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Project TitleImproving Global Optimisation Search Schemes for Quantum Chemical Simulations
SummaryThe intern will develop protocols which will enhance the success rate and speed of the genetic algorithm, a global optimisation search scheme, available in the open source Atomic Simulation Environment (ASE). ASE is a set of tools and Python modules for setting up, manipulating, running, visualizing and analyzing atomistic simulations.
Job DescriptionA typical genetic algorithm runs in a loop where trial structures are selected from an exclusive population and are paired and/or mutated. Molecular configurations that are better will replace weaker candidates in the population. Initializing the population, however, typically relies on little chemical intuition which leaves much of configuration space unsampled.

The student will use existing data to create protocols in Python to intelligently create a starting set of geometries to more broadly sample configuration space. The successful intern will also use quantum mechanics based calculations to relax trial structures and use machine leaning algorithms to cluster during global optimisation search runs to test the effectiveness of their protocols. New strategies will then be tested on new trial systems to determine their capabilities on a broader set of systems.
Use of Blue WatersTo test the effectiveness of global optimisation search schemes, hundreds of runs comprised of thousands of trial structures must be calculated to get the statistics necessary to quantify improvements. Local resources here at CSUF will be used to prototype initial population generation protocols. The resources at Blue Waters will be used for promising candidates to parallelize all the necessary runs to get relevant statistical accuracy to benchmark improvements. Also the parallelization available at Blue Waters will enhance the chemical accuracy of the quantum mechanics based calculations as well as enhance the clustering algorithm's ability to categorize structures. This will be useful when the improved code is applied to new, catalytically relevant systems to determine important chemical properties.
Start Date03/01/2017
End Date03/01/2018
LocationGroves Research Group
Department of Chemistry and Biochemistry
California State University, Fullerton
Fullerton, CA
Nicholas Kellas