Calculations of planar defect energies in substitutional alloys using the special-quasirandom-structure approach

Abstract

A method is described for calculating the energetics of planar defects in alloys based on the special-quasirandom-structure (SQS) approach. We examine the accuracy of the approach employing atomistic calculations based on a classical embedded-atom-method (EAM) interatomic potential for hexagonal close packed (hcp) alloys, for which benchmark results can be obtained by direct configurational averaging. The results of these calculations demonstrate that the SQS-based approach can be employed to derive the concentration dependence of the energies of twin boundaries, unstable stacking faults and surfaces to within an accuracy of approximately 10 %. The SQS considered in this study contain up to 72 atoms and hence are small enough to be considered in first-principles density-functional-theory (DFT) based calculations. The application of the SQS-based approach in direct DFT-based calculations is demonstrated in a study of the concentration dependence of interfacial energies for {1121} twins in hcp Ti-Al alloys.

Thermodynamic and Ab Initio Design of Multicomponent Alloys Based on (Fe50Mn30Co10Cr10)-xBx (x = 0, 5, 7, 10, and 15 at.%)

“…Solid solution modelling was applied to obtain a random structure with the optimal chemical disorder arrangement [ 43 ]. This was performed using the special quasi-random structures (SQS) methodology [ 70 , 71 , 72 , 73 , 74 , 75 ] implemented in an alloy theoretic automated toolkit (ATAT) program [ 76 ]. An objective function was minimized, taking into account (i) a supercell size of 60 atoms, (ii) a chemical composition of (Fe 50 Mn 30 Cr 10 Co 10 )-xBx (x = 0, 5, 7, 10, and 15 at.% associated with alloy-B0, alloy-B5, alloy-B7, alloy-B10, and alloy-B15, respectively), and (iii) a third nearest-neighbor distance for FCC and HCP structures ranging from 3.0 to 6.0 Å.…”

Thermodynamic Properties as a Function of Temperature of AlMoNbV, NbTaTiV, NbTaTiZr, AlNbTaTiV, HfNbTaTiZr, and MoNbTaVW Refractory High-Entropy Alloys from First-Principles Calculations

“…Furthermore, when defects are present, it is typically necessary to average several atomic configuration permutations (meaning replacing all A atoms with B atoms, B atoms with C atoms, etc.) of the SQS together to capture the variations in the local environment surrounding the defect [22,24,[34][35][36][37]. Other methods exist, such as random supercell sampling [20,38] and small sets of ordered structures (SSOSs) [39], but they are not widely adopted in the literature.…”

Genetic Algorithms and Machine Learning for Predicting Surface Composition, Structure, and Chemistry: A Historical Perspective and Assessment

“…The lineage from Chang remained mostly separate from Smith except for two references: Investigations of surface reconstructions by Landree et al in 1997 and a generalized review by Paszkowicz in 2009 summarizing the use of GA across chemistry up until then, which connected most original lineages. During all these developments, GA have found additional uses in chemistry in determining physical properties of bulk materials, − kinetic rate constants, − and parameters for MD simulations. − …”