SKM 2023 – wissenschaftliches Programm

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MM: Fachverband Metall- und Materialphysik

MM 12: Poster I

Montag, 27. März 2023, 18:15–20:00, P2/OG1+2

18:15 MM 12.1 Time-of-Flight X-ray Photoelectron Microscopy (ToF-X-PEEM) — •G. Schönhense, O. Tkach, O. Fedchenko, Y. Lytvynenko, D. Vasilyev, Q.L. Nguyen, T.R.F. Peixoto, A. Gloskovskii, S. Chernov, M. Hoesch, N. Wind, M. Heber, C. Schlueter, C. Sharma, K. Rossnagel, M. Scholz, and H.-J. Elmers
18:15 MM 12.2 Chlorine Corrosion of Superheater Steels — •Matthias Kroh, Sebastian Pentz, Ferdinand Haider, and Georg Krupkov
18:15 MM 12.3 Nanoscale heat transport in heterostructures measured with UXRD at European XFEL — •Jan-Etienne Pudell, Marc Herzog, Max Mattern, Jasmin Jarecki, Alexander von Reppert, Ulrike Boesenberg, Angel Rodriguez-Fernandez, Wonhiuk Jo, Roman Shayduk, Wei Lu, Gregory Malinowski, Michel Hehn, Matias Bargheer, and Anders Madsen
18:15 MM 12.4 Structural evolution and atomic transport in severely deformed bi-metallic samples — •Shraddha V. Sevlikar, Gerhard Wilde, and Sergiy V. Divinskiy
18:15 MM 12.5 Study of Electron Transport in a DNA model — •Jorge Cardenas-Gamboa, José García, and Solmar Varela
18:15 MM 12.6 Investigations on thermal contact conductance between filled polymer composites and solids using micro thermography — •Oliver Roser, Andreas Griesinger, and Othmar Marti
18:15 MM 12.7 Hydrogen Diffusion in High-Pressure Torsion (HPT) deformed Magnesium and Magnesium-alloys — •Giorgia Guardi, Sabine Schlabach, Julia Ivanisenko, Stefan Wagner, and Astrid Pundt
18:15 MM 12.8 A systematic investigation of metastable phases in Niobium using density-functional theory — •Susanne Kunzmann, Gabi Schierning, and Anna Grünebohm
18:15 MM 12.9 Computational local point-based boundary conditions method for eigenfrequencies in microwave eccentric spherical cavities — •Zoya Eremenko, Igor Volovichev, Oleksiy Breslavets, and Grigorios Zouros
18:15 MM 12.10 Machine learning force fields in VASP — •Ferenc Karsai, Andreas Singraber, Jonathan Lahnsteiner, Ryosuke Jinnouchi, and Georg Kresse
18:15 MM 12.11 Structure prediction of iron hydrides at high pressures by machine-learned interatomic potentials — •Hossein Tahmasbi, Kushal Ramakrishna, Mani Lokamani, Mandy Bethkenhagen, and Attila Cangi
18:15 MM 12.12 Machine Learning Interatomic Potentials for amorphous mesoporous metallosilicates — •Julian Greif, Konstantin Gubaev, and Blazej Grabowski
18:15 MM 12.13 Deep learning for generation of optimal reaction environments — •Rhyan Barrett and Julia Westermayr
18:15 MM 12.14 Efficient graph neural networks for accurate interatomic potentials between surfaces and adsorbed atoms — •Nian Wu, Fabio Priante, Eric Kramer Rosado, and Adam S Foster
18:15 MM 12.15 Investigation of bonding mechanism between early transition metals and antimony — •Carolin Petersen, Christian Stenz, and Matthias Wuttig
18:15 MM 12.16 DFT structural characterization of β- and δ- intermetallic Al-Fe-Si phases — •Nebahat Bulut, Hanka Becker, Andreas Leineweber, and Jens Kortus
18:15 MM 12.17 A method for charge-sloshing free precise linear-scaling density-functional calculations — •Rudolf Zeller
18:15 MM 12.18 How to Train a Neural Network Potential — •Alea Miako Tokita and Jörg Behler
18:15 MM 12.19 PyRamanGUI: An open-source multi-purpose tool to analyze Raman spectra — •Simon Brehm, Cameliu Himcinschi, Jakob Kraus, and Jens Kortus
18:15 MM 12.20 Non-contact friction on various material systems — •Kim Lambert, Niklas Weber, Matthias Krüger, and Cynthia Vokert
18:15 MM 12.21 Thermodynamical Stability Analysis of a Model Quasicrystal — •Moritz Holzwarth, Johannes Roth, and Hans-Rainer Trebin
18:15 MM 12.22 Excitation-induced non-thermal effects in silicon — •Simon Kümmel, Dominic Klein, and Johannes Roth
18:15 MM 12.23 Towards understanding the chemical bonding of unconventional metals — •Christian Stenz, Johannes Holters, and Matthias Wuttig
18:15 MM 12.24 An efficiently automated method to sample the energies of grain boundaries — •Timo Schmalofski, Martin Kroll, Rebecca Janisch, and Holger Dette
18:15 MM 12.25 Cubic scaling GW in the exciting code — •Manoar Hossain, Alexander Buccheri, Andris Gulans, and Claudia Draxl
18:15 MM 12.26 Physics Informed Neural Networks based Solvers for the Time-Dependent Schrödinger Equation — •Karan Shah and Attila Cangi
18:15 MM 12.27 High-throughput calculations for property maps of solids — •Daniela Ivanova, Daniel Wortmann, Stefan Blügel, Matthias Wuttig, and Carl-Friedrich Schön
18:15 MM 12.28 A high-level workflow-based approach towards the exploration of magnetocaloric Heusler alloys by automated high-throughput simulations — •Simon Bekemeier, Alisa Chirkova, and Christian Schröder
18:15 MM 12.29 Ontology-Template-Based Description of Anisotropic Conductivity Measurements — •Lennart Schwan, Michael Feige, Moritz Bluhm, Basil Ell, Andreas Hütten, and Sonja Schöning
18:15 MM 12.30 An Ontology of Magnetocaloric Materials ResearchSimon Bekemeier, Moritz Blum, Luana Caron, Philipp Cimiano, Basil Ell, Inga Ennen, Michael Feige, Thomas Hilbig, Andreas Hütten, Günter Reiss, Tapas Samanta, Sonja Schöning, Christian Schröder, Lennart Schwan, and •Martin Wortmann
18:15 MM 12.31 Laser processing of metal materials created by additive technologies. Optimization of structure and mechanical properties — •Iryna Galstian, Evgen Len, Tobias Gustmann, and Nicole Geißler
18:15 MM 12.32 MD Simulation of 3D Laser Printing — •Jonas Schmid, Kevin Vietz, Dominic Klein, and Johannes Roth
18:15 MM 12.33 Molecular dynamics simulation of additive manufacturing: A highly non-equilibrated business — •Kevin Vietz, Azad Gorgis, Dominic Klein, and Johannes Roth
18:15 MM 12.34 Atomistic simulations of crack-tip interface interactions in lamellar TiAl microstructures — •Onur Can Sen and Rebecca Janisch
  18:15 MM 12.35 The contribution has been withdrawn.
18:15 MM 12.36 Fracture surface energy of glasses obtained from crystalline structure and bond energy data — •Marco Holzer, Tina Waurischk, Janine George, Robert Maaß, and Ralf Müller
18:15 MM 12.37 An in situ crack detection approach in additive manufacturing based on acoustic emission and machine learning — •Viktoriia Nikonova, Denys Kononenko, Dmitry Chernyavsky, Mikhail Seleznev, and Jeroen van den Brink
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