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@PHDTHESIS{Beumers:775359,
author = {Beumers, Peter Christoph},
othercontributors = {Bardow, André and Bräuer, Andreas Siegfried},
title = {{P}hysically-based models for the analysis of {R}aman
spectra; 1. {A}uflage},
volume = {23},
school = {RWTH Aachen University},
type = {Dissertation},
address = {Aachen},
publisher = {Wissenschaftsverlag Mainz GmbH},
reportid = {RWTH-2019-12164},
isbn = {978-3-95886-319-4},
series = {Aachener Beiträge zur technischen Thermodynamik},
pages = {1 Online-Ressource (XVII, 107 Seiten) : Illustrationen,
Diagramme},
year = {2019},
note = {Druckausgabe: 2019. - Auch veröffentlicht auf dem
Publikationsserver der RWTH Aachen University 2020;
Dissertation, RWTH Aachen University, 2019},
abstract = {In recent years, spectroscopy has developed into an
increasingly valuable tool to determine the composition of
mixtures; for scientific questions as well as for the
industry. The increasing use of spectroscopy raises the
question how to best use the obtained data. For the analysis
of spectral data, the method of Indirect Hard Modeling (IHM)
has been established besides statistical methods like PLS.
IHM is a nonlinear method that can therefore efficiently
treat nonlinear effects such as peak-shifts. In the present
work, the IHM method is expanded to increase its
applicability. IHM treats nonlinear effects in the spectral
evaluation. Therefore, the direct proportionality between
the concentration and the Raman signal of a component can be
used for calibration. The resulting linear calibration model
allows for reliable extrapolation. Thus, IHM can be used to
study reactive systems, even if only binary subsystems can
be used for calibration. However, thermodynamic systems with
intermediates can so far only be calibrated by using
thermodynamic models. In this work, a method is established
that calibrates a reactive system with intermediates only
based on the reaction mechanism as well as stoichiometry and
electroneutrality. Spectral backgrounds, e.g., fluorescence,
can be treated by a spectral pretreatment or via background
models. However, spectral backgrounds are still a common
source of error in IHM. Derivatives have long been used very
effectively in statistical methods. Therefore, IHM is
adapted so that it becomes possible to evaluate the first
derivative of spectra. The calibration of IHM is mostly
limited to the relative spectral intensities of the involved
components. In the present work, a method is presented that
uses the information in the calibration spectra more
thoroughly. For this purpose, nonlinear effects are
parametrized as a function of concentration. The commonly
used peak profiles do not reflect the physical reality at a
detector very well. As a result, narrow modelled peaks may
change their apparent intensity if they are shifted. To
correct these shortcomings, a new peak model is proposed in
this work that is more closely aligned to the physical
reality of a detector.},
cin = {412110},
ddc = {620},
cid = {$I:(DE-82)412110_20140620$},
typ = {PUB:(DE-HGF)11 / PUB:(DE-HGF)3},
doi = {10.18154/RWTH-2019-12164},
url = {https://publications.rwth-aachen.de/record/775359},
}
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