Three-dimensional image based modelling of transport parameters in lithium–sulfur batteries

Literature Information

Publication Date 2018-10-02
DOI 10.1039/C8CP04763D
Impact Factor 3.676
Authors

Chun Tan, Matthew D. R. Kok, Sohrab R. Daemi, Daniel J. L. Brett, Paul R. Shearing


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Abstract

An elemental sulfur electrode was imaged with X-ray micro and nano computed tomography and segmented into its constituent phases. Morphological parameters including phase fractions and pore and particle size distributions were calculated directly from labelled image data, and flux based simulations were performed to determine the effective molecular diffusivity of the pore phase and electrical conductivity of the conductive carbon and binder phase, Deff and σeff, that can be used as an input for Li–S battery modelling. In addition to its crucial role in providing electrical conductivity within the sulfur electrode, the intrinsic porosity of the carbon binder domain was found to significantly influence Li-ion transport within the electrode. Neglecting this intrinsic porosity results in an overestimation of the electrical conductivity within the sulfur electrode, and an underestimation of the tortuosity of the Li-ion conducting phase by ca. 56%. The derivation of effective transport parameters directly from image data may aid in the development of more realistic models of Li–S battery systems by reducing the reliance on empirical correlations, and the uncertainties arising from assumptions made in these correlations.

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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
Articles per Year: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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