Computational search for RE-free and RE-lean permanent magnets
Abstract
Permanent magnets (PM) are an essential part of the green energy transition and are used in large amounts in electric vehicle motors (up to 2 kg/car) and windmill generators (400-600 kg). However, commercially used PMs nowadays rely heavily on rare-earth elements, which are problematic from geopolitical and environmental points of view. The search for new suitable materials is conducted globally, both on theoretical and experimental fronts, where theory is meant to guide and speed up the experimental work. New approaches are often used, such as data mining and machine learning, where material databases are available and new stable materials are generated in an attempt to go beyond the existing databases. This project aims to suggest new ways of predicting the necessary materials’ properties, which will assist in future data mining and machine learning (ML) searches. The second goal is looking at some promising materials where only one or two necessary characteristics are missing for possible fine-tuning. Alena Vishina (AV) has been working in the area of PM for more than 6 years and has a large necessary experience to conduct the project.
