Using Machine Learning and Quantum Mechanics to Understand Chemical Reactions on Surfaces
TITLE:
Using Machine Learning and Quantum Mechanics to Understand Chemical Reactions on Surfaces
DATE:
Friday, October 19th, 2018
TIME:
4:00 PM
LOCATION:
GMCS-301
SPEAKER:
Michael Groves, Assistant Professor, Physical and Theoretical Chemistry, CSU Fullerton.
ABSTRACT:
Catalysts, which are substances that increase the rate of a given chemical
reaction without being consumed themselves, have a critical importance to
humanity’s standard of living. For example, ammonia is used to produce
fertilizer. The industrial method to produce ammonia, which relies on an
iron-based catalyst, lead to a dramatic increase in the human population at
the beginning of the 20th century due to increased crop yields through
newly abundant access to fertilizer. It is usually preferable for the
catalyst to be in a different phase than the chemicals undergoing the
reaction for easy separation. This is called Heterogeneous Catalysis.
What this talk will cover is my research group’s efforts to computationally
predict the structure of new heterogeneous catalysts and then test their
effectiveness in heath and energy related applications. We will discuss
how machine learning and quantum mechanical methods play an active role
in screening next generation catalysts designed to solve current problems.
HOST:
Dr. Andrew Cooksy
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