Access Type
Open Access Thesis
Date of Award
January 2019
Degree Type
Thesis
Degree Name
M.S.
Department
Computer Science
First Advisor
Loren Schwiebert
Abstract
A generalized identity exchange algorithm is presented for Monte Carlo simulations in the grand canonical ensemble. The algorithm, referred to as Molecular Exchange Monte Carlo (MEMC), may be applied to multicomponent systems of arbitrary molecular topology, and provides significant enhancements in the sampling of phase space over a wide range of compositions and temperatures. Three different approaches are presented for the insertion of large molecules, and the pros and cons of each method are discussed. The performance of the algorithms is highlighted through grand canonical Monte Carlo histogram-reweighting simulations performed on several systems, including 2,2,4-trimethylpentane+neopentane, butane+perfluorobutane, methane+n-alkanes, and water+impurity. Relative acceptance efficiencies of up to 400 times that of standard configurational-bias Monte Carlo are obtained for molecule transfers.
Recommended Citation
Soroush Barhaghi, Mohammad, "Molecular Exchange Monte Carlo. A Generalized Method For Identity Exchanges In Grand Canonical Monte Carlo Simulations" (2019). Wayne State University Theses. 738.
https://digitalcommons.wayne.edu/oa_theses/738