Computational prediction of novel two-dimensional tungsten nitride superconductors

Transition metal nitrides are well-known 3D superconductor materials. However, there is a lack of knowledge related to their two-dimensional (2D) counterparts, which have several potential technological applications. In this work, we predict, using an evolutionary algorithm coupled with a first-principles approach, a set of novel 2D superconductive structures based on tungsten nitride. Through a systematic process including energetic and dynamical analysis, three thermodynamically stable compositions along with metastable compounds were studied in the following stoichiometries: W₄N₂, W₂N₂, and W₂N₃. Their superconductive temperature (Tc) values, estimated by means of the Eliashberg superconductive theory and the McMillan equation, range from 2.3 to 21.6 K, where the highestTcvalue corresponds to a W₂N₃metastable hexagonal system. A systematic analysis of the structural, electronic, vibrational and electron-phonon (e-ph) properties, allowed us to recognize the variables that modulate theTcin theses systems. The superconductive behavior is strongly affected by changes in the nitrogen density of states at Fermi level, the e-ph coupling constant and the lattice symmetry. The present results aim to encourage further theoretical and experimental efforts over non fully explored superconductors in two dimensions.