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Title: Hybrid methods for molecular spectroscopy and reactivity
Author: Fare, Clyde
ISNI:       0000 0004 7969 8279
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2018
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In this thesis a variety of different studies are undertaken coupled together through ap- plication of the hybrid method ONIOM to compute reaction energies, barrier heights and vibrational modes of molecules. ONIOM is a means to combine multiple levels of theory such that different regions of a molecular system are treated with different levels of accuracy enabling computation on large molecular systems with complex environments at an accuracy that would be impossible using a single level of theory. The price of ONIOM is a requirement for computational chemists to specify regions of interest, and in the case of biomolecules where forcefields are typically used to treat the environment to choose suitably parameterised forcefield. My initial investigations focused on means to automate this process hence allow ONIOM to be used within high throughput studies to compute properties of populations of molecules. Toward this end I present an API allowing construction and execution of ONIOM calculations including parameterisation for biomolecular simulation which both improves providence in computational chemical research and enables high throughput calculations. Following this I investigate ONIOM applied to graphitic fragments first examining a 1,3 dipolar cycloaddition then in order to address the question of how to choose model regions within these extended delocalised systems I examine whether systematic fragmentation and use of very cheap computational metrics can allow automatic model selection within a test hydrogenation reaction. I then turn to an alternative means of computing the effect of the environment: machine learning and perform a small machine study on solvation of a series of 6095 constitutional isomers examining whether both the implicit solvation method PCM and an explicit model of solvation making use of ONIOM can be learned use the machine learning algorithm Kernel Ridge Regression. Finally in the last part of my thesis I perform an experimental time resolved spectroscopic study of the photoactive protein EOSFP examining the photo induced changes that occur both during and after exposure to the 405nm light which drives photoconversion in this protein and make use ONIOM to compute vibrational modes that aid assignment of vibrational spectra.
Supervisor: Bearpark, Michael ; van Thor, Jasper Sponsor: Engineering and Physical Sciences Research Council
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral