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A perspective on inverse design of battery interphases using multi-scale modelling, experiments and generative deep learning

Crossref DOI link: https://doi.org/10.1016/j.ensm.2019.06.011

Published Print: 2019-09

Update policy: https://doi.org/10.1016/elsevier_cm_policy

Authors

Bhowmik, Arghya

Castelli, Ivano E.

Garcia-Lastra, Juan Maria

Jørgensen, Peter Bjørn

Winther, Ole

Vegge, Tejs
Funding

Funding for this research was provided by:

VILLUM FONDEN

DeepDFT (0023105)

European Union's Horizon 2020 research and innovation programs FET Open (766581)

European Union's Horizon 2020 research and innovation programs FET Open (711792)

FET Proactive (824066)

FET Proactive (854472)
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Text and Data Mining valid from 2019-09-01

Text and Data Mining valid from 2019-09-01

Version of Record valid from 2019-06-26
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This article is maintained by: Elsevier

Article Title: A perspective on inverse design of battery interphases using multi-scale modelling, experiments and generative deep learning

Journal Title: Energy Storage Materials

CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.ensm.2019.06.011

Content Type: article

Copyright: © 2019 The Authors. Published by Elsevier B.V.