Homogenization-Informed Convolutional Neural Networks for Estimation of Li-ion Battery Effective Properties
Author:
Funder
U.S. Department of Energy
Publisher
Springer Science and Business Media LLC
Subject
General Chemical Engineering,Catalysis
Link
https://link.springer.com/content/pdf/10.1007/s11242-022-01862-9.pdf
Reference80 articles.
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3. Arunachalam, H., Korneev, S., Battiato, I., Onori, S.: Multiscale modeling approach to determine effective lithium-ion transport properties. 2017 Am. Cont. Conf. , 92–97, (2017)
4. Arunachalam, H., Onori, S., Battiato, I.: On veracity of macroscopic lithium-ion battery models. J. Electrochem. Soc. 162, A1940–A1951 (2015). https://doi.org/10.1149/2.0771509jes
5. Backeberg, N.R., Iacoviello, F., Rittner, M., Mitchell, T.M., Jones, A.P., Day, R., Wheeler, J., Shearing, P.R., Vermeesch, P., Striolo, A.: Quantifying the anisotropy and tortuosity of permeable pathways in clay-rich mudstones using models based on X-ray tomography. Sci. Rep. 7, 14838 (2017)
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