Leveraging Machine Learning for Accelerated Electrode–Electrolyte Interface Design in Rechargeable Li‐Based Batteries
- DOI
- 10.1002/smll.74632
- Published
- 2026-08-14
- Container
- Small
- Publisher
- Wiley
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1002/smll.74632,
title = {Leveraging Machine Learning for Accelerated Electrode–Electrolyte Interface Design in Rechargeable Li‐Based Batteries},
author = {Xiaorui Liu and Qingyu Li and Jianghao Liang and Zhiqiang Li and Haozhi Wang and Yida Deng},
year = {2026},
journal = {Small},
doi = {10.1002/smll.74632},
url = {https://doi.org/10.1002/smll.74632}
}RIS
TY - JOUR TI - Leveraging Machine Learning for Accelerated Electrode–Electrolyte Interface Design in Rechargeable Li‐Based Batteries AU - Xiaorui Liu AU - Qingyu Li AU - Jianghao Liang AU - Zhiqiang Li AU - Haozhi Wang AU - Yida Deng PY - 2026 JO - Small DO - 10.1002/smll.74632 UR - https://doi.org/10.1002/smll.74632 ER -
APA
Liu, X., Li, Q., Liang, J., Li, Z., Wang, H., & Deng, Y. (2026). Leveraging Machine Learning for Accelerated Electrode–Electrolyte Interface Design in Rechargeable Li‐Based Batteries. Small. https://doi.org/10.1002/smll.74632
Source records
- crossref · retrieved 2026-09-26T02:50:34.758Z