Data-driven PSP linkages for atomistic datasets
Author(s)
Gomberg, Joshua A.
Advisor(s)
Editor(s)
Collections
Supplementary to:
Permanent Link
Abstract
For a variety of materials, atomic-scale modeling techniques are commonly employed as a means of investigating fundamental properties, including both structural and chemical responses. While force-field based calculations are significantly less computationally expensive than their quantum-mechanical counterparts, the datasets often investigated are large in size (10^3 – 10^9 atoms) and high-dimensional, and thus cumbersome for use in multi-scale models. The development of quantitative “process-structure-property” (PSP) linkages for atomistic simulations presents a powerful route to convert atomistic simulation data into actionable knowledge. Here, a framework is presented for quantifying structure from these simulations in full- and reduced-dimensional form, and a series of protocols are developed for establishing regression models for process-structure and structure-property linkages.
Sponsor
Date
2017-05-23
Extent
Resource Type
Text
Resource Subtype
Dissertation