New engineering science insights into the electrodes pairing of electrochemical energy storage devices assisted by machine learning

Qu L, Wang P, Motevalli B, Liang Q, Wang K, Jiang W, Liu JZ, Li D.

DOI: 10.21203/rs.3.rs-831006/v1
Published: 2022-05-18
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Cite this work

BibTeX

@article{allodium:10.21203/rs.3.rs-831006/v1,
  title = {New engineering science insights into the electrodes pairing of electrochemical energy storage devices assisted by machine learning},
  author = {Qu L and  Wang P and  Motevalli B and  Liang Q and  Wang K and  Jiang W and  Liu JZ and  Li D.},
  year = {2022},
  doi = {10.21203/rs.3.rs-831006/v1},
  url = {https://doi.org/10.21203/rs.3.rs-831006/v1}
}

RIS

TY  - JOUR
TI  - New engineering science insights into the electrodes pairing of electrochemical energy storage devices assisted by machine learning
AU  - Qu L
AU  -  Wang P
AU  -  Motevalli B
AU  -  Liang Q
AU  -  Wang K
AU  -  Jiang W
AU  -  Liu JZ
AU  -  Li D.
PY  - 2022
DO  - 10.21203/rs.3.rs-831006/v1
UR  - https://doi.org/10.21203/rs.3.rs-831006/v1
ER  -

APA

L, Q., P, W., B, M., Q, L., K, W., W, J., JZ, L., & D., L. (2022). New engineering science insights into the electrodes pairing of electrochemical energy storage devices assisted by machine learning. https://doi.org/10.21203/rs.3.rs-831006/v1

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europe-pmc · retrieved 2026-11-10T14:14:51.330Z