000909289 001__ 909289
000909289 005__ 20220906191327.0
000909289 020__ $$a978-3-95806-639-7
000909289 0247_ $$2Handle$$a2128/31792
000909289 037__ $$aFZJ-2022-03102
000909289 1001_ $$0P:(DE-Juel1)172666$$aRedies, Matthias$$b0$$eCorresponding author
000909289 245__ $$aHigh-Performance Computing Approach to Hybrid Functionals in the All-Electron DFT Code FLEUR$$f - 2022-06-22
000909289 260__ $$aJülich$$bForschungszentrum Jülich GmbH Zentralbibliothek, Verlag$$c2022
000909289 300__ $$axi, 109
000909289 3367_ $$2DataCite$$aOutput Types/Dissertation
000909289 3367_ $$0PUB:(DE-HGF)3$$2PUB:(DE-HGF)$$aBook$$mbook
000909289 3367_ $$2ORCID$$aDISSERTATION
000909289 3367_ $$2BibTeX$$aPHDTHESIS
000909289 3367_ $$02$$2EndNote$$aThesis
000909289 3367_ $$0PUB:(DE-HGF)11$$2PUB:(DE-HGF)$$aDissertation / PhD Thesis$$bphd$$mphd$$s1662437763_14098
000909289 3367_ $$2DRIVER$$adoctoralThesis
000909289 4900_ $$aSchriften des Forschungszentrums Jülich Reihe Schlüsseltechnologien / Key Technologies$$v257
000909289 502__ $$aDissertation, RWTH Aachen University, 2022$$bDissertation$$cRWTH Aachen University$$d2022
000909289 520__ $$aVirtual materials design attempts to use computational methods to discover new materials with superior properties within the vast space of all conceivable materials. Density-functional theory (DFT) is central to this field, enabling scientists to predict material properties from first principles, i.e. without relying on external parameters or experimental values. While standard DFT is capable of predicting many materials with satisfying accuracy, it struggles with some properties such as details of the electronic structure or certain material classes, e.g. materials exhibiting strongly correlated electrons. This has created a need for methods with greater predictive power. One such class of methods are hybrid exchange-correlation functionals which combine the exact Hartree-Fock exchange with local exchange-correlation functionals, resulting in highly accurate predictions for many insulating or semiconductor materials. However, the computational cost of hybrid functionals increases rapidly with system size and limits their application to small systems. This thesis aims to solve the computational challenge posed by hybrid functionals in large systems by utilizing the massive computational power of today’s supercomputers
000909289 536__ $$0G:(DE-HGF)POF4-5211$$a5211 - Topological Matter (POF4-521)$$cPOF4-521$$fPOF IV$$x0
000909289 8564_ $$uhttps://juser.fz-juelich.de/record/909289/files/Schluesseltech_257.pdf$$yOpenAccess
000909289 909CO $$ooai:juser.fz-juelich.de:909289$$popenaire$$popen_access$$pVDB$$pdriver$$pdnbdelivery
000909289 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)172666$$aForschungszentrum Jülich$$b0$$kFZJ
000909289 9131_ $$0G:(DE-HGF)POF4-521$$1G:(DE-HGF)POF4-520$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5211$$aDE-HGF$$bKey Technologies$$lNatural, Artificial and Cognitive Information Processing$$vQuantum Materials$$x0
000909289 9141_ $$y2022
000909289 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
000909289 915__ $$0LIC:(DE-HGF)CCBY4$$2HGFVOC$$aCreative Commons Attribution CC BY 4.0
000909289 920__ $$lyes
000909289 9201_ $$0I:(DE-Juel1)PGI-1-20110106$$kPGI-1$$lQuanten-Theorie der Materialien$$x0
000909289 9201_ $$0I:(DE-Juel1)IAS-1-20090406$$kIAS-1$$lQuanten-Theorie der Materialien$$x1
000909289 9201_ $$0I:(DE-82)080009_20140620$$kJARA-FIT$$lJARA-FIT$$x2
000909289 9201_ $$0I:(DE-82)080012_20140620$$kJARA-HPC$$lJARA - HPC$$x3
000909289 980__ $$aphd
000909289 980__ $$aVDB
000909289 980__ $$aUNRESTRICTED
000909289 980__ $$abook
000909289 980__ $$aI:(DE-Juel1)PGI-1-20110106
000909289 980__ $$aI:(DE-Juel1)IAS-1-20090406
000909289 980__ $$aI:(DE-82)080009_20140620
000909289 980__ $$aI:(DE-82)080012_20140620
000909289 9801_ $$aFullTexts