TY  - THES
AU  - Redies, Matthias
TI  - High-Performance Computing Approach to Hybrid Functionals in the All-Electron DFT Code FLEUR
VL  - 257
PB  - RWTH Aachen University
VL  - Dissertation
CY  - Jülich
M1  - FZJ-2022-03102
SN  - 978-3-95806-639-7
T2  - Schriften des Forschungszentrums Jülich Reihe Schlüsseltechnologien / Key Technologies
SP  - xi, 109
PY  - 2022
N1  - Dissertation, RWTH Aachen University, 2022
AB  - 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
LB  - PUB:(DE-HGF)3 ; PUB:(DE-HGF)11
UR  - https://juser.fz-juelich.de/record/909289
ER  -