Investigations into liquid state physics in energy applications with machine-learning interatomic potentials: An active learning framework utilizing subascent

Lee, Shao-Chun

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University of Illinois at Urbana-Champaign

Investigations into liquid state physics in energy applications with machine-learning interatomic potentials: An active learning framework utilizing subascent

dc:creator Lee, Shao-Chun

thesis:degree_name Ph.D.

dc:date2024

Abstract

dc:description

Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2026-05-01

Degree

thesis:*

Name thesis:degree_name: Ph.D.
Level thesis:degree_level: Dissertation
Discipline thesis:degree_discipline: Nuclear, Plasma, Radiolgc Engr
Grantor: University of Illinois at Urbana-Champaign
Year dc:date: 2024

Author and committee

dc:creator, dc:contributor.*

Author dc:creator: Lee, Shao-Chun
Contributors dc:contributor: Zhang, Yang
Heuser, Brent J
Curreli, Davide
Schweizer, Kenneth S

Subjects

dc:subject × 6

Rights

dc:rights

Language dc:language: en, eng

Identifiers

dc:identifier.*

Handle dc:identifier: https://hdl.handle.net/2142/124663
OAI identifier oai:identifier: oai:www.ideals.illinois.edu:2142/124663

Chain of custody

source

Harvested from: University of Illinois - Urbana-Champaign
Base URL: www.ideals.illinois.edu/oai-pmh
Last updated: 2026-07-22
Source record: OAI-PMH GetRecord

related terms

citation

Lee, Shao-Chun. Investigations into liquid state physics in energy applications with machine-learning interatomic potentials: An active learning framework utilizing subascent. Dissertation thesis, University of Illinois at Urbana-Champaign, 2024. https://hdl.handle.net/2142/124663

Investigations into liquid state physics in energy applications with machine-learning interatomic potentials: An active learning framework utilizing subascent

Abstract

Degree

Author and committee

Subjects

Rights

Identifiers

Chain of custody

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