Attribution Fingerprinting by Interpretable Machine Learning Reveals Category‐Specific Additive Design Rules for Zinc Anodes
- DOI
- 10.1002/adma.75609
- Published
- 2026-11-02
- Container
- Advanced Materials
- Publisher
- Wiley
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1002/adma.75609,
title = {Attribution Fingerprinting by Interpretable Machine Learning Reveals Category‐Specific Additive Design Rules for Zinc Anodes},
author = {Guolang Zhou and Minmeng Tang and Xinwang Xu and Xin Tang and Tianshi Wang and Chong Zhao and Chao Tang and Cheng Liu and Tengfei Miao and Le Xu and Yubo Yan and Zhendong Yu and Zhipeng Cheng and Lili Zhang and Wenshuai Zhu and Junwu Zhu},
year = {2026},
journal = {Advanced Materials},
doi = {10.1002/adma.75609},
url = {https://doi.org/10.1002/adma.75609}
}RIS
TY - JOUR TI - Attribution Fingerprinting by Interpretable Machine Learning Reveals Category‐Specific Additive Design Rules for Zinc Anodes AU - Guolang Zhou AU - Minmeng Tang AU - Xinwang Xu AU - Xin Tang AU - Tianshi Wang AU - Chong Zhao AU - Chao Tang AU - Cheng Liu AU - Tengfei Miao AU - Le Xu AU - Yubo Yan AU - Zhendong Yu AU - Zhipeng Cheng AU - Lili Zhang AU - Wenshuai Zhu AU - Junwu Zhu PY - 2026 JO - Advanced Materials DO - 10.1002/adma.75609 UR - https://doi.org/10.1002/adma.75609 ER -
APA
Zhou, G., Tang, M., Xu, X., Tang, X., Wang, T., Zhao, C., Tang, C., Liu, C., Miao, T., Xu, L., Yan, Y., Yu, Z., Cheng, Z., Zhang, L., Zhu, W., & Zhu, J. (2026). Attribution Fingerprinting by Interpretable Machine Learning Reveals Category‐Specific Additive Design Rules for Zinc Anodes. Advanced Materials. https://doi.org/10.1002/adma.75609
Source records
- crossref · retrieved 2026-11-04T15:12:02.533Z