MaMMoS · MAgnetic Multiscale MOdelling Suite

Magnetic materials are essential for many applications in energy, information, and communication technologies. However, the complex phenomena at different length and time scales often limit the development of new magnetic materials and devices. The goal of this project is to develop a magnetic multiscale modeling suite that will allow the design and optimisation of magnetic materials and devices based on multiscale modelling, characterisation, and numerical optimisation. To achieve interoperability between software and analysis tools, we will establish a domain ontology for magnetic materials. We will collaborate with EU magnet industry to create standards for linking simulation software for magnetic materials from first principles simulations and micromagnetics to device level simulators. MaMMoS will use artificial intelligence (AI) to fuse modeling and characterization data. AI methods will identify and correct systematic errors in the simulation data, enabling more accurate predictions. Moreover, AI models can fill gaps where measurements are not available. AI models can also serve as a surrogate in multi-objective optimisation. Optimisation will guide further experiments or simulations, reducing the development time. In MaMMoS, we will apply this approach to speed up the development of permanent magnets with reduced critical elements for electric machines and to optimise the layout of magnetic field sensors for high linearity range. The MaMMoS software will be validated against benchmarks defined according to the industrial requirements for electric machine and sensor design. The multiscale magnetic materials modeling suite will be made open source to enable easy access to high-end simulation tools. Interoperability will facilitate data sharing and reuse among researchers and industries. Interpretable machine learning will reveal insights into the physics and chemistry of magnetic materials and guide the discovery of new materials for the European green deal.