Trapping and Tunneling of Hydrogen, Deuterium and Oxygen in Niobium

TL;DR

This study uses machine learning and quantum calculations to analyze how hydrogen, deuterium, and oxygen atoms are trapped and tunnel within niobium's crystal structure, revealing new trapping sites and quantum tunneling behaviors.

Contribution

It introduces a machine-learning interatomic potential trained on DFT to identify new trapping sites and analyze quantum tunneling of light atoms in niobium.

Findings

Identification of a lower-energy 'edge' trapping site for H and D.

Quantification of tunnel splittings in the GHz range for trapped H and D.

Validation of trapping site stability with DFT calculations.

Abstract

We investigate isolated O-H and O-D pairs trapped in BCC Nb using a machine-learning interatomic potential (MLIP) trained to density-functional theory (DFT). The MLIP enables large-supercell analysis and identification of trapping sites within BCC Nb, as well as efficient mapping of three-dimensional (3D) potential-energy surfaces. In addition to the pair of tetrahedral``face'' sites previously identified based on DFT, we identify a lower-energy pair of ``edge'' trapping sites and confirm the stability of H and D at these trapping sites with DFT. We solve the Schr\"odinger equation for H and D in the 3D potential that surrounds the trapping sites. Solutions based on the static-lattice limit yield tunnel splittings in the range $J/h \in\{3-100\}$ GHz for both trapping sites.