Structure prediction of stable sodium germanides at 0 and 10 GPa
Year: 2024
Type: article
Abstract: In this paper we used random structure searching (AIRSS) to carry out a systematic search for crystalline Na-Ge materials at both 0 and 10 GPa. The high-throughput structural relaxations were accelerated using a machine-learned interatomic potential (MLIP) fit to density-functional theory (DFT) reference data, allowing ∼ 1.5 million structures to be relaxed. At ambient conditions we predict three new Zintl phases, Na 3 Ge 2 , Na 2 Ge , and Na 9 Ge 4 , to be stable and a number of Ge-rich layered structures to lie in close proximity to the convex hull. The known Na δ Ge 34 clathrate and Na 4 Ge 13 host-guest structures are found to be relatively stabilized at higher temperature by vibrational contributions to the free energy. Overall, the low-energy phases exhibit exceptional structural diversity, with the expected mixture of covalent and ionic bonding confirmed using the electron-localization function (ELF). The local Ge structural motifs present at each composition were determined using smooth overlap of atomic positions (SOAP) descriptors and the Ge-K edge was simulated for representatives of each motif, providing a direct link to experimental x-ray absorption spectroscopy (XAS). Two Ge-rich phases are predicted to be stable at 10 GPa; NaGe 3 and NaGe 2 have simple kagome and simple hexagonal Ge lattices respectively with Na contained in the pores. NaGe 3 is isostructural with the MgB 3 and MgSi 3 family of kagome superconductors and remains dynamically stable at 0 GPa. Removing the Na from NaGe 2 results in the hexagonal lonsdalite Ge allotrope, which has a direct band gap. Published by the American Physical Society 2024
Source: Physical Review Materials
Language: English
Subfield: Materials Chemistry
Field: Materials Science
Domain: Physical Sciences
Open Access status: hybrid
Awards: CCP9: Computational Electronic Structure of Condensed Matter, G21365943, Support for the UKCP consortium, G258572227, The UK Car-Parrinello HEC Consortium, Collaborative Computational Project in NMR Crystallography, Baskerville: a national accelerated compute resource, Cambridge Service for Data Driven Discovery (CSD3) - A National Data Intensive Science Cloud for Converged Simulation, AI & Analytics, G7469073440, G8779788597
OpenAlex ID: W4403535572