Using a computationally driven screening to enhance magnetocaloric effect of metal monoborides

In most cases, substitution studies that aim to optimize magnetic properties are performed at the magnetic atomic site. However, in the case of MnB, magnetic substitutions at the Mn site significantly decrease the once promising magnetocaloric and magnetic properties. This study employs computationally directed search to optimize the magnetocaloric properties of MnB where partial substitutions of boron atoms (Mn50B50- (x) Si (x) and Mn50B50- (x) Ge (x) where x = 3.125, 6.25, and 12.5) reveal new compounds with a greater magnetocaloric effect than pure MnB at the same Curie temperature. These new compounds were obtained by arc melting the pure elements and further characterized. The computationally driven screening process is based on density functional theory calculations that do not require large databases of known compounds. This work demonstrates that using simple computational screening procedures to search for new magnetocaloric materials with improved properties can be done quickly, cost-effectively, and while maintaining reliability.