Abstract
We describe and implement a structural search methodology which divides the global configuration space into enumerable subspaces, termed isopointal sets, and then searches within them using simulated annealing. This division allows us to follow a natural order for searching the infinite global configuration space, by respecting the observed tendency for molecular or colloidal particles to form crystals with a very limited set of local environments and symmetries. The method also produces near-optimal structural candidates with each symmetry searched, a useful feature for systems exhibiting polymorphic crystallization. We have applied this to dense packing simply-connected hard shapes in two dimensions, but the same method is applicable to optimizing arbitrary Hamiltonians, or ab-initio structural searches in higher dimensions.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
