Large Scale Structure Prediction of Near-Stoichiometric Magnesium Oxide Based on a Machine-Learned Interatomic Potential: Novel Crystalline Phases and Oxygen-Vacancy Ordering
Hossein Tahmasbi, Stefan Goedecker, S. Alireza Ghasemi

TL;DR
This study uses a neural network potential and minima hopping to discover new crystalline phases and oxygen-vacancy arrangements in magnesium oxide, revealing structures with unique properties and low energy configurations.
Contribution
The paper introduces a machine-learned interatomic potential combined with minima hopping to systematically explore MgO's complex energy landscape, uncovering novel phases and vacancy orderings.
Findings
Discovered new low-energy rocksalt-like structures with varied stacking sequences.
Identified dense spectrum of non-stoichiometric MgO phases with oxygen vacancies.
Found structures with properties like low thermal conductivity and high electrical conductivity.
Abstract
Using a fast and accurate neural network potential we are able to systematically explore the energy landscape of large unit cells of bulk magnesium oxide with the minima hopping method. The potential is trained with a focus on the near-stoichiometric compositions, in particular on suboxides, i.e., MgO with . Our extensive exploration demonstrates that for bulk stoichiometric compounds, there are several new low-energy rocksalt-like structures in which Mg atoms are octahedrally six--coordinated and form trigonal prismatic motifs with different stacking sequences. Furthermore, we find a dense spectrum of novel non-stoichiometric crystal phases of MgO for each composition of . These structures are mostly similar to the rock salt structure with octahedral coordination and five--coordinated Mg atoms. Due to the removal of one oxygen atom, the energy…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
