Unifying the Thermodynamic, Electronic, and Mechanical Landscapes of Double-Transition-Metal MXenes for Data-Driven Material Design

This dataset provides a comprehensive computational database of 4,400 double-transition-metal (DTM) MXene candidates, covering thermodynamic stability, electronic structure, and elastic tensor-derived mechanical properties within a unified density functional theory (DFT) framework. Compositional space: The database spans 11 transition metals (Sc, Ti, V, Cr, Y, Zr, Nb, Mo, Hf, Ta, W), two X elements (C and N), 10 surface terminations (H, O, F, S, Cl, Se, Br, Te, I, OH), and three layer thicknesses (n = 2, 3, 4), yielding 4,400 unique DTM MXene compositions with the general formula M′ₙM″ₘXₙ₊ₘ₋₁Tₓ. Computational workflow: Initial structures were pre-relaxed using the CHGNet machine learning interatomic potential, followed by full structural optimization using DFT at the PBE/GGA level (VASP, 520 eV cutoff). Elastic tensor components were calculated using the stress–strain finite-difference method with a tighter electronic convergence criterion of 1 × 10⁻⁵ eV.