A deconstructive analysis of charge-transfer and electrostatic field fluctuations to supplement first-principles modeling of disordered metals
ORAL
Abstract
High entropy alloys present a new class of disordered metals with hopeful applications in the next generation of materials and technology. However, much of the core physics underlying these and other, more generic forms of disordered matter remain the subject of ongoing inquiry. We thus present a minimal working model to describe random fluctuations in electronic charge and electrostatic "Madelung" field configurations in disordered metals. This work reveals both the nature and microscopic origins of these statistical qualities; it also suggests possible avenues for extending modern first-principles approaches to disorder that currently lack these features (e.g. conventional KKR-CPA). In our theory, disorder and interelectron Coulomb repulsion are incorporated in a standard perturbative manner, as is appropriate when simulating metallic alloys. The problem is then reformulated using a self-consistent linear response framework, which is capable of reproducing the same qualitative statistical trends obtained in more comprehensive treatments of disorder (e.g. LSMS) as we also show here. Our work may therefore bridge the gap between physical accuracy and computational affordability in first-principles disorder modeling and answer long-standing questions faced by the disordered materials community.
* The ab initio calculations in this work are based on open-source ab initio software package MuST, a project supported in part by NSF Office of Advanced Cyberinfrastructure and the Division of Materials Research within the NSF Directorate of Mathematical and Physical Sciences under Award Nos. 1931367 (HT), 1931445 (KT), and 1931525 (YW).
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Presenters
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Wai-Ga D Ho
Florida State University
Authors
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Wai-Ga D Ho
Florida State University
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Wasim R Mondal
Middle Tennessee State University
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Hanna Terletska
Middle Tennessee State University
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Ka Ming Tam
Louisiana State University
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Mariia Karabin
Oak Ridge National Lab
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Markus Eisenbach
Oak Ridge National Laboratory
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Yang Wang
Pittsburgh Supercomput Ctr
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Vladimir Dobrosavljevic
Florida State University