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Machine Learning Meets Quantum Chemistry Using Theory Data and Experiments to Design Catalysts

Catalysis is the cornerstone of modern chemical industry. Catalysts not only convert the natural resources into products we can use in our daily lives, but also aid to solve the hazardous side reaction issues.  A suitable catalyst should minimize the energy penalty of the reaction and maximize the selectivity to desired products. This webinar will discuss some of the ways MedeA can be used to understand reaction mechanisms, then incorporate machine learning technics to accelerate catalysts discovery and advance catalysis theory.

  • Explore reaction pathways with MedeA tools

  • Calculate surface strain effect of core-shell nanoparticles

  • Quantify alloy effect on catalysts

  • Study biopolymer interaction effect on catalysts

  • Operating potential effect on the stability of electro-catalysts

  • High-throughput screening of bimetallic materials

  • Electronic structure of adsorbates on catalysts

  • Bayesian learning approach to predict site reactivity

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Watch the recorded session
Training: Orbital Level Understanding of Adsorbate-Surface Interactions in Catalysis

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Slides from the training webinar.
Training: Orbital Level Understanding of Adsorbate-Surface Interactions in Catalysis

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