Dresden 2020 – wissenschaftliches Programm

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CPP: Fachverband Chemische Physik und Polymerphysik

CPP 104: Topical Session: Data Driven Materials Science - Machine Learning Applications (joint session MM/CPP)

Donnerstag, 19. März 2020, 17:30–19:00, BAR 205

17:30 CPP 104.1 How polymorphism of adsorbate molecules determines the physical properties of metal/organic interfaces: a large scale study — •Johannes J. Cartus, Andreas Jeindl, Lukas Hörmann, and Oliver T. Hofmann
17:45 CPP 104.2 Investigation of short-range order in multicomponent alloys with the use of machine-learning interatomic potentials — •Tatiana Kostiuchenko, Alexander Shapeev, Fritz Körmann, and Andrey Ruban
18:00 CPP 104.3 An equation for membrane permeability: Insight from compressed sensing — •Arghya Dutta and Tristan Bereau
18:15 CPP 104.4 Transferable Gaussian Process Regression for prediction of molecular crystals harmonic free energy. — •Marcin Krynski and Mariana Rossi
18:30 CPP 104.5 Bayesian modeling for potential energy surface minimization — •Estefania Garijo del Rio, Sami Juhani Kaapa, and Karsten Wedel Jacobsen
18:45 CPP 104.6 A computational route between band mapping and band structureR. Patrick Xian, •Vincent Stimper, Marios Zacharias, Shuo Dong, Maciej Dendzik, Samuel Beaulieu, Matthias Scheffler, Bernhard Schölkopf, Martin Wolf, Laurenz Rettig, Christian Carbogno, Stefan Bauer, and Ralph Ernstorfer
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