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<p>MXenes have emerged as a prominent class of two-dimensional materials in the field of solid lubrication, and nitrogen doping has recently been identified as an effective strategy for tailoring their properties. Herein, we present a comprehensive dataset of 210 pristine and N-doped MXene structures with detailed electronic, thermodynamic, and tribological properties obtained through density functional theory (DFT). Selected properties are visualized to illustrate doping effects. This dataset not only provides fundamental insights into the interfacial behavior of MXenes but also establishes a foundational benchmark for the machine-learning-driven design of reliable, low-friction N-doped MXene coatings.</p>

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N-doped MXenes for tribological applications: A high-throughput DFT dataset

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月17日

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  • Mingyang Xu,
  • Yu Gao,
  • Wenhao He,
  • Zhongrong Geng,
  • Qian Meng,
  • Zhibin Lu

摘要

MXenes have emerged as a prominent class of two-dimensional materials in the field of solid lubrication, and nitrogen doping has recently been identified as an effective strategy for tailoring their properties. Herein, we present a comprehensive dataset of 210 pristine and N-doped MXene structures with detailed electronic, thermodynamic, and tribological properties obtained through density functional theory (DFT). Selected properties are visualized to illustrate doping effects. This dataset not only provides fundamental insights into the interfacial behavior of MXenes but also establishes a foundational benchmark for the machine-learning-driven design of reliable, low-friction N-doped MXene coatings.