Accelerated design for magnetocaloric performance in Mn-Fe-P-Si compounds using machine learning

Magnetocaloric performance is of vital importance for Mn-Fe-P-Si alloys. However, when processes and compositions are considered, designing alloys with large magnetic entropy changes (ΔSm), low thermal hysteresis (ΔThys), and Curie temperatures (TC) around room temperature become relatively complicated. In this study, we adopt machine learning methods to predict the magnetocaloric performance of Mn-Fe-P-Si compounds for the first time. To...