Abstract
In the present work, we revise and extend the Characteristic Crystallographic Element (CCE) norm, an algorithm used to simultaneously detect radial and orientational similarity of computer-generated structures with respect to specific reference crystals and local symmetries. Based on the identification of point group symmetry elements, the CCE descriptor is able to gauge local structure with high precision and finely distinguish between competing morphologies. As test cases we use computer-generated monomeric and polymer systems of spherical particles interacting with the hard-sphere and square-well attractive potentials. We demonstrate that the CCE norm is able to detect and differentiate, between others, among: hexagonal close packed (HCP), face centered cubic (FCC), hexagonal (HEX) and body centered cubic (BCC) crystals as well as non-crystallographic fivefold (FIV) local symmetry in bulk 3-D systems; triangular (TRI), square (SQU) and honeycomb (HON) crystals, as well as pentagonal (PEN) local symmetry in thin films of one-layer thickness (2-D systems). The descriptor is general and can be applied to identify the symmetry elements of any point group for arbitrary atomic or particulate system in two or three dimensions, in the bulk or under confinement.
Highlights
In recent decades, computer simulations at the molecular level [1,2] have steadily proved to be an invaluable tool in understanding the connection between atomic structure and behavior and macroscopic properties of materials [3,4]
All results to be presented in the continuation have been obtained with a discretization step of 0.1 rad for all polar and azimuthal angles needed for the identification of the symmetry axi(e)s that minimize the Crystallographic Element (CCE) norm
We have presented a revised an extended version of the characteristic crystallographic element (CCE) descriptor, used to characterize local structure in general atomic and particulate systems in 2 or 3 dimensions, in the bulk or under confinement
Summary
Computer simulations at the molecular level [1,2] have steadily proved to be an invaluable tool in understanding the connection between atomic structure and behavior and macroscopic properties of materials [3,4]. In parallel, advanced software packages are available that allow efficient atomic/molecular visualization and/or analysis of the computer-generated structures including animation of the corresponding trajectories [5,6,7,8,9]. For crystallization and phase transitions, visual inspection is vital as it allows a better understanding of structural changes and provides a preliminary identification of the established ordered morphologies. It is critical to employ objective and quantitative methods in the analysis of local structure in computer-generated atomic and particulate systems
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