8 November 2022
Magnetic materials currently employed in electric motors and generators were discovered in exploratory laboratory work, usually by trial and error. Finding ways to discover new materials, more efficient and sustainable, by computer predictions is very attractive, with high potential.
One of the main difficulties to computationally predict the performance of magnetic materials is the thermodynamic nature of their relevant properties. It is not easy to make the bridge between standardized Density Functional Theory (DFT) calculations, valid only at zero Kelvin temperature, to properties at finite temperatures.
João Amaral, Assistant Researcher at CICECO – Aveiro Institute of Materials, has been developing new simulation tools to accelerate the discovery of new magnetic materials for energy applications. The methodology makes use of DFT calculations at 0 K to predict various crucial thermodynamic properties for real-world performance of these materials. This way, the scientific community can, in a computationally efficient way, computationally predict the performance of new materials, screening them before moving on to laboratory synthesis.
The computational approach is based on building a database of the joint density of states of various atomic lattices and magnetic interactions. The advantage is that, with this information, the calculation of thermodynamic properties is fast and rigorous. Still, building this database requires intense calculations which may take months or even years to run in conventional computers.
The European High Performance Computing initiative (EuroHPC), through a Joint Undertaking between various public and private infrastructures, allows access to worldwide top ranked computing centers. One of these infrastructures is LUMI, a supercomputer based near the city of Kajaani, in Finland. With around 200 thousand AMD EPYC computing cores, this computational power allows for extremely demanding simulations, impossible to perform in useful time in conventional computers. In terms of sustainability, LUMI uses its own generated heat for the warming of the surrounding urban area. This smart use of thermal energy covers 20% of heating energy costs in the city area of Kajaani, saving the equivalent of 12.4 tons of CO2.
With the approval of 850 thousand hours of computation time at LUMI, the database necessary for the discovery of new magnetic materials for energy applications is now being built at breakneck speed.
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