Towards the prediction of properties in large clusters of ionic liquids with quantum chemical methods
thesis
posted on 2020-09-11, 07:01 authored by ZOE LUISA ELEANOR SEEGERIonic liquids have many potential applications such as a green alternative to electrolytes in batteries. This thesis develops computational models that can be used to predict their properties such that task-specific ionic liquids can be identified.
History
Campus location
AustraliaPrincipal supervisor
Katya PasAdditional supervisor 1
Jason RigbyYear of Award
2020Department, School or Centre
ChemistryCourse
Doctor of PhilosophyDegree Type
DOCTORATEFaculty
Faculty of ScienceUsage metrics
Keywords
DFTdensity functional theoryMP2benchmarkingoptimizationclustersionic liquidsDLPNODLPNO-CCSD(T)proticaproticdomain-based local pair natural orbitalcoupled clusterbenchmarkCCSD(T)fragment molecular orbitalfmosrs-mp2Three-Body Effectstwo-body effectsdispersioninteraction energyintermolecular forcesmachine learningclusteringglobal minimumlocal minimapotential energy surfacemolecular dynamicsopls-aalammpsAgglomerative clusteringionsQuantum ChemistryComputational Chemistry
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