Recent advances in high-performance computing have resulted in massive databases of materials properties calculated with techniques such as ab initio density functional theory. In fact, some of the largest of such databases have calculations of nearly all distinct, ordered, experimentally-reported compounds. This thesis discusses the application of data in one such database, the Open Quantum Materials Database (OQMD), along three broad fronts. (a) High-throughput materials discovery: prediction of hitherto unreported ternary oxyfluorides and Heusler-based compounds using techniques such as prototype decoration and cluster expansion to generate novel hypothetical structures, in conjunction with convex hull-based phase stability analysis. (b) Fingerprinting the high-pressure materials genome: exploration of the enthalpy landscape of all materials at high-pressure using a simple linear approximation for compound enthalpy, and ambient-pressure energy and volume data in the OQMD; using the framework to predict novel high-pressure-stable phases in ambient-immiscible systems. (c) Network representation of all materials: a top-down view of phase diagrams through the lens of complex network theory, unraveling the complete thermodynamic network of all materials, and using it to extract otherwise-intractable knowledge—a quantitative scale of material reactivity, the "nobility index"— and thereby identifying the noblest materials in nature.

Creator

• Ishwar Hegde, Vinay

DOI

• https://doi.org/10.21985/n2-wprf-he69

Subject

• Materials Science
• Computational physics

Language

• en

Alternate Identifier

• etdadmin_upload_780845
• http://dissertations.umi.com/northwestern:15403

Keyword

• high-pressure
• OQMD
• complex networks
• density functional theory
• high-throughput
• materials discovery

Date created

• 2019-01-01

Resource type

• Dissertation

Rights statement

• In Copyright