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Understanding and Predicting Hydrogen Embrittlement in Metals Demonstrates the Predictive Power of MLPs for Complex Metallurgical Phenomena
Understanding and Predicting Hydrogen Embrittlement in Metals Demonstrates the Predictive Power of MLPs for Complex Metallurgical Phenomena
Katherine Hollingsworth
Aug 27, 20242 min read
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Webinar: Δ-Machine Learning beyond DFT: from phase transitions to quantum paraelectricity & CO...
UGM Plenary Speaker Spotlight Tuesday, we host Dr. Carla Verdi; Faculty at University of Vienna, Austria and Dr. Georg Kresse; Professor...
Katherine Hollingsworth
Oct 16, 20224 min read
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Thursday's UGM Training: Generating and Applying Machine-Learned Potentials with MedeA
UGM MedeA Training Generating and Applying Machine-Learned Potentials with MedeA Instructor: Dr. David Reith Density functional theory...
Katherine Hollingsworth
Oct 12, 20221 min read
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Wednesday's UGM Webinar: Atomistic Simulations with High-Dimensional Neural Network Potentials
UGM Plenary Speaker Spotlight This week, we host Jörg Behler; Full Professor of Theoretical Chemistry University of Göttingen, Germany...
Katherine Hollingsworth
Oct 10, 20222 min read
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Tuesday's UGM Webinar: Materials Innovations for Chemical Separations
Jeffrey Grossman; Department Head of Materials Science and Engineering at the Massachusetts Institute of Technology
Katherine Hollingsworth
Sep 30, 20223 min read
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Upcoming Webinar: Radionuclide Sequestration in MOFs
Radionuclide Sequestration in MOFs: DFT Method Exploration and a Conceptualization of Graph Neural Networks This webinar will be focused...
Katherine Hollingsworth
Sep 14, 20223 min read
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