Analysis of thousands of electrochemical impedance spectra of lithium-ion cells through a machine learning inverse model

Sam Buteau; J. R. Dahn

doi:10.1149/2.1051908jes

Analysis of thousands of electrochemical impedance spectra of lithium-ion cells through a machine learning inverse model

Sam Buteau, J. R. Dahn

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Research output: Contribution to journal › Article › peer-review

41 Citations (Scopus)

Original language	English
Pages (from-to)	A1611-A1622
Journal	Journal of the Electrochemical Society
Volume	166
Issue number	8
DOIs	https://doi.org/10.1149/2.1051908jes
Publication status	Published - 2019

ASJC Scopus Subject Areas

Electronic, Optical and Magnetic Materials
Renewable Energy, Sustainability and the Environment
Surfaces, Coatings and Films
Electrochemistry
Materials Chemistry

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1149/2.1051908jes

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AU - Dahn, J. R.

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Analysis of thousands of electrochemical impedance spectra of lithium-ion cells through a machine learning inverse model

ASJC Scopus Subject Areas

UN SDGs

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