107 citations · 122 across the 10 of their papers we have counts for
10 papers
Out-of-distribution generalization of deep-learning surrogates for 2D PDE-generated dynamics in the small-data regime
Binh Duong Nguyen, Stefan Sandfeld
Partial differential equations (PDEs) are a central tool for modeling the dynamics of physical, engineering, and materials systems, but high-fidelity simulations are often computat…
Combining unsupervised and supervised learning in microscopy enables defect analysis of a full 4H-SiC wafer
Binh Duong Nguyen, Johannes Steiner, Peter Wellmann +1
Detecting and analyzing various defect types in semiconductor materials is an important prerequisite for understanding the underlying mechanisms as well as tailoring the production…
DISO: A Domain Ontology for Modeling Dislocations in Crystalline Materials
Ahmad Zainul Ihsan, Said Fathalla, Stefan Sandfeld
Crystalline materials, such as metals and semiconductors, nearly always contain a special defect type called dislocation. This defect decisively determines many important material…
Accurate Distances Measures and Machine Learning of the Texture-Property Relation for Crystallographic Textures Represented by One-Point Statistics
Tarek Iraki, Lukas Morand, Norbert Link +2
The crystallographic texture of metallic materials is a key microstructural feature that is responsible for the anisotropic behavior, e.g., important in forming operations. In mate…
Efficient Surrogate Models for Materials Science Simulations: Machine Learning-based Prediction of Microstructure Properties
Binh Duong Nguyen, Pavlo Potapenko, Aytekin Dermici +3
Determining, understanding, and predicting the so-called structure-property relation is an important task in many scientific disciplines, such as chemistry, biology, meteorology, p…
Deep Learning of Crystalline Defects from TEM images: A Solution for the Problem of "Never Enough Training Data"
Kishan Govind, Daniela Oliveros, Antonin Dlouhy +2
Crystalline defects, such as line-like dislocations, play an important role for the performance and reliability of many metallic devices. Their interaction and evolution still pose…
Statistical analysis of Discrete Dislocation Dynamics simulations: initial structures, cross-slip and microstructure evolution
Aytekin Demirci, Dominik Steinberger, Markus Stricker +3
Over the past decades, discrete dislocation dynamics simulations have been shown to reliably predict the evolution of dislocation microstructures for micrometer-sized metallic samp…
Data-mining of dislocation microstructures: concepts for coarse-graining of internal energies
Hengxu Song, Nina Gunkelmann, Giacomo Po +1
Continuum models of dislocation plasticity require constitutive closure assumptions, e.g., by relating details of the dislocation microstructure to energy densities. Currently, the…
Universality of Avalanche Exponents in Plastic Deformation of Disordered Solids
Zoe Budrikis, David Fernandez-Castellanos, Stefan Sandfeld +2
Plastic yield of amorphous solids occurs by power law distributed slip avalanches whose universality is still debated. Determination of the power law exponents from experiments and…
Propagating compaction bands in confined compression of snow: Experiment and Modelling
T. W. Barraclough, J. R. Blackford, S. Liebenstein +4
We show that the plastic deformation of snow under uniaxial compression is characterized by complex spatio-temporal strain localization phenomena. Deformation is characterized by r…