Speaker: Prof. James P. Lewis, Synfuels China Ltd., Hong Kong Science Park, Chinese Academy of Sciences

Time: 10:00 a.m., October 27, 2023, GMT+8

Venue: College of Chemistry and Molecular Engineering Room A717

Abstract:

Machine learning, a computational dream for decades, has now been realized. With increase in computational speed, the age of big data enables society to apply machine-learning algorithms tall aspects of life. Recently, even scientists have utilized the age of big data to understand and control nature, whereby to improve our understanding of materials as well as design new material. My research group has endeavored to participate in this exciting direction by applying machine-learning tools to several physical chemistry and materials science-fundamental research problems including catalysts. With machine learning, our research has expanded to new directions such asn redcfing global reaction mechanisms. understanding adsorbate interactions on catalvsts. and to further improve neural network potentials for rapid structure evaluations that are needed for materials structure prediction. Fast and efficient computational chemistry and materials science software has further enabled rapid accumulation of data from which machine learning algorithms can recognize patterns and make predictions. We will discuss our journey where machine learning meets quantum chemistry in catalysis.

Source: College of Chemistry and Molecular Engineering