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@ARTICLE{Neumann:587556,
author = {Neumann, Matthias and Gräfensteiner, Phillip and Santos de
Oliveira, Cristine and Martins-Schalinski, Juliana and
Koppka, Sharon and Enke, Dirk and Huber, Patrick and
Schmidt, Volker},
title = {{T}he {M}orphology of {N}anoporous {G}lass: {S}tochastic
3{D} {M}odeling, {S}tereology and the {I}nfluence of {P}ore
{W}idth},
journal = {Physical review materials},
volume = {8},
number = {4},
issn = {2475-9953},
address = {College Park, MD},
publisher = {APS},
reportid = {PUBDB-2023-04372},
pages = {045605},
year = {2024},
abstract = {Excursion sets of Gaussian random fields are used to model
the three-dimensional (3D) morphology of differently
manufactured porous glasses (PGs), which vary with respect
to their mean pore widths measured by mercury intrusion
porosimetry. The stochastic 3D model is calibrated by means
of volume fractions and two-point coverage probability
functions estimated from tomographic image data. Model
validation is performed by comparing model realizations and
image data in terms of morphological descriptors which are
not used for model fitting. For this purpose, we consider
mean geodesic tortuosity and constrictivity of the pore
space, quantifying the length of the shortest transportation
paths and the strength of bottleneck effects, respectively.
Additionally, a stereological approach for parameter
estimation is presented, i.e., the 3D model is calibrated
using merely two-dimensional (2D) cross-sections of the 3D
image data. Doing so, on average, a comparable goodness of
fit is achieved as well. The variance of the calibrated
model parameters is discussed, which is estimated on the
basis of randomly chosen, individual 2D cross-sections.
Moreover, interpolating between the model parameters
calibrated to differently manufactured glasses enables the
predictive simulation of virtual but realistic PGs with mean
pore widths that have not yet been manufactured. The
predictive power is demonstrated by means of
cross-validation. Using the presented approach,
relationships between parameters of the manufacturing
process and descriptors of the resulting morphology of PGs
are quantified, which opens possibilities for an efficient
optimization of the underlying manufacturing process.},
cin = {CIMMS},
ddc = {530},
cid = {I:(DE-H253)CIMMS-20211022},
pnm = {632 - Materials – Quantum, Complex and Functional
Materials (POF4-632) / SFB 986 B07 - Polymere in
grenzflächenbestimmten Geometrien: Struktur, Dynamik und
Funktion an planaren und in porösen Hybridsystemen (B07)
(318019437) / SFB 986 C10 - Photonische Metamaterialien mit
anpassbarer und schaltbarer Anisotropie durch
Funktionalisierung von porösen Festkörpern mit
Flüssigkristallen (C10*) (445052466) / DFG project
G:(GEPRIS)390874152 - EXC 2154: POLiS - Post Lithium Storage
Cluster of Excellence (390874152)},
pid = {G:(DE-HGF)POF4-632 / G:(GEPRIS)318019437 /
G:(GEPRIS)445052466 / G:(GEPRIS)390874152},
experiment = {EXP:(DE-MLZ)NOSPEC-20140101},
typ = {PUB:(DE-HGF)16},
UT = {WOS:001218097200004},
doi = {10.1103/PhysRevMaterials.8.045605},
url = {https://bib-pubdb1.desy.de/record/587556},
}