Join us in this engaging episode with Dr. Singh, who introduces us to an exciting application of machine learning in the realm of material science. He elucidates how chemical alloying can impact the formation enthalpy of rare-earth intermetallics.

The use of machine learning in rare-earth intermetallic design has been minimal, largely due to the limited availability of reliable datasets. To overcome this, Dr. Singh and his team have developed an extensive 'in-house' rare-earth database, containing over 600 compounds. Each entry in this database is enriched with formation enthalpy data and associated atomic features obtained using high-throughput density-functional theory (DFT).

With this resource at their disposal, Dr. Singh's team then applied the SISSO (Sure Independence Screening and Sparsifying Operator) based machine learning met ...