论文标题
实验和第一原理数据的数据同化方法数据：（ND，PR，LA，CE）的有限温度磁化$ _ {2} $（Fe，Co，ni）$ _ {14} $ _ {14} $ b
Data Assimilation Method for Experimental and First-Principles Data: Finite-Temperature Magnetization of (Nd,Pr,La,Ce)$_{2}$(Fe,Co,Ni)$_{14}$B
论文作者
论文摘要
我们提出了一种数据鉴别方法，用于评估在高维成分空间上永久磁体的有限温度磁化。基于一个从包括缺失值在内的两个数据集构造预测因子的一般框架，制定了一种实用的磁性材料方案，其中有限组合空间中的少量实验数据与大量的第一原理计算数据集成在一起。我们将方案应用于（nd $ _ {1-α-β-γ} $ pr $_α$ la $_β$_β$_γ$_γ$）$ _ {2} $（Fe $ _ {1-Δ-δ-ζ} $_Δ获得了整个$（α，β，γ，δ，ζ）$空间在任意温度下的磁化。结果表明，在低温下，CO掺杂不会增强磁化强度，而磁化强度随着$δ$以上的增加而增加。
We propose a data-assimilation method for evaluating the finite-temperature magnetization of a permanent magnet over a high-dimensional composition space. Based on a general framework for constructing a predictor from two data sets including missing values, a practical scheme for magnetic materials is formulated in which a small number of experimental data in limited composition space are integrated with a larger number of first-principles calculation data. We apply the scheme to (Nd$_{1-α-β-γ}$Pr$_α$La$_β$Ce$_γ$)$_{2}$(Fe$_{1-δ-ζ}$Co$_δ$Ni$_ζ$)$_{14}$B. The magnetization in the whole $(α, β, γ, δ, ζ)$ 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 $δ$ above 320 K.
