No abstract

An ionic nano-convection model has been established for elucidating early stage anodisation of aluminium plate and the direct consequence of such convection is an ordered pattern of charge distribution near the oxide/electrolyte interface, guiding the initial ordering of the pore formation.

The present work proposes a novel methodology for constructing coarse-grained (CG) models, which aims at minimizing the difference between the CG model and its original system. The difference is defined as a functional of the ratio of equilibrium conformational probability densities to the original one, then is further expanded by equilibrium averages of a set of sufficient and independent physical quantities as basis functions. An orthonormalization strategy is adopted to get the independent basis functions from sufficiently preselected interesting physical quantities of the system. The probability density matching coarse-graining (PMCG) scheme effectively takes into account the overall characteristics of the original systems to form CG models, and it is a natural improvement of the usual CG scheme wherein equilibrium averages of many physical quantities are intuit chosen to reproduce without considering correlations among these quantities. We verify the general PMCG framework in constructing a one-site CG water model from TIP3P model. Both structure of liquids and pressure are found to be well reproduced at the same time in the one-site CG water model.