Visualization and analysis of atomistic simulation data with OVITO–the Open Visualization Tool
01 Jan 2010-Modelling and Simulation in Materials Science and Engineering (IOP Publishing)-Vol. 18, Iss: 1, pp 015012
TL;DR: The Open Visualization Tool (OVITO) as discussed by the authors is a 3D visualization software designed for post-processing atomistic data obtained from molecular dynamics or Monte Carlo simulations, which is written in object-oriented C++, controllable via Python scripts and easily extendable through a plug-in interface.
Abstract: The Open Visualization Tool (OVITO) is a new 3D visualization software designed for post-processing atomistic data obtained from molecular dynamics or Monte Carlo simulations. Unique analysis, editing and animations functions are integrated into its easy-to-use graphical user interface. The software is written in object-oriented C++, controllable via Python scripts and easily extendable through a plug-in interface. It is distributed as open-source software and can be downloaded from the website http://ovito.sourceforge.net/.
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TL;DR: Several of the fundamental algorithms used in LAMMPS are described along with the design strategies which have made it flexible for both users and developers, and some capabilities recently added to the code which were enabled by this flexibility are highlighted.
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TL;DR: In this paper, a discrete Burgers circuit integral over the elastic displacement field is used to identify partial and interfacial dislocations in atomistic models of crystals with defects, which is not limited to specific lattices or dislocation types.
Abstract: We present a computational method for identifying partial and interfacial dislocations in atomistic models of crystals with defects. Our automated algorithm is based on a discrete Burgers circuit integral over the elastic displacement field and is not limited to specific lattices or dislocation types. Dislocations in grain boundaries and other interfaces are identified by mapping atomic bonds from the dislocated interface to an ideal template configuration of the coherent interface to reveal incompatible displacements induced by dislocations and to determine their Burgers vectors. In addition, the algorithm generates a continuous line representation of each dislocation segment in the crystal and also identifies dislocation junctions.
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TL;DR: In this article, the authors discuss existing and new computational analysis techniques to classify local atomic arrangements in large-scale atomistic computer simulations of crystalline solids and introduce a new structure identification algorithm, the neighbor distance analysis, which is designed to identify atomic structure units in grain boundaries.
Abstract: We discuss existing and new computational analysis techniques to classify local atomic arrangements in large-scale atomistic computer simulations of crystalline solids. This article includes a performance comparison of typical analysis algorithms such as common neighbor analysis (CNA), centrosymmetry analysis, bond angle analysis, bond order analysis and Voronoi analysis. In addition we propose a simple extension to the CNA method that makes it suitable for multi-phase systems. Finally, we introduce a new structure identification algorithm, the neighbor distance analysis, which is designed to identify atomic structure units in grain boundaries.
985 citations
TL;DR: In this article, the authors discuss existing and new computational analysis techniques to classify local atomic arrangements in large-scale atomistic computer simulations of crystalline solids and introduce a new structure identification algorithm, the Neighbor Distance Analysis, that is designed to identify atomic structure units in grain boundaries.
Abstract: We discuss existing and new computational analysis techniques to classify local atomic arrangements in large-scale atomistic computer simulations of crystalline solids. This article includes a performance comparison of typical analysis algorithms such as Common Neighbor Analysis, Centrosymmetry Analysis, Bond Angle Analysis, Bond Order Analysis, and Voronoi Analysis. In addition we propose a simple extension to the Common Neighbor Analysis method that makes it suitable for multi-phase systems. Finally, we introduce a new structure identification algorithm, the Neighbor Distance Analysis, that is designed to identify atomic structure units in grain boundaries.
943 citations
TL;DR: In this paper, a method for extracting dislocation lines from atomistic simulation data in a fully automated way is described, which is called dislocation extraction algorithm (DXA), which generates a geometric description of dislocations lines contained in an arbitrary crystalline model structure.
Abstract: We describe a novel method for extracting dislocation lines from atomistic simulation data in a fully automated way. The dislocation extraction algorithm (DXA) generates a geometric description of dislocation lines contained in an arbitrary crystalline model structure. Burgers vectors are determined reliably, and the extracted dislocation network fulfills the Burgers vector conservation rule at each node. All remaining crystal defects (grain boundaries, surfaces, etc), which cannot be represented by one-dimensional dislocation lines, are output as triangulated surfaces. This geometric representation is ideal for visualization of complex defect structures, even if they are not related to dislocation activity. In contrast to the recently proposed on-the-fly dislocation detection algorithm (ODDA) Stukowski (2010 Modelling Simul. Mater. Sci. Eng. 18 015012) the new method is extremely robust. While the ODDA was designed for a computationally efficient on-the-fly analysis, the DXA method enables a detailed analysis of dislocation lines even in highly distorted crystal regions, as they occur, for instance, close to grain boundaries or in dense dislocation networks.
849 citations
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