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Frontiers of Multi-scale Modeling in Materials, Energy & Catalysis X

22–26 Apr 2024
Europe/Berlin timezone

Session

Session IV: Chemical Machine Learning

24 Apr 2024, 09:00

Presentation materials

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  1. 18. Materials Search using the Convex Hull Genetic Algorithm and ML
    Prof. Matthew Probert (School of Physics, Engineering and Technology University of York)
    24/04/2024, 09:00
  2. 19. Exploring Alternative Dispersion Corrections for the BEEF-vdW Functional
    Ms Elisabeth Keller (Fritz-Haber-Institut der MPG)
    24/04/2024, 09:30
  3. 20. Machine-Learning Driven Exploration of Catalytic Reaction Network
    Dr Hyunwook Jung (Fritz-Haber-Institut der MPG)
    24/04/2024, 09:50
  4. 21. Charge Equilibration in Machine Learning Potentials
    Dr Martin Vondrak (Fritz-Haber-Institut der MPG)
    24/04/2024, 10:10
  5. 22. Towards Multi-Fidelity Machine Learning Using Robust Density Functional Tight Binding Models
    Mr Mengnan Cui (Fritz-Haber-Institut der MPG)
    24/04/2024, 10:50
  6. 23. Improving the Diversity of Transition State Searches With On-The-Fly Learned Biasing Potentials
    Mr Nils Gönnheimer (Fritz-Haber-Institut der MPG)
    24/04/2024, 11:10
  7. 24. Learning to Spell Materials - Coordinate-free Discovery with Natural Language Processing
    Mr Konstantin Jakob (Fritz-Haber-Institut der MPG)
    24/04/2024, 11:30
  8. 25. AI-Empowered Universal Workflow for Molecular Design of Performant Photoswitches
    Mr Robert Strothmann (Fritz-Haber-Institut der MPG)
    24/04/2024, 11:50
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