Molecular Dynamics and Stochastic Simulations of Surface Diffusion

Transition state theory;Rate;Modeling;Computational chemistry;Coarse-graining;Langevin

Moix, Jeremy Michael ; Chemistry and Biochemistry

University:Georgia Institute of Technology

Department:Chemistry and Biochemistry

关键词: Transition state theory;    Rate;    Modeling;    Computational chemistry;    Coarse-graining;    Langevin;   

Others  :  https://smartech.gatech.edu/bitstream/1853/14580/1/moix_jeremy_m_200705_phd.pdf

美国|英语

来源: SMARTech Repository

【 摘 要 】

Despite numerous advances in experimental methodologies capable of addressing the various phenomenon occurring on metal surfaces, atomic scale resolution of the microscopic dynamics remains elusive for most systems. Computational models of the processes may serve as an alternative tool to fill this void. To this end, parallel molecular dynamics simulations of self-diffusion on metal surfaces have been developed and employed to address microscopic details of the system. However these simulations are not without their limitations and prove to be computationally impractical for a variety of chemically relevant systems, particularly for diffusive events occurring in the low temperature regime. To circumvent this difficulty, a corresponding coarse-grained representation of the surface is also developed resulting in a reduction of the required computational effort by several orders of magnitude, and this description becomes all the more advantageous with increasing system size and complexity. This representation provides a convenient framework to address fundamental aspects of diffusion in nonequilibrium environments and an interesting mechanism for directing diffusive motion along the surface is explored. In the ensuing discussion, additional topics including transition state theory in noisy systems and the construction of a checking function for protein structure validation are outlined. For decades the former has served as a cornerstone for estimates of chemical reaction rates. However, in complex environments transition state theory most always provides only an upper bound for the true rate. An alternative approach is described that may alleviate some of the difficulties associated with this problem. Finally, one of the grand challenges facing the computational sciences is to develop methods capable of reconstructing protein structure based solely on readily-available sequence information. Herein a checking function is developed that may prove useful for addressing whether a particular proposed structure is a viable possibility.