…
A data-driven modeling approach is presented to quantify the influence of morphology on effective properties in nanostructured sodium vanadium phosphate $\mathrm{Na}_3\mathrm{V}_2(\mathrm{PO}_4)_3$/ carbon composites (NVP/C), which are used…
The 3D microstructure of porous media, such as electrodes in lithium-ion batteries or fiber-based materials, significantly impacts the resulting macroscopic properties, including effective diffusivity or permeability. Consequently,…
Moving to larger cell formats in lithium-ion batteries increases overall useable energy but introduces inhomogeneities that influence aging. This study investigates degradation in 21700-type cells with NCM cathodes and graphite/SiOx anodes…
Silicon offers great promise as a potential anode active material and the optimum alternative to lithium metal in all-solid-state lithium-ion batteries. However, its practical application is limited by severe volume expansion (~300%) during…
Fracture of lithium-ion battery electrodes is found to contribute to capacity fade and reduce the lifespan of a battery. Traditional fracture models for batteries are restricted to consideration of a single, idealised particle; here,…
Recently, considerable efforts have been made on research and improvement for Ni-rich lithium-ion batteries to meet the demand from vehicles and grid-level large-scale energy storage. Development of next-generation high-performance…
Lithium-ion batteries are used to store energy in electric vehicles. Physical models based on electro-chemistry accurately predict the cell dynamics, in particular the state of charge. However, these models are nonlinear partial…
The properties of rechargeable lithium-ion batteries are determined by the electrochemical and kinetic properties of their constituent materials as well as by their underlying microstructure. Microstructural design can be leveraged to…
The improvement of Li-ion battery performance requires development of models that capture the essential physics and chemistry in Li-ion battery electrode materials. In this paper a novel electrochemical phase-field model is presented that…
Microstructure often dictates materials performance, yet it is rarely treated as an explicit design variable because microstructure is hard to quantify, predict, and optimize. Here, we introduce an image centric, closed-loop framework that…
Capacity degradation of lithium-ion batteries under long-term cyclic aging is modelled via a flexible sigmoidal-type regression set-up, where the regression parameters can be interpreted. Different approaches known from the literature are…
The unified 3D phase-field model for the description of the lithium-ion cell as a whole is developed. The model takes into account the realistic distribution of particles in porous electrodes, percolative transport of ions, and the…
Image acquisition techniques such as micro-computed tomography are nowadays widely available. Quantitative analysis of the resulting 3D image data enables geometric characterization of the micro-structure of materials. Stochastic geometry…
This paper presents the development of machine learning-enabled data-driven models for effective capacity predictions for lithium-ion batteries under different cyclic conditions. To achieve this, a model structure is first proposed with the…
Accurately predicting aging of lithium-ion batteries would help to prolong their lifespan, but remains a challenge owing to the complexity and interrelation of different aging mechanisms. As a result, aging prediction often relies on…