ChBE Seminar Series: Gerassimons Orkoulas

Tuesday, February 23, 2010
11:00 a.m.-12:15 p.m.
Room 2110 Chemical and Nuclear Engineering Bldg.
Professor Ray Adomaitis

Spatial Updating Monte Carlo Algorithms in Particle Simulations: Application to Protein Crystallization

Presented by Gerassimons (Makis) Orkoulas
Department of Chemical and Biomolecular Engineering

Spatial updating Monte Carlo algorithms constitute generalizations of random and sequential updating algorithms for Ising and lattice-gas systems to off-lattice, continuum fluid models. By analogy with a lattice-gas, in a grand canonical Monte Carlo simulation of a continuum fluid model, spatial updating is implemented by selecting a point in space and deducing the type of move (insertion or removal) by examining the local environment around the point. In this work, the phase behavior of systems representative of globular proteins is investigated via a combination of spatial updating grand canonical Monte Carlo simulations and simulated tempering techniques. Despite the fact that grand canonical spatial updating is efficient at high densities, it cannot probe the solid phase and thus cannot be used to simulate fluid-solid transitions. A solution to the previous drawback can be achieved by incorporating volume fluctuations in a grand canonical system. Such a setup corresponds to a great grand canonical ensemble for which all intensive variables are fixed and all extensive variables fluctuate without bounds. The range of fluctuations may be bounded by placing a restriction or a constraint on the system. Incorporation of spatial updating in a constrained great grand canonical ensemble allows the simulations to explore very high densities and leads to determination of fluid-solid equilibrium. Accurate simulation of phase transitions that involve dense, nearly incompressible phases is of crucial importance in protein and colloid crystallization for which fluid-fluid separation might be metastable against solidification. These techniques are currently being used to elucidate the phase diagrams and understand the physics of crystallization of globular proteins at the microscopic/mesoscopic level. Finally, these algorithms can be used in droplet and crystal nucleation studies to obtain: (i) nucleation barriers, (ii) free energies of cluster formation, and (iii) the critical cluster size beyond which clusters (on the average) grow.

Audience: Graduate  Faculty  Post-Docs 


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