(124h) Genarris 2.0: A Random Structure Generator for Molecular Crystals | AIChE

(124h) Genarris 2.0: A Random Structure Generator for Molecular Crystals

Authors 

Marom, N. - Presenter, Carnegie Mellon University
Tom, R., Carnegie Mellon University
Bier, I., Carnegie Mellon University
Rose, T., Carnegie Mellon University
O'Brien, H., Carnegie Mellon University
Genarris 2.0 is an open source Python package for performing configuration space screening by random structure generation for crystals of molecules with no bond-rotational degrees of freedom. The target unit cell volume is determined by estimating the molecular volume. Crystal structures are then generated in all space groups compatible with the requested number of molecules per cell (Z) with one molecule in the asymmetric unit (Z’=1), including those with special Wyckoff positions. To avoid generating unphysical structures, constraints are applied on the intermolecular distances, based on van der Waals radii. Special settings are applied for strong hydrogen bonds, which are automatically detected. Once an initial dataset of several thousand structures is generated, a smaller curated dataset may be selected based on user-defined quality and diversity criteria to serve as an initial guess for structure search algorithms or as a training set for machine learning. For clustering based on packing motif similarity Genarris uses the affinity propagation machine learning algorithm with either a relative coordinate descriptor (RCD) or a radial distribution function (RDF) representation.