Fe-Pd-X Thin Film-Polymer Composites for Sensor Applications - First-principles evaluation of magneto-crystalline anisotropy and related intrinsic properties of Fe-Pd-X: optimization of alloy composition

该项目是合作的一部分，旨在开发用于传感器应用的新型磁性形状记忆Fe-Pd-X合金。磁性形状记忆合金（MSMA）近年来受到广泛关注。由于Ni2MnGa中高达10%的大磁致应变，它们对致动器应用很感兴趣。然而，由于低阻挡力，这种材料的应用受到限制。Fe70Pd30合金是一种很有前途的MSMA，其应变较小，但阻塞应力显著高于10 MPa。通过添加第三元素对该合金进行优化是促进其在传感器中的应用的必要条件。在这里，第一性原理计算被设想为(i)获得对Fe-Pd合金的本征性质（自发磁化，四方畸变，磁晶各向异性）的基本理解，（ii）如果添加其他元素来产生三元（四元）Fe-Pd- x （-Y）体系，则预测本征性质的变化。低外场和消失外应力下的场致应变与自发磁化成正比，而可达到的最大应变和阻滞应力不可避免地由磁晶各向异性能决定。因此，要判断某种合金的技术适用性，就必须了解这两种性质。另一方面，MSMA的磁晶各向异性难以测量。因此，第一性原理计算对于预期性质的预测和对测量数据的理解都是必需的。

This project is part of a collaboration aiming at new magnetic shape memory Fe-Pd-X alloys for sensor applications. Magnetic shape memory alloys (MSMA) have received much attention in recent years. They are of interest for actuator applications due to large magnetically induced strains of up to 10% in Ni2MnGa. However, application of this material is restricted due to low blocking forces. A promising MSMA is the Fe70Pd30 alloy with smaller strains but significantly higher blocking stresses of 10 MPa. Optimization of this alloy by adding third elements is necessary to facilitate its application in sensors. Here, first-principles calculations are envisaged to (i) gain fundamental understanding of the intrinsic properties (spontaneous magnetization, tetragonal distortion, magneto-crystalline anisotropy) of Fe-Pd alloys and (ii) predict the change of intrinsic properties if other elements are added to produce ternary (quaternary) Fe-Pd-X(-Y) systems. While the field-induced strain at low external field and vanishing external stress is proportional to the spontaneous magnetization, the achievable maximum strain and the blocking stress are unavoidably determined by the magneto-crystalline anisotropy energy. Thus, knowledge of both intrinsic properties is necessary to judge the technological applicability of a certain alloy. On the other hand, the magneto-crystalline anisotropy of MSMA is difficult to measure. Thus, first-principles calculations are needed both for the prediction of expected properties and for the understanding of measured data.