Accelerating the Development of Novel Soft Magnetic Materials

Abstract: The next generation of materials for electrical machines must possess an attractive combination of multiple properties. However, developing such materials using conventional approaches is expensive and time-consuming. In contrast, the accelerated discovery approach relies on high-throughput synthesis, characterization, property evaluation, and predictive AI/ML modelling to rapidly screen many compositions. We deployed several advanced high-throughput techniques, such as additive manufacturing, spark plasma sintering, chemical flow synthesis, magnetron co-sputtering, thermodynamic modelling, and machine learning to quickly discover new high-performance materials. As an example, laser additive manufacturing techniques, direct energy deposition (DED) and/or powder bed fusion (PBF), are used to produce Fe-Co-Ni, Fe-Co-Ni-xAl, Fe-xSi, etc. material libraries. Compositions with an optimum magnetic-mechanical-electrical property set, required for next generation energy conversion machines, have been identified. Our results demonstrate the attractiveness of high throughput techniques for the quick development of high-performance materials.

Biography: Dr Varun Chaudhary is an assistant professor in the Department of Industrial and Materials Science at Chalmers University of Technology, Sweden. He received his Ph.D. from the Interdisciplinary Graduate School at Nanyang Technological University (NTU), Singapore, and his M.Tech. in Materials Science from Indian Institute of Technology, Kanpur. Previously, Dr. Chaudhary was a Senior Research Fellow at the School of Materials Science and Engineering at NTU, Singapore. He has also served as a DST Research Fellow at the National Physical Laboratory, New Delhi, and as a Research Scientist at Rolls-Royce Corporate Lab, Singapore.

Dr. Chaudhary’s research is centred on a wide range of magnetic materials tailored for energy applications. His specific areas of interest include magnetocaloric materials, soft magnets, permanent magnets, high entropy alloys, functionally graded materials, accelerated materials development, additive manufacturing, artificial intelligence and machine learning.