Kinetic-Bias Model for the Dynamic Simulation of Molecular Aggregation. The Liquid, Solute, Solvated-Nanodrop, and Solvated-Nanocrystal States of Benzoic Acid

Abstract

A kinetically biased molecular dynamics (KB-MD) algorithm is developed as an addition to the Milano Chemistry Molecular Simulation (MiCMoS) package. Within a condensed medium, the algorithm sorts out molecular pairs coupled by a strong interaction energy and reduces their kinetic energy by a damping factor, redistributing the resulting excess among other partners within the medium. The aim is to enhance in an iterative manner the incipient intermolecular cohesion, on the way to the formation of recognition aggregates. The algorithm is applied to bulk liquid and crystalline benzoic acid, to homogeneous solutions in methanol, and to liquid or crystalline nanoclusters embedded in methanol solvent. Favorable outcomes are observed in liquid media with the formation of large molecular clusters and in the enhancement of the lifetimes of nanocrystals. Homogeneous solutions are found to require extremely long simulation times to show significant aggregation. Organization into a crystalline structure from liquid precursors is still a faraway simulation goal, but the present approach can be a useful tool, along with the introduction of appropriate collective structural variables, for tackling this long-standing problem at the atomic level