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| OVITO | |
|---|---|
| Name | OVITO |
| Developer | Kurt Lehnert (University of Stuttgart may be associated) |
| Released | 2008 |
| Programming language | Python (programming language), C++ |
| Operating system | Microsoft Windows, Linux, macOS |
| Genre | Scientific visualization, Materials science |
| License | Proprietary software / Free software (dual-licensed) |
OVITO
OVITO is a scientific visualization and analysis application widely used in materials science, computational physics, and computational chemistry for processing atomistic simulation data. It provides tools for inspecting trajectories from molecular dynamics, evaluating structural metrics developed in studies by groups like Molecular Dynamics (MD) research community and visualizing results for conferences such as Materials Research Society meetings and publications in journals like Physical Review Letters and Journal of Chemical Physics. Developed to bridge simulation engines and visualization, the software integrates with workflows from packages such as LAMMPS, GROMACS, VASP, DL_POLY, and HOOMD-blue.
OVITO originated to serve researchers handling large-scale atomistic datasets generated by engines including LAMMPS, GROMACS, and VASP. It emphasizes interactive investigation and reproducible post-processing of trajectories produced in projects tied to institutions like Max Planck Society, Lawrence Berkeley National Laboratory, and Argonne National Laboratory. The project has been presented at conferences such as International Conference on Computational Materials Science and adopted in courses at universities including Massachusetts Institute of Technology and ETH Zürich. Its ecosystem intersects with community standards and file formats established by groups associated with OpenKIM and the Materials Genome Initiative.
OVITO implements a variety of analysis pipelines for atomistic datasets including calculation of coordination numbers, identification schemes derived from methods pioneered by researchers like Steinhardt and Nelson (physicist), and computation of per-atom properties used in studies published in Nature Materials and Science Advances. Typical operations include cluster finding used in work from groups at Oak Ridge National Laboratory, dislocation analysis rooted in methods discussed by Vitek, surface detection comparable to approaches in surface science literature, and strain tensor calculations similar to those in reports by National Institute of Standards and Technology. Visualization styles support rendering strategies seen at SIGGRAPH and image preparation for journals such as Nature Communications.
The software supports importing trajectory and structure files common to major simulation packages: LAMMPS dump, GROMACS XTC/TRR, VASP POSCAR/CONTCAR, and XYZ among others. It also reads output from force-field and potential repositories like OpenKIM and interoperates with formats exchanged in projects involving OpenBabel and ASE (Atomic Simulation Environment). Support for metadata and per-atom properties enables integration with dataset standards promoted by initiatives such as Materials Project and archives hosted by NIST.
OVITO provides an interactive viewport supporting techniques familiar to users of ParaView, VMD (Visual Molecular Dynamics), and Blender for 3D rendering, camera control, and publication-quality image export. Its GUI supplies pipeline-based editing, layer controls, and property browsers akin to interfaces in ImageJ and MATLAB (software), enabling preparation of figures for venues like APS March Meeting and Euromat. Visual styles include ball-and-stick, polyhedral rendering, slicing, and volumetric mapping used in works from Center for Functional Nanomaterials and visualization tutorials at IEEE VIS.
A built-in Python interpreter exposes an API modeled on practices from the Scientific Python ecosystem, facilitating automation comparable to scripting workflows in NumPy, SciPy, and pandas (software). Users write custom modifiers and data pipelines drawing on concepts from scikit-image and integrate with plotting libraries such as Matplotlib and Plotly. Plugin support and a community-contributed repository enable extensions influenced by projects hosted on GitHub and collaborative efforts within research groups at University of Cambridge and Imperial College London.
OVITO is optimized for large datasets produced by high-throughput computing resources at centers like Oak Ridge National Laboratory and Lawrence Livermore National Laboratory. Core routines are implemented in C++ with multithreading paradigms similar to those used in OpenMP and parallel IO strategies paralleling efforts in HDF5 and MPI-based projects. GPU-accelerated rendering and compute kernels echo techniques developed for tools like HOOMD-blue and benefit users working with supercomputers from consortia such as PRACE and XSEDE.
Researchers employ the application for analyzing defects, grain boundaries, dislocation networks, and phase transitions in studies reported to journals including Acta Materialia, Physical Review B, and Applied Physics Letters. It features in workflows for nanoparticle morphology characterization used by groups at Lawrence Berkeley National Laboratory and in simulating tribology studies conducted at ETH Zürich and TU Delft. Industrial R&D teams in sectors such as semiconductor research at Intel and materials design at BASF leverage OVITO for pre-publication visualization, while educators adopt it for laboratory exercises at institutions like University of California, Berkeley and University of Oxford.
Category:Materials science software