MS2: A Coarse-Grained Molecular Model for Computational Studies of Cellulosic Biomaterials
Date of Award
6-2014
Degree Type
Thesis
Degree Name
Master of Science (MS)
Department
Biomedical and Chemical Engineering
Advisor(s)
Radhakrishna Sureshkumar
Keywords
Biofuels, Cellulose, Coarse-Grained, Computational, Molecular Dynamics, Simulations
Abstract
We have developed a coarse-grained molecular model to investigate carbohydrates-solvent interactions that govern important phenomena such as cellulose dissolution. Cellulose, the most abundant biomass on earth, is yet to be used for large-scale biofuel production because of its poor dissolution rate in most solvents. MS2, the coarse-grained model proposed in this work, could help better understand the reasons behind such stability by allowing simulations that span greater time/length scales while capturing more atomistic details than other models would allow. Moreover, MS2 can differentiate between 1-4, 1-6 and 1-3 glycosidic bonds and therefore, can be very useful for computational studies of many other carbohydrates such as starch, dextran and amylose, among others.
MS2 was used to make reasonable prediction of the glass transition temperature of aqueous glucose solution and radial distribution functions of cellobiose in water. When applied to the study of cellulosic crystals both in vacuum and water, the specificity of the primary alcohol conformation, the unit cell parameters and the hydrogen bonding network were successfully predicted by MS2. To the best of our knowledge, some of those details have never been captured before by coarse-grained models proposed so far. These studies can be used to identify more effective solvents and chemical environments conducive to dissolution of cellulosic biomaterials.
Access
Surface provides description only. Full text is available to ProQuest subscribers. Ask your Librarian for assistance.
Recommended Citation
Reveil, Mardochee, "MS2: A Coarse-Grained Molecular Model for Computational Studies of Cellulosic Biomaterials" (2014). Theses - ALL. 31.
https://surface.syr.edu/thesis/31