Berlin 2024 –
scientific programme
MM 62: Developement of Calculation Methods III
Thursday, March 21, 2024, 15:45–18:00, C 264
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15:45 |
MM 62.1 |
Phase transitions in radial distribution biased Molecular Dynamics simulations — •Lars Dammann, Patrick Huber, and Robert H. Meißner
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16:00 |
MM 62.2 |
Finite temperature electronic structure calculations for heavy element tetrahedral semiconductors using a dynamic tight-binding model — •Shaoming Zhang, Martin Schwade, and David A. Egger
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16:15 |
MM 62.3 |
Machine Learning Potentials for Multi-State Systems: Predicting Photoluminescence Spectra from Molecular Dynamics — Christopher Linderälv, •Nicklas Österbacka, Julia Wiktor, and Paul Erhart
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16:30 |
MM 62.4 |
Dynasor 2.0: From simulation to experiment through correlation functions — •Esmée Berger, Erik Fransson, Fredrik Eriksson, Eric Lindgren, and Paul Erhart
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16:45 |
MM 62.5 |
Machine-learned interatomic potential for microstructure formation in Ni-rich NiAl systems — •Adam Fisher, Julie B. Staunton, Huan Wu, and Peter Brommer
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17:00 |
MM 62.6 |
Cross-Platform Hyperparameter Optimizer for Machine-Learning Potential Fitting — •Daniel F. Thomas du Toit, Yuxing Zhou, and Volker L. Deringer
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17:15 |
MM 62.7 |
Warm Dense Hydrogen as a Benchmark for Machine-Learning Potentials — Bastian Jäckl, Thomas Bischoff, and •Matthias Rupp
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17:30 |
MM 62.8 |
Ab initio Raman spectroscopy including temperature: Theory and application for GaN and BaZrS3 — •Florian Knoop, Nimrod Benshalom, Matan Menahem, Omer Yaffe, and Olle Hellman
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17:45 |
MM 62.9 |
An efficient method for estimating the dynamics of full polarizability tensor in ab initio molecular dynamics simulations — •Pouya Partovi-Azar
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