Data-driven PSP linkages for atomistic datasets

Gomberg, Joshua A.

Title:

Data-driven PSP linkages for atomistic datasets

dc.contributor.advisor	Kalidindi, Surya R.
dc.contributor.author	Gomberg, Joshua A.
dc.contributor.committeeMember	McDowell, David L.
dc.contributor.committeeMember	Li, Mo
dc.contributor.committeeMember	Haaland, Benjamin
dc.contributor.committeeMember	Garmestani, Hamid
dc.contributor.department	Materials Science and Engineering
dc.date.accessioned	2018-08-20T15:28:03Z
dc.date.available	2018-08-20T15:28:03Z
dc.date.created	2017-08
dc.date.issued	2017-05-23
dc.date.submitted	August 2017
dc.date.updated	2018-08-20T15:28:03Z
dc.description.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.
dc.description.degree	Ph.D.
dc.format.mimetype	application/pdf
dc.identifier.uri	http://hdl.handle.net/1853/60125
dc.language.iso	en_US
dc.publisher	Georgia Institute of Technology
dc.subject	Grain boundaries
dc.subject	Materials informatics
dc.subject	Molecular dynamics
dc.subject	Pair correlation function
dc.subject	Principal component analysis
dc.subject	Process-structure-property linkage
dc.subject	Interatomic potentials
dc.subject	Multiscale modeling
dc.title	Data-driven PSP linkages for atomistic datasets
dc.type	Text
dc.type.genre	Dissertation
dspace.entity.type	Publication
local.contributor.advisor	Kalidindi, Surya R.
local.contributor.corporatename	School of Materials Science and Engineering
local.contributor.corporatename	College of Engineering
relation.isAdvisorOfPublication	e5ad79b6-4761-4f35-86c3-0890d432fe44
relation.isOrgUnitOfPublication	21b5a45b-0b8a-4b69-a36b-6556f8426a35
relation.isOrgUnitOfPublication	7c022d60-21d5-497c-b552-95e489a06569
thesis.degree.level	Doctoral