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@PHDTHESIS{Brder:891865,
author = {Bröder, Jens},
title = {{H}igh-throughput {A}ll-{E}lectron {D}ensity {F}unctional
{T}heory {S}imulations for a {D}ata-driven {C}hemical
{I}nterpretation of {X}-ray {P}hotoelectron {S}pectra},
volume = {229},
school = {RWTH Aachen},
type = {Dissertation},
address = {Jülich},
publisher = {Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag},
reportid = {FZJ-2021-01785},
isbn = {978-3-95806-526-0},
series = {Schriften des Forschungszentrums Jülich. Reihe
Schlüsseltechnologien / Key Technologies},
pages = {viii, 169, XL S.},
year = {2021},
note = {Dissertation, RWTH Aachen, 2020},
abstract = {Enabling computer-driven materials design to find and
create materials with advanced propertiesfromthe 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-through put simulations
and their data. Basic and advanced workflows are implemented
in an open source Pythonpackage AiiDA-FLEUR, especially to
calculate properties for the chemical analysis of
X-rayphotoemission 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
fittingmethod driven by data from ab initio simulations. For
complex multi-phase spectra this proposedevaluation 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-Wand
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 = {PGI-1 / IAS-1 / JARA-FIT / JARA-HPC},
cid = {I:(DE-Juel1)PGI-1-20110106 / I:(DE-Juel1)IAS-1-20090406 /
$I:(DE-82)080009_20140620$ / $I:(DE-82)080012_20140620$},
pnm = {521 - Quantum Materials (POF4-521)},
pid = {G:(DE-HGF)POF4-521},
typ = {PUB:(DE-HGF)3 / PUB:(DE-HGF)11},
urn = {urn:nbn:de:0001-2021052737},
url = {https://juser.fz-juelich.de/record/891865},
}