Computational understanding of Li-ion batteries

Urban, Alexander; Seo, Dong-Hwa; Ceder, Gerbrand

doi:10.1038/npjcompumats.2016.2

Computational understanding of Li-ion batteries

Journal Article · Fri Mar 18 00:00:00 EDT 2016 · npj Computational Materials

DOI:https://doi.org/10.1038/npjcompumats.2016.2· OSTI ID:1474909

^[1]; ^[2]; Ceder, Gerbrand ^[3]

Univ. of California, Berkeley, CA (United States). Dept. of Materials Science and Engineering
Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States). Dept. of Materials Science and Engineering
Univ. of California, Berkeley, CA (United States). Dept. of Materials Science and Engineering; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Materials Sciences Division

Over the last two decades, computational methods have made tremendous advances, and today many key properties of lithium-ion batteries can be accurately predicted by first principles calculations. For this reason, computations have become a cornerstone of battery-related research by providing insight into fundamental processes that are not otherwise accessible, such as ionic diffusion mechanisms and electronic structure effects, as well as a quantitative comparison with experimental results. The aim of this review is to provide an overview of state-of-the-art ab initio approaches for the modelling of battery materials. Here, we consider techniques for the computation of equilibrium cell voltages, 0-Kelvin and finite-temperature voltage profiles, ionic mobility and thermal and electrolyte stability. The strengths and weaknesses of different electronic structure methods, such as DFT+U and hybrid functionals, are discussed in the context of voltage and phase diagram predictions, and we review the merits of lattice models for the evaluation of finite-temperature thermodynamics and kinetics. With such a complete set of methods at hand, first principles calculations of ordered, crystalline solids, i.e., of most electrode materials and solid electrolytes, have become reliable and quantitative. However, the description of molecular materials and disordered or amorphous phases remains an important challenge. We highlight recent exciting progress in this area, especially regarding the modelling of organic electrolytes and solid–electrolyte interfaces.

View Accepted Manuscript (DOE)

Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC)

Grant/Contract Number:: AC02-05CH11231; FG02-96ER45571

OSTI ID:: 1474909

Journal Information:: npj Computational Materials, Journal Name: npj Computational Materials Journal Issue: 1 Vol. 2; ISSN 2057-3960

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United States

Language:: English

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