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N-doped MXenes for tribological applications: A high-throughput DFT dataset
Mingyang Xu1,2, Yu Gao3,4, Wenhao He2
1School of Materials Science and Engineering, Lanzhou Jiaotong University, Lanzhou, 730070, China.
Scientific Data
|April 17, 2026
Summary
Nitrogen doping enhances MXene materials for solid lubrication. This study provides a dataset of N-doped MXene properties for designing advanced, low-friction coatings.
Area of Science:
- Materials Science
- Tribology
- Computational Chemistry
Background:
- MXenes are advanced 2D materials with significant potential in solid lubrication.
- Nitrogen doping is an emerging technique to tune MXene properties for specific applications.
Purpose of the Study:
- To create a comprehensive dataset of pristine and nitrogen-doped MXene properties.
- To provide fundamental insights into the interfacial behavior of N-doped MXenes.
- To establish a benchmark for machine learning-guided design of N-doped MXene coatings.
Main Methods:
- Density Functional Theory (DFT) calculations were employed.
- A dataset of 210 MXene structures (pristine and N-doped) was generated.
- Electronic, thermodynamic, and tribological properties were computed and visualized.
Main Results:
- Nitrogen doping significantly alters the electronic, thermodynamic, and tribological characteristics of MXenes.
- Visualizations highlight the impact of nitrogen doping on material properties.
- The generated dataset offers a valuable resource for understanding MXene interfacial behavior.
Conclusions:
- N-doped MXenes show promise for developing high-performance solid lubricants.
- The dataset serves as a foundation for future machine learning-based material design.
- This work facilitates the creation of reliable, low-friction N-doped MXene coatings.
