Abstract 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.
Xu et al. (Fri,) studied this question.