| Description |
Clyde A. Daly Jr.
(Haverford College, U.S.A.)
Abstract
Many complex macroscopic phenomena have their origins in microscopic, molecule and atom level interactions. Using techniques like molecular dynamics and machine learning, connections can be made between these two scales of observation. In this talk, I will showcase the power of these techniques in four cases. First, the solvation properties of carbon dioxide in ionic liquids are examined using one dimensional and two dimensional infrared spectroscopy. Second, the structure of the hydrated proton is elucidated by combining molecular dynamics with infrared and Raman spectroscopy. Third, molecular dynamics is used to examine the behavior of nanoparticles when interacting with biomolecules. Fourth, machine learning is used to develop design rules for creating sustainable nanotechnologies. In my new position at Haverford College, I am extending these techniques to study more complex related systems. |
CMSP Seminar (Atomistic Simulation Webinar Series): Modeling Complex Phenomena with Machine Learning and Molecular Dynamics
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