pyMolDyn is an interactive viewer of atomic systems defined in a unit cell and is particularly useful for crystalline and amorphous materials. It identifies and visualizes cavities (vacancies, voids) in simulation cells corresponding to all seven 3D Bravais lattices, makes no assumptions about cavity shapes, allows for atoms of different size, and locates the cavity centers (the centers of the largest spheres not including an atom center). We define three types of cavity and develop a method based on the split and merge algorithm to calculate all three. The visualization of the cavities uses the marching cubes algorithm. The program allows one to calculate and export pair distribution functions (between atoms and/or cavities), as well as bonding and dihedral angles, cavity volumes and surface areas, and measures of cavity shapes, including asphericity, acylindricity, and relative shape anisotropy. The open source Python program is based on GR framework and GR3 routines and can be used to generate high resolution graphics and videos. © 2016 Wiley Periodicals, Inc.

One of the key aspects of good scientific practice is the handling of research data (German Research Foundation, 2019). Archiving research data and making it findable, accessible, interoperable and re-usable by other researchers is crucial for reproducibility and can also yield new findings (Wilkinson et al., 2016). This is not only true for research data resulting from experiments or simulations, but particularly for information on how a sample was created, how a measurement was performed and which parameters were used for a simulation. SampleDB is a web-based sample and measurement metadata database developed at Jülich Centre for Neutron Science (JCNS) and Peter Grünberg Institute (PGI). Researchers can use SampleDB to store and retrieve information on samples, measurements and simulations, analyze them using Jupyter notebooks, track sample storage locations and responsibilities and view sample life cycles.

Landau-Lifshitz-Gilbert (LLG) spin-dynamics calculations based on the extended Heisenberg Hamiltonian is an important tool in computational materials science involving magnetic materials. LLG simulations allow to bridge the gap from expensive quantum mechanical calculations with small unit cells to large supercells where the collective behavior of millions of spins can be studied. In this work we present the AiiDA-Spirit plugin that connects the spin-dynamics code Spirit to the AiiDA framework. AiiDA provides a Python interface that facilitates performing high-throughput calculations while automatically augmenting the calculations with metadata describing the data provenance between calculations in a directed acyclic graph. The AiiDA-Spirit interface thus provides an easy way for high-throughput spin-dynamics calculations. The interface to the AiiDA infrastructure furthermore has the advantage that input parameters for the extended Heisenberg model can be extracted from high-throughput first-principles calculations including a proper treatment of the data provenance that ensures reproducibility of the calculation results in accordance to the FAIR principles. We describe the layout of the AiiDA-Spirit plugin and demonstrate its capabilities using selected examples for LLG spin-dynamics and Monte Carlo calculations. Furthermore, the integration with first-principles calculations through AiiDA is demonstrated at the example of γ–Fe, where the complex spin-spiral ground state is investigated.

Abstract-pyMolDyn is an interactive viewer of atomic systems defined in a unit cell and is particularly useful for crystalline and amorphous materials. It identifies and visualizes cavities (vacancies, voids) in simulation cells corresponding to all seven 3D Bravais lattices, makes no assumptions about cavity shapes, allows for atoms of different size, and locates the cavity centers (the centers of the largest spheres not including an atom center). We define three types of cavity and develop a method based on the split and merge algorithm to calculate all three. The visualization of the cavities uses the marching cubes algorithm. The program allows one to calculate and export pair distribution functions (between atoms and/or cavities), as well as bonding and dihedral angles, cavity volumes and surface areas, and measures of cavity shapes, including asphericity, acylindricity, and relative shape anisotropy. The open source Python program is based on GR framework and GR3 routines and can be used to generate high resolution graphics and videos.