Nucleation of Molecular Crystals Driven by Relative Information Entropy

Abstract

Simulating nucleation of molecular crystals is extremely challenging for all but the simplest cases. The challenge lies in formulating effective order parameters that are capable of driving the transition process. In recent years, order parameters based on molecular pair-functions have been successfully used in combination with enhanced sampling techniques to simulate nucleation of simple molecular crystals. However, despite the success of these approaches, we demonstrate that they can fail when applied to more complex cases. In fact, we show that order parameters based on molecular pair-functions, while successful at nucleating benzene, fail for paracetamol. Hence, we introduce a novel approach to formulate order parameters. In our approach, we construct reduced dimensional distributions of relevant quantities on the fly and then quantify the difference between these distributions and selected reference distributions. By computing the distribution of different quantities and by choosing different reference distributions, it is possible to systematically construct an effective set of order parameters. We then show that our new order parameters are capable of driving the nucleation of ordered states and, in particular, the form I crystal of paracetamol.

Dynamic simulation of liquid molecular nanoclusters: structure, stability and quantification of internal (pseudo)symmetries

“…The distribution of angles between molecular C-H vectors in chloroform clusters is on the contrary perfectly uniform in distance (ESI, Figure S2). Quantitative treatment of orientation probability densities in bulk systems [22][23][24] could be given for a more detailed discussion of the matter; this would be however outside the scope of the present work. We merely point out that the distribution of inter ring angles in liquid benzene clusters is identical to that of the bulk liquid (ESI, Figure S3).…”

Systematic Finite-Temperature Reduction of Crystal Energy Landscapes.

“…To this aim we base our approach on the definition of hierarchical, probabilistic fingerprints, able to capture key characteristics of the fluctuating local molecular environment of crystal structures. Inspired by the descriptors pro-posed in a recent paper on CO 2 packing polymorphism, 30 and by results published by other groups 31,32 we define fingerprints encoding information on crystal structures in the form of a set of probability densities. Following the extended pair distribution function approach at the heart of the definition of order parameters developed for molecular crystals, [33][34][35] we include in the fingerprints information on molecular position, relative orientation, and molecular conformation.…”

“…divergence used by Gobbo et al 31 or the generalized entropy introduced by Piaggi et al, 32 Identifying labile structures. Having defined a measure of the dissimilarity between crystal packings we can automate the identification of labile structures, i.e.…”

Molecular properties of interfaces relevant for clathrate hydrate agglomeration

“…Recent nucleation studies couple order parameters, defined using short-ranged correlations among molecules, with enhanced sampling techniques, e.g., metadynamics, to observe the rare events leading to nucleation. Gobbo et al recently proposed a systematic approach to develop order parameters that quantify the difference between distributed properties (e.g., long-ranged correlations) of a system and those of a crystalline structure [38]. This approach promises to be applicable to complex systems such as those in which hydrates form in pipelines.…”