Data Assimilation Method for Experimental and First-Principles Data: Finite-Temperature Magnetization of (Nd,Pr,La,Ce)${}_2$(Fe,Co,Ni)${}_{14}$B

Abstract

We propose a data-assimilation method for evaluating the finite-temperature magnetization of a permanent magnet over a high-dimensional composition space. Based on a general framework for constructing a predictor from two data sets including missing values, a practical scheme for magnetic materials is formulated in which a small number of experimental data in limited composition space are integrated with a larger number of first-principles calculation data. We apply the scheme to (Nd${}_{1-\alpha -\beta -\gamma }$Pr${}_{\alpha }$La${}_{\beta }$Ce${}_{\gamma }$)${}_2$(Fe${}_{1-\delta -\zeta }$Co${}_{\delta }$Ni${}_{\zeta }$)${}_{14}$B. The magnetization in the whole $(\alpha ,\beta ,\gamma ,\delta ,\zeta )$ space at arbitrary temperature is obtained. It is shown that the Co doping does not enhance the magnetization at low temperatures, whereas the magnetization increases with increasing $\delta$ above 320 K.

11 pages, 7 figures