Rare Earth permanent magnets are found in various aspects of modern life, ranging from computers to maglev trains, power tools to MRI scanners. Their significance cannot be overemphasized, as life without them would be challenging. Nonetheless, the extraction of rare Earth elements for these magnets is often a laborious and energy-intensive process. Scientists have been searching for an improved method, and it appears that they may have found one with the help of a machine learning algorithm. Materials Nexus, in collaboration with researchers from the Henry Royce Institute and the University of Sheffield, has developed MagNex, a free-of-rare-earth-elements permanent magnet. MagNex is reportedly produced with materials that cost only one-fifth of regular permanent magnets. Additionally, this new magnet has reduced carbon emissions by 70 percent (in terms of kilograms of CO2 per kilogram of material) compared to rare-Earth permanent magnets. The significance of these advancements extends beyond the immediate benefits. Traditional permanent magnets were developed from rare-Earth element alloys, a process that involved extensive and time-consuming explorations for the right materials.

In contrast, the development of MagNex, from design to testing, was 200 times faster. "We’re thrilled that our collaboration with Materials Nexus has yielded such an incredibly positive outcome, " commented Professor Iain Todd FREng, Professor of Metallurgy and Materials Processing at the University of Sheffield. The combination of Materials Nexus' AI-based materials discovery approach and the advanced alloy manufacturing capabilities at the Henry Royce Institute in Sheffield resulted in the rapid development of a novel magnetic material. This achievement showcases the promising future of materials and manufacturing. The utilization of AI to unlock the potential of next-generation materials offers great promise for research, industry, and sustainability. The AI system analyzes over 100 million potential alloy compositions to identify those with the desired properties of a permanent magnet, free of rare-earth elements, and meeting affordability and sustainability requirements. This approach has significant potential for the creation of new materials. "This groundbreaking discovery, facilitated by innovative machine learning software, has been made possible through Innovate UK funding, " stated Bruce Adderley, Director for Make & Use – Net-Zero at Innovate UK. "It has the potential to significantly impact our net-zero ambitions, particularly in renewable energy and low-carbon transport, by eliminating the need for rare earth elements in high-performance permanent magnets. " Computers have already played a significant role in the discovery of new substances. Now, machine learning algorithms and similar approaches are being employed in laboratory settings, such as the self-driving lab developed at the University of Toronto.