Structure and thermodynamics of defects in Na-feldspar from a neural network potential

Author(s)
Alexander Gorfer, Rainer Abart, Christoph Dellago
Abstract

The diffusive phase transformations occurring in feldspar, a common mineral in the crust of the Earth, are essential for reconstructing the thermal histories of magmatic and metamorphic rocks. Due to the long timescales over which these transformations proceed, the mechanism responsible for sodium diffusion and its possible anisotropy has remained a topic of debate. To elucidate this defect-controlled process, we have developed a neural network potential (NNP) trained on first-principle calculations of Na-feldspar (albite) and its charged defects. This force field reproduces various experimentally known properties of feldspar, including its lattice parameters and elastic constants as well as heat capacity and DFT-calculated defect formation energies. A new type of dumbbell interstitial defect is found to be most favorable, and its free energy of formation at finite temperature is calculated using thermodynamic integration. The necessity of including electrostatic corrections before training an NNP is demonstrated by predicting more consistent defect formation energies.

Organisation(s)
Department of Lithospheric Research, Computational and Soft Matter Physics
Journal
Physical Review Materials
Volume
8
No. of pages
12
ISSN
2475-9953
DOI
https://doi.org/10.48550/arXiv.2402.14640
Publication date
07-2024
Peer reviewed
Yes
Austrian Fields of Science 2012
103015 Condensed matter, 102019 Machine learning
ASJC Scopus subject areas
Materials Science(all), Physics and Astronomy (miscellaneous)
Portal url
https://ucrisportal.univie.ac.at/en/publications/structure-and-thermodynamics-of-defects-in-nafeldspar-from-a-neural-network-potential(af3c0b4a-24d9-47a7-8646-cab9afbc774e).html