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Shang et al. J. Mater. Inf. 2025, 5, 52 https://dx.doi.org/10.20517/jmi.2025.36 Page 13 of 15

function of MXenes. Our work achieves a balance of high accuracy and interpretability in ML predictions of
the work function of MXenes, providing valuable insights and tools for materials science.

DECLARATIONS
Authors’ contributions
Investigation, formal analysis, writing - original draft: Shang, L.
Analyzed the data, contributed analysis tools: Yang, Y.
Provide professional guidance on data processing, machine learning: Yu, Y.
Supervision: Xiang, P.
Provide support in material expertise: Ma, L.
Validation, funding acquisition, software: Guo, Z.
Validation, supervision: Dai, M.

Availability of data and materials
The data and code supporting the findings of this study are available at: https://github.com/Moneshanghai/
MXeneStackedML. Further inquiries can be directed to the corresponding author(s).

Financial support and sponsorship
This work was supported by the National Natural Science Foundation of China (No. 52403306) and the
Hebei Natural Science Foundation (No. B2024202047).

Conflicts of interest
All authors declared that there are no conflicts of interest.

Ethical approval and consent to participate
Not applicable.

Consent for publication
Not applicable.

Copyright
© The Author(s) 2025.

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