Hauptseite > Publikationsdatenbank > High-Performance Computing Approach to Hybrid Functionals in the All-Electron DFT Code FLEUR > print

001     909289
005     20220906191327.0
020 _ _ |a 978-3-95806-639-7
024 7 _ |a 2128/31792
|2 Handle
037 _ _ |a FZJ-2022-03102
100 1 _ |a Redies, Matthias
|0 P:(DE-Juel1)172666
|b 0
|e Corresponding author
245 _ _ |a High-Performance Computing Approach to Hybrid Functionals in the All-Electron DFT Code FLEUR
|f - 2022-06-22
260 _ _ |a Jülich
|c 2022
|b Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag
300 _ _ |a xi, 109
336 7 _ |a Output Types/Dissertation
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336 7 _ |a DISSERTATION
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336 7 _ |a PHDTHESIS
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336 7 _ |a Thesis
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336 7 _ |a Dissertation / PhD Thesis
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336 7 _ |a doctoralThesis
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490 0 _ |a Schriften des Forschungszentrums Jülich Reihe Schlüsseltechnologien / Key Technologies
|v 257
502 _ _ |a Dissertation, RWTH Aachen University, 2022
|c RWTH Aachen University
|b Dissertation
|d 2022
520 _ _ |a Virtual 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
536 _ _ |a 5211 - Topological Matter (POF4-521)
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856 4 _ |u https://juser.fz-juelich.de/record/909289/files/Schluesseltech_257.pdf
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909 C O |o oai:juser.fz-juelich.de:909289
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910 1 _ |a Forschungszentrum Jülich
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|v Quantum Materials
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914 1 _ |y 2022
915 _ _ |a OpenAccess
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915 _ _ |a Creative Commons Attribution CC BY 4.0
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920 _ _ |l yes
920 1 _ |0 I:(DE-Juel1)PGI-1-20110106
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980 _ _ |a I:(DE-Juel1)IAS-1-20090406
980 _ _ |a I:(DE-82)080009_20140620
980 _ _ |a I:(DE-82)080012_20140620
980 1 _ |a FullTexts

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