Path-integral and Coarse-graining Strategies for Complex Molecular Phenomena


Autoria(s): Webb, Michael Anthony
Data(s)

2016

Resumo

Molecular simulation provides a powerful tool for connecting molecular-level processes to physical observables. However, the facility to make those connections relies upon the application and development of theoretical methods that permit appropriate descriptions of the systems or processes to be studied. In this thesis, we utilize molecular simulation to study and predict two phenomena with very different theoretical challenges, beginning with (1) lithium-ion transport behavior in polymers and following with (2) equilibrium isotope effects with relevance to position-specific and clumped isotope studies. In the case of ion transport in polymers, there is motivation to use molecular simulation to provide guidance in polymer electrolyte design, but the length and timescales relevant for ion diffusion in polymers preclude the use of direct molecular dynamics simulation to compute ion diffusivities in more than a handful of candidate systems. In the case of equilibrium isotope effects, the thermodynamic driving forces for isotopic fractionation are often fundamentally quantum mechanical in nature, and the high precision of experimental instruments demands correspondingly accurate theoretical approaches. Herein, we describe respectively coarse-graining and path-integral strategies to address outstanding questions in these two subject areas.

Formato

application/pdf

Identificador

http://thesis.library.caltech.edu/9761/1/webb_michael_2016_thesis.pdf

Webb, Michael Anthony (2016) Path-integral and Coarse-graining Strategies for Complex Molecular Phenomena. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/Z90Z7172. http://resolver.caltech.edu/CaltechTHESIS:05252016-213050706 <http://resolver.caltech.edu/CaltechTHESIS:05252016-213050706>

Relação

http://resolver.caltech.edu/CaltechTHESIS:05252016-213050706

http://thesis.library.caltech.edu/9761/

Tipo

Thesis

NonPeerReviewed