7 citations · 16 across the 20 of their papers we have counts for
22 papers
Tracking the Emergence and Persistence of Abnormal Grain Growth in an Aluminum Alloy using Diffraction-Contrast Tomography
Helmuth-André Schulz-Harder, Karolína Gutbrod, Madlen Atzen +12
Abnormal grain growth is inherently three-dimensional, making 3D tracking of grain evolution essential for understanding its underlying mechanisms. This study combines synchrotron-…
Statistical analysis of virion-cell interactions mediated by peptide nanofibrils and peptide amphiphiles using STEM tomography
Philipp Rieder, Julia La Roche, Orkun Furat +8
Peptide nanofibrils (PNFs) and peptide amphiphiles (PAs) are promising tools for enhancing viral transduction and gene transfer. However, quantitative insight into how their supram…
Virtual materials testing of ASSB cathodes combining AI-based stochastic 3D modeling and numerical simulations
Anina Dufter, Sabrina Weber, Orkun Furat +7
The performance of all-solid-state battery (ASSB) cathodes strongly depends on their microstructure. Optimizing the cathode morphology can therefore enhance effective macroscopic p…
Physics-informed Neural Operators for Predicting 3D Electromagnetic Fields Transformed by Metasurfaces
Orkun Furat, Vinay Chakravarthi Gogineni, Henrik Bindslev +1
Metasurfaces, typically realized as arrays of nanopillars, transform electromagnetic (EM) fields depending on their geometry and spatial arrangement. For solving the inverse proble…
Fitting Generalized Power Diagrams to 3D Image Data: A Prerequisite for Virtual Materials Testing
Andreas Alpers, Orkun Furat, Christian Jung +4
This paper reviews algorithmic and modeling approaches for fitting generalized power diagrams to three-dimensional image data, a key step in virtual materials testing (VMT). Beyond…
Quantitative characterization of hydrophobic agglomeration at different mixing intensities using a copula-based probabilistic modeling approach
Niklas Eiermann, Orkun Furat, Jan Nicklas +2
The agglomeration of small poorly wetted alumina particles in a stirred tank is investigated. For different experimental conditions, two bivariate probability densities for the are…
Statistical learning of structure-property relationships for transport in porous media, using hybrid AI modeling
Somayeh Hosseinhashemi, Philipp Rieder, Orkun Furat +5
The 3D microstructure of porous media, such as electrodes in lithium-ion batteries or fiber-based materials, significantly impacts the resulting macroscopic properties, including e…
Stereological 3D modeling of nano-scale catalyst particles using TEM projections
Lukas Fuchs, Kerstin Wein, Jens Friedland +3
Catalysis, particularly heterogeneous catalysis, is crucial in the chemical industry and energy storage. Approximately 80% of all chemical products produced by heterogeneous cataly…
Generative adversarial framework to calibrate excursion set models for the 3D morphology of all-solid-state battery cathodes
Orkun Furat, Sabrina Weber, Johannes Schubert +7
This paper presents a computational method for generating virtual 3D morphologies of functional materials using low-parametric stochastic geometry models, i.e., digital twins, cali…
Stochastic 3D reconstruction of cracked polycrystalline NMC particles using 2D SEM data
Philipp Rieder, Orkun Furat, Francois L. E. Usseglio-Viretta +5
Li-ion battery performance is strongly influenced by their cathodes' properties and consequently by the 3D microstructure of the particles the cathodes are comprised of. During cal…
A length-scale insensitive cohesive phase-field interface model: application to concurrent bulk and interface fracture simulation in Lithium-ion battery materials
Wan-Xin Chen, Xiang-Long Peng, Jian-Ying Wu +3
A new cohesive phase-field (CPF) interface fracture model is proposed on the basis of the Euler-Lagrange equation of the phase-field theory and the interface fracture energy check…
Generating multi-scale NMC particles with radial grain architectures using spatial stochastics and GANs
Lukas Fuchs, Orkun Furat, Donal P. Finegan +6
Understanding structure-property relationships of Li-ion battery cathodes is crucial for optimizing rate-performance and cycle-life resilience. However, correlating the morphology…
Virtual reassembling of 3D fragments for the data-driven analysis of fracture mechanisms in composite materials
Thomas Wilhelm, Trang Thu Võ, Orkun Furat +2
This paper introduces a novel method for characterizing fracture mechanisms in composite materials using 3D image data gained by computed tomography (CT) measurements. In mineral l…
Investigating the influence of particle size and shape on froth flotation based benefication of lithium-rich minerals in slags
Franziska Strube, Thomas Wilhelm, Johanna Sygusch +4
The demand for lithium, as well as other critical resources, needed for electrochemical energy storage is expected to grow significantly in the future. Slags obtained from pyrometa…
Investigating the multidimensional separation behavior of particles in a cyclosizer setting -- A case study on calcite, fluorite and magnesite
Johanna Sygusch, Thomas Wilhelm, Orkun Furat +2
Particle separation is typically investigated regarding one particulate property only. Virtually all separation processes, however, act on various particle properties in different…
Application of multivariate Tromp functions for evaluating the joint impact of particle size, shape and wettability on the separation of ultrafine particles via flotation
Johanna Sygusch, Thomas Wilhelm, Orkun Furat +3
Froth flotation predominantly separates particles according to their differences in wettability. However, other particle properties such as size, shape or density significantly inf…
An AFM-based approach for quantification of guest particle deformation during mechano-fusion
Phillip Gräfensteiner, Judith Friebel, Lisa Ditscherlein +3
During the mechano-fusion process for dry particle coating, (hetero)-aggregates are formed consisting of host particles which are coated by smaller guest particles. During this pro…
Determination of droplet size from wide-angle light scattering image data using convolutional neural networks
Tom Kirstein, Simon Aßmann, Orkun Furat +2
Wide-angle light scattering (WALS) offers the possibility of a highly temporally and spatially resolved measurement of droplets in spray-based methods for nanoparticle synthesis. T…
Using convolutional neural networks for stereological characterization of 3D hetero-aggregates based on synthetic STEM data
Lukas Fuchs, Tom Kirstein, Christoph Mahr +5
The structural characterization of hetero-aggregates in 3D is of great interest, e.g., for deriving process-structure or structure-property relationships. However, since 3D imaging…
Multidimensional characterization of particle morphology and mineralogical composition using CT data and R-vine copulas
Orkun Furat, Tom Kirstein, Thomas Leißner +4
Computed tomography (CT) can capture volumes large enough to measure a statistically meaningful number of micron-sized particles with a sufficiently good resolution to allow for th…
Mixed moving average field guided learning for spatio-temporal data
Imma Valentina Curato, Orkun Furat, Lorenzo Proietti +1
Influenced mixed moving average fields are a versatile modeling class for spatio-temporal data. However, their predictive distribution is not generally known. Under this modeling a…
Description of ore particles from XMT images, supported by SEM-based image analysis
Orkun Furat, Thomas Leißner, Ralf Ditscherlein +6
In this paper, 3D image data of ore particle systems is investigated. By combining X-ray micro tomography (XMT) with scanning electron microscope (SEM) based image analysis additio…