Doctor of Philosophy (PhD)
Sampling molecular conformations is an important step in evaluating physical, mechanical, hydrodynamic, and optical properties of flexible molecules especially polymers. One powerful method for this purpose is configurational-bias Monte Carlo in which one random segment of a molecule is chosen, all segments toward one random end are removed, and then regrown segment by segment to produce a new geometry to be accepted/rejected according to probability laws. The advantage of this method is the ability to generate acceptable conformations that are favorable for intra- and intermolecular energies to save computational costs. However, when there are several interdependent energetic terms, trial generation can be very time consuming because a trial must be generated that is satisfactory for all energetic terms. There are two important cases where a number of intramolecular energies are coupled: bending angle energies in a branched point, and bending and torsional angle energies for growing segments between two fixed points.
According to probability laws, if trials are generated according to their probability density function, all trials will be accepted. The basic idea of the methods, which have been developed for the two above cases, is to generate trials that are close to the Boltzmann distributions of intramolecular energies. It has been proved that new methods are faster and more efficient than traditional methods. One of the methods for generating bending angle trials have been used in nucleation simulations of flexible amine molecules which accelerates simulation process by four to five folds.
Sepehri, Aliasghar, "Innovative Monte Carlo Methods for Sampling Molecular Conformations" (2018). LSU Doctoral Dissertations. 4201.