Molecularity: A fast and efficient criterion for probing superconductivity

Abstract

We present an efficient criterion for doing fast estimations of the critical temperature of hydrogen-based superconductors. We start by expanding the applicability of three-dimensional descriptors of electron localization to superconducting states within the framework of superconducting density functional theory (DFT). We first apply this descriptor to a model system, the hydrogen chain, which allows one to prove two main concepts: (i) the electron localization changes very little when the transition from the normal to the superconducting state takes place, i.e., it can be described at the DFT level from the normal state; and (ii) the formation of molecules can be characterized within this theoretical framework, enabling one to quickly filter out systems with marked molecular character and hence with low potential to be good superconductors. These two ideas are then exploited in real binary and ternary systems, showing (i) that the bonding type can be characterized automatically and (ii) that this provides a different index which enables one to feed machine-learning algorithms for a better prediction of critical temperatures. Overall, this sets a grounded theoretical scenario for an automatic and efficient high-throughput screening of potential hydrogen-based superconductors.