Statistical Mechanics of Dynamics and Structure in Liquids

点击翻译按钮获取中文摘要

David Chandler of the University of California, Berkeley, is supported by the Theoretical and Computational Chemistry Program to continue his research in statistical mechanics directed at understanding structure and dynamics of liquids and related systems. In the first project, charge frustrated models of oil-water-surfactant systems will be used to develop and exploit isomorphisms between very different phenomena, including metal-insulator transitions in liquid solutions and vitrification of supercooled liquids. In another project, hydrophobicity at small and large length scales will be exploited to develop a generally applicable statistical field theory. This formulation will be applied as a bridge between large length scale phenomenology and small scale atomistic theories of complex fluids, and used to analyze systems such as polymer melts and blends, and liquid crystals. These techniques are also expected to enable development of an equilibrium theory for water and other associated fluids. In the area of dynamics, transition path sampling will be used to devise phenomenological theories for weak acid dissociation and proton transfer in aqueous systems. Methods for treating quantum effects within the context of transition path sampling will be explored, with the goal of enabling quantitative treatments of kinetics involving light atoms such as protons in water. In a final project, concepts governing ensembles of trajectories will be developed further, especially for systems far from equilibrium. Outcomes are expected to enable the analysis of broken symmetry, corresponding to broken ergodicity and to phase transitions of driven systems. Improved understanding of liquid systems structure and dynamics has far-reaching implications for fundamental science and technology applications. Outcomes from this project will impact materials science, including polymers and liquid crystal systems. As well, new results on proton transfer and the hydrophobic effect will have strong connections to biologically relevant systems, including protein folding.