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@PHDTHESIS{Brder:816617,
author = {Bröder, Jens},
othercontributors = {Blügel, Stefan and Mazzarello, Riccardo and Linsmeier,
Christian},
title = {{H}igh-throughput all-electron density functional theory
simulations for a data-driven chemical interpretation of
{X}-ray photoelectron spectra},
volume = {229},
school = {RWTH Aachen University},
type = {Dissertation},
address = {Jülich},
publisher = {Forschungszentrum Jülich GmbH, Zentralbibliothek, Verlag},
reportid = {RWTH-2021-03326},
series = {Schriften des Forschungszentrums Jülich. Reihe
Schlüsseltechnologien/ key technologies},
pages = {1 Online-Ressource (viii, 169, XL Seiten) : Illustrationen,
Diagramme},
year = {2021},
note = {Druckausgabe: 2021. - Onlineausgabe: 2021. - Auch
veröffentlicht auf dem Publikationsserver der RWTH Aachen
University; Dissertation, RWTH Aachen University, 2020},
abstract = {Enabling computer-driven materials design to find and
create materials with advanced properties from the enormous
haystack of material phase space is a worthy goal for
humanity. Most high-technologies, for example in the energy
or health sector, strongly depend on advanced tailored
materials. Since conventional research and screening of
materials is rather slow and expensive, being able to
determine material properties on the computer poses a
paradigm shift. For the calculation of properties for pure
materials on the nano scale ab initio methods based on the
theory of quantum mechanics are well established. Density
Functional Theory (DFT) is such a widely applied method from
first principles with high predictive power. To screen
through larger sets of atomic configurations physical
property calculation processes need to be robust and
automated. Automation is achieved through the deployment of
advanced frameworks which manage many workflows while
tracking the provenance of data and calculations. Through
workflows, which are essential property calculator
procedures, a high-level automation environment is
achievable and accumulated knowledge can be reused by
others. Workflows can be complex and include multiple
programs solving problems over several physical length
scales. In this work, the open source all-electron DFT
program FLEUR implementing the highly accurate
Full-potential Linearized Augmented Plane Wave (FLAPW)
method is connected and deployed through the open source
Automated Interactive Infrastructure and Database for
Computational Science (AiiDA) framework to achieve
automation. AiiDA is a Python framework which is capable of
provenance tracking millions of high-throughput simulations
and their data. Basic and advanced workflows are implemented
in an open source Python package AiiDA-FLEUR, especially to
calculate properties for the chemical analysis of X-ray
photoemission spectra. These workflows are applied on a wide
range of materials, in particular on most known metallic
binary compounds. The chemical-phase composition and other
material properties of a surface region can be understood
through the careful chemical analysis of high-resolution
X-ray photoemission spectra. The spectra evaluation process
is improved through the development of a fitting method
driven by data from ab initio simulations. For complex
multi-phase spectra this proposed evaluation process is
expected to have advantages over the widely applied
conventional methods. The spectra evaluation process is
successfully deployed on well-behaved spectra of materials
relevant for the inner wall (blanket and divertor)
plasma-facing components of a nuclear fusion reactor. In
particular, the binary beryllium systems Be-Ti, Be-W and
Be-Ta are investigated. Furthermore, different approaches to
calculate spectral properties like chemical shifts and
binding energies are studied and benchmarked against the
experimental literature and data from the NIST X-ray
photoelectron spectroscopy database.},
cin = {137510 / 130000},
ddc = {530},
cid = {$I:(DE-82)137510_20140620$ / $I:(DE-82)130000_20140620$},
pnm = {MaX - Materials design at the eXascale (676598) / MaX -
MAterials design at the eXascale. European Centre of
Excellence in materials modelling, simulations, and design
(824143)},
pid = {G:(EU-Grant)676598 / G:(EU-Grant)824143},
typ = {PUB:(DE-HGF)11 / PUB:(DE-HGF)3},
doi = {10.18154/RWTH-2021-03326},
url = {https://publications.rwth-aachen.de/record/816617},
}
Gast ::