Data Mining for Parameters Affecting Polymorph Selection in Contorted Hexabenzocoronene Derivatives.

ABSTRACT: The macroscopic properties of molecular materials can be drastically influenced by their solid-state packing arrangements, of which there can be many (e.g., polymorphism). Strategies to controllably and predictively access select polymorphs are thus highly desired, but computationally predicting the conditions necessary to access a given polymorph is challenging with the current state of the art. Using derivatives of contorted hexabenzocoronene, cHBC, we employed data mining, rather than first-principles approaches, to find relationships between the crystallizing molecule, postdeposition solvent-vapor annealing conditions that induce polymorphic transformation, and the resulting polymorphs. This analysis yields a correlative function that can be used to successfully predict the appearance

SUBMITTER: Hiszpanski AM 

PROVIDER: S-EPMC6550467 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature