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Challenges and opportunities in using Kinetic Monte Carlo for battery research and innovation

descriptionPublicationkeyboard_double_arrow_right Article 01 Jan 2025 France English Publisher:Royal Society of Chemistry (RSC)Journal:EES Batteries, volume 1, pages 788-802 (eissn: 3033-4071, Copyright policy )
Authors: Bin Jassar, Mohammed; de Bruin, Theodorus; Nieto-Draghi, Carlos; Steinmann, Stephan N.;

doi: 10.1039/d5eb00070j

Challenges and opportunities in using Kinetic Monte Carlo for battery research and innovation

Abstract

Kinetic Monte Carlo is already exploited to understand and improve batteries via molecular-level insights, but would be even more reliable with improved algorithms for time-scale disparities, more flexible lattices and more accurate time-constants.

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France
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Keywords

[CHIM.THEO] Chemical Sciences/Theoretical and/or physical chemistry, [CHIM.OTHE] Chemical Sciences/Other

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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gold