Analysis of Diffusion in Solid-State Electrolytes through MD Simulations, Improvement of the Li-Ion Conductivity in β-Li3PS4 as an Example
Publication type: Journal Article
Publication date: 2018-06-12
scimago Q1
wos Q2
SJR: 1.378
CiteScore: 10.2
Impact factor: 5.5
ISSN: 25740962
PubMed ID:
30057999
Materials Chemistry
Electrochemistry
Electrical and Electronic Engineering
Energy Engineering and Power Technology
Chemical Engineering (miscellaneous)
Abstract
Molecular dynamics simulations are a powerful tool to study diffusion processes in battery electrolyte and electrode materials. From molecular dynamics simulations, many properties relevant to diffusion can be obtained, including the diffusion path, amplitude of vibrations, jump rates, radial distribution functions, and collective diffusion processes. Here it is shown how the activation energies of different jumps and the attempt frequency can be obtained from a single molecular dynamics simulation. These detailed diffusion properties provide a thorough understanding of diffusion in solid electrolytes, and provide direction for the design of improved solid electrolyte materials. The presently developed analysis methodology is applied to DFT MD simulations of Li-ion diffusion in β-Li3PS4. The methodology presented is generally applicable to diffusion in crystalline materials and facilitates the analysis of molecular dynamics simulations. The code used for the analysis is freely available at: https://bitbucket.org/niekdeklerk/md-analysis-with-matlab. The results on β–Li3PS4 demonstrate that jumps between bc planes limit the conductivity of this important class of solid electrolyte materials. The simulations indicate that the rate-limiting jump process can be accelerated significantly by adding Li interstitials or Li vacancies, promoting three-dimensional diffusion, which results in increased macroscopic Li-ion diffusivity. Li vacancies can be introduced through Br doping, which is predicted to result in an order of magnitude larger Li-ion conductivity in β–Li3PS4. Furthermore, the present simulations rationalize the improved Li-ion diffusivity upon O doping through the change in Li distribution in the crystal. Thus, it is demonstrated how a thorough understanding of diffusion, based on thorough analysis of MD simulations, helps to gain insight and develop strategies to improve the ionic conductivity of solid electrolytes.
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de Klerk N., Van Der Maas E., Wagemaker M. Analysis of Diffusion in Solid-State Electrolytes through MD Simulations, Improvement of the Li-Ion Conductivity in β-Li3PS4 as an Example // ACS Applied Energy Materials. 2018. Vol. 1. No. 7. pp. 3230-3242.
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de Klerk N., Van Der Maas E., Wagemaker M. Analysis of Diffusion in Solid-State Electrolytes through MD Simulations, Improvement of the Li-Ion Conductivity in β-Li3PS4 as an Example // ACS Applied Energy Materials. 2018. Vol. 1. No. 7. pp. 3230-3242.
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TY - JOUR
DO - 10.1021/acsaem.8b00457
UR - https://doi.org/10.1021/acsaem.8b00457
TI - Analysis of Diffusion in Solid-State Electrolytes through MD Simulations, Improvement of the Li-Ion Conductivity in β-Li3PS4 as an Example
T2 - ACS Applied Energy Materials
AU - de Klerk, Niek
AU - Van Der Maas, Eveline
AU - Wagemaker, M.
PY - 2018
DA - 2018/06/12
PB - American Chemical Society (ACS)
SP - 3230-3242
IS - 7
VL - 1
PMID - 30057999
SN - 2574-0962
ER -
Cite this
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@article{2018_de Klerk,
author = {Niek de Klerk and Eveline Van Der Maas and M. Wagemaker},
title = {Analysis of Diffusion in Solid-State Electrolytes through MD Simulations, Improvement of the Li-Ion Conductivity in β-Li3PS4 as an Example},
journal = {ACS Applied Energy Materials},
year = {2018},
volume = {1},
publisher = {American Chemical Society (ACS)},
month = {jun},
url = {https://doi.org/10.1021/acsaem.8b00457},
number = {7},
pages = {3230--3242},
doi = {10.1021/acsaem.8b00457}
}
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MLA
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de Klerk, Niek, et al. “Analysis of Diffusion in Solid-State Electrolytes through MD Simulations, Improvement of the Li-Ion Conductivity in β-Li3PS4 as an Example.” ACS Applied Energy Materials, vol. 1, no. 7, Jun. 2018, pp. 3230-3242. https://doi.org/10.1021/acsaem.8b00457.
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