Engineering of entropy-driven surface doping towards stabilized high-voltage NCM cathodes: Li (Ni, Co, Mn, Ce, La, Zr, Al) O
Ni-rich LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NCM) cathodes in layered oxide cathodes are attractive for high-energy lithium-ion batteries but suffer from rapid capacity fade and thermal instability at high charge voltages. In this study, we propose an entropy-assisted multi-element doping strategy to mitigate these issues. Specifically, two routes are designed and compared: bulk-like localized high-entropy doping (BHE-NCM) and surface-distributed high-entropy-zone doping (SHE-NCM). The surface entropy-doped NCM cathode delivers enhanced electrochemical performance, including higher capacity retention under 4.5 V cycling and superior rate capability, compared to both bulk-like and pristine counterparts. Comprehensive material characterization reveals that surface-localized doping stabilizes the layered structure with reduced microcrack formation and creates a uniform dopant-rich surface region with improved thermal and electrochemical stability. Overall, entropy-assisted doping at the near surface zone effectively alleviates structural degradation and interface reactions in Ni-rich NCM, enabling improved cycling performance at high voltage. This work highlights the significance of surface entropy engineering as a promising strategy for designing high-voltage cathodes with improved safety and longevity.
Authors
- Xiao Sun (ORCID: https://orcid.org/0000-0002-5770-0943)
- Zezhou Lin (ORCID: https://orcid.org/0000-0002-1799-6591)
- Yijun Zhong (ORCID: https://orcid.org/0000-0003-4112-7115)
- William D.A. Rickard (ORCID: https://orcid.org/0000-0002-8118-730X)
- Tony P. Tang
- Yucheng Huang (ORCID: https://orcid.org/0000-0002-7818-8811)
- Hanwen Liu (ORCID: https://orcid.org/0000-0002-0874-3752)
- Leqi Zhao (ORCID: https://orcid.org/0000-0003-2270-1257)
- Zongping Shao (ORCID: https://orcid.org/0000-0001-7670-183X)
Institutions
- Hong Kong Polytechnic University (HK)
- Curtin University (AU)
- Department of Mines and Petroleum (AU)
Publication Details
- Journal
- Materials Reports Energy
- Published
- 2025-10-17
- DOI
- https://doi.org/10.1016/j.matre.2025.100378
- Citations
- 1
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.73