Ary R. Ferreira | Searcharxiv

arXiv2020

Chemical Bonding in Metallic Glasses from Machine Learning and Crystal Orbital Hamilton Population

The chemistry (composition and bonding information) of metallic glasses (MGs) is at least as important as structural topology for understanding their properties and production/processing peculiarities. This article reports a machine learning (ML)-based approach that brings an unprecedented "big picture" view of chemical bond strengths in MGs of a prototypical alloy system. The connection between electronic structure and chemical bonding is given by crystal orbital Hamilton population (COHP) analysis; within the framework of density functional theory (DFT). The stated comprehensive overview is made possible through a combination of: efficient quantitative estimate of bond strengths supplied by COHP analysis; representative statistics regarding structure in terms of atomic configurations achieved with classical molecular dynamics simulations; and the smooth overlap of atomic positions (SOAP) descriptor. The study is supplemented by an application of that ML model under the scope of mechanical loading; in which the resulting overview of chemical bond strengths revealed a chemical/structural heterogeneity that is in line with the tendency to bond exchange verified for atomic local environments. The encouraging results pave the way towards alternative approaches applicable in plenty of other contexts in which atom categorization (from the perspective of chemical bonds) plays a key role.

cond-mat.mtrl-sci↗

arXiv2011

{\it Ab initio} $^{27}Al$ NMR chemical shifts and quadrupolar parameters for $Al_2O_3$ phases and their precursors

The Gauge-Including Projector Augmented Wave (GIPAW) method, within the Density Functional Theory (DFT) Generalized Gradient Approximation (GGA) framework, is applied to compute solid state NMR parameters for $^{27}Al$ in the $α$, $θ$, and $κ$ aluminium oxide phases and their gibbsite and boehmite precursors. The results for well-established crystalline phases compare very well with available experimental data and provide confidence in the accuracy of the method. For $γ$-alumina, four structural models proposed in the literature are discussed in terms of their ability to reproduce the experimental spectra also reported in the literature. Among the considered models, the $Fd\bar{3}m$ structure proposed by Paglia {\it et al.} [Phys. Rev. B {\bf 71}, 224115 (2005)] shows the best agreement. We attempt to link the theoretical NMR parameters to the local geometry. Chemical shifts depend on coordination number but no further correlation is found with geometrical parameters. Instead our calculations reveal that, within a given coordination number, a linear correlation exists between chemical shifts and Born effective charges.

cond-mat.mtrl-sci↗