Abstract
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.
Highlights
Magnetic materials play an important role in modern technology
The classical Heisenberg model is an approximation to the quantum mechanical problem which assumes that the magnetic moments are localized on atoms and can be described as classical vectors which is applicable for a wide range of materials
We demonstrate how the integration of the Spirit code into the AiiDA framework through the AiiDA-Spirit plugin can facilitate multi-scale modeling for magnetic materials
Summary
Magnetic materials play an important role in modern technology Their most important applications range from electrical motors to the storing and processing of digital information. While quantum mechanical calculations allow to predict the interaction strength among magnetic atoms (Liechtenstein et al, 1987), large scale simulations for nanometer to micrometer length scales are unfeasible due to their computational cost. Mapping these interactions to a classical Heisenberg model allows to bridge the scales from the atomic length scale to the length scale of devices. The classical Heisenberg model is an approximation to the quantum mechanical problem which assumes that the magnetic moments are localized on atoms and can be described as classical vectors which is applicable for a wide range of materials
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