Building Materials Genome from Ground-State Configuration to Engineering Advance
Zi-Kui Liu

TL;DR
This paper introduces a multi-scale entropy approach combining ground- and non-ground-state configurations to accurately predict the free energy of material phases, advancing materials genome understanding.
Contribution
It proposes a novel entropy-based method that integrates DFT-calculated configurations to improve phase property predictions at finite temperatures.
Findings
Successfully predicts free energies of phases using combined configurations.
Demonstrates improved accuracy over traditional ground-state-only methods.
Provides a framework for linking microscopic configurations to macroscopic properties.
Abstract
Individual phases are commonly considered as the building blocks of materials. However, the accurate theoretical prediction of properties of individual phases remains elusive. The top-down approach by decoding genomic building blocks of individual phases from experimental observations is non-unique. The density functional theory (DFT), as the state-of-the-art solution of quantum mechanics, prescribes the existence of a ground-state configuration at zero K for a given system. It is self-evident that the ground-state configuration alone is insufficient to describe a phase at finite temperatures as symmetry-breaking non-ground-state configurations are excited statistically at temperatures above zero K. Our multi-scale entropy approach (recently terms as Zentropy theory) postulates that the entropy of a phase is composed of the sum of the entropy of each configuration weighted by its…
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Taxonomy
TopicsMachine Learning in Materials Science
