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A Deeper Understanding of Material P...

Repa, Gil M.,

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A Deeper Understanding of Material Properties Through Computational Model Development /

Record Type:	Electronic resources : Monograph/item
Title/Author:	A Deeper Understanding of Material Properties Through Computational Model Development // Gil M Repa.
Author:	Repa, Gil M.,
Description:	1 electronic resource (150 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 86-01, Section: B.
Contained By:	Dissertations Abstracts International86-01B.
Subject:	Chemistry. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31237325
ISBN:	9798383200667

A Deeper Understanding of Material Properties Through Computational Model Development /
Repa, Gil M.,

A Deeper Understanding of Material Properties Through Computational Model Development /Gil M Repa. - 1 electronic resource (150 pages)

Source: Dissertations Abstracts International, Volume: 86-01, Section: B.

The pace of materials development can be significantly increased by computational models that accurately capture the characteristics of experimental materials. While advances in computational architecture have enabled researchers to calculate the properties of pure materials with high fidelity, it is often disorder of the perfect crystal that gives rise to technologically relevant properties. This thesis aims to contribute a robust modeling framework for disordered materials by developing improved criteria to access metal oxide point defects, interfaces, and nanoparticles using theories that are efficient and easily generalizable. Insights into technologically relevant materials are developed, including discovery and assignment of spectroscopic signals to new defect geometries in doped SrTiO3 , identification of ring-like atomic motifs in amorphous Al2O3 responsible for experimentally observed electronic properties, and combination molecular dynamics and density functional theory approaches to produce more realistic amorphous TiO2 nanoparticles and interfaces.

English

ISBN: 9798383200667Subjects--Topical Terms:

516420
Chemistry.
Subjects--Index Terms:

Amorphous materials

A Deeper Understanding of Material Properties Through Computational Model Development /
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100 1 $a Repa, Gil M., $e author. $0 (orcid)0000-0003-4944-4019 $3 3817115
245 1 2 $a A Deeper Understanding of Material Properties Through Computational Model Development / $c Gil M Repa.
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300 $a 1 electronic resource (150 pages)
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500 $a Source: Dissertations Abstracts International, Volume: 86-01, Section: B.
500 $a Advisors: Fredin, Lisa A. Committee members: Young, Elizabeth R.; Ferguson, Greg; Rangarajan, Srinivas.
502 $b Ph.D. $c Lehigh University $d 2024.
520 $a The pace of materials development can be significantly increased by computational models that accurately capture the characteristics of experimental materials. While advances in computational architecture have enabled researchers to calculate the properties of pure materials with high fidelity, it is often disorder of the perfect crystal that gives rise to technologically relevant properties. This thesis aims to contribute a robust modeling framework for disordered materials by developing improved criteria to access metal oxide point defects, interfaces, and nanoparticles using theories that are efficient and easily generalizable. Insights into technologically relevant materials are developed, including discovery and assignment of spectroscopic signals to new defect geometries in doped SrTiO3 , identification of ring-like atomic motifs in amorphous Al2O3 responsible for experimentally observed electronic properties, and combination molecular dynamics and density functional theory approaches to produce more realistic amorphous TiO2 nanoparticles and interfaces.
546 $a English
590 $a School code: 0105
650 4 $a Chemistry. $3 516420
650 4 $a Computational chemistry. $3 3350019
650 4 $a Materials science. $3 543314
650 4 $a Inorganic chemistry. $3 3173556
650 4 $a Nanoscience. $3 587832
653 $a Amorphous materials
653 $a Density functional theory
653 $a Dopants
653 $a Materials chemistry
653 $a Nanoparticles
653 $a Perovskites
690 $a 0485
690 $a 0219
690 $a 0794
690 $a 0488
690 $a 0565
710 2 $a Lehigh University. $b Chemistry. $e degree granting institution. $3 3817116
720 1 $a Fredin, Lisa A. $e degree supervisor.
773 0 $t Dissertations Abstracts International $g 86-01B.
790 $a 0105
791 $a Ph.D.
792 $a 2024
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31237325