Driving forward the future of magnetic materials through advanced micromagnetic simulation

这项工作的重点将是模拟不同磁性材料的响应，包括扩散、晶界和晶粒形状等影响。此外，我们将把结果与机器学习相结合，以绘制出可能的优化结构，重点关注体积分数、几何构型和所需的材料特性，从而提供设计标准。最后，我们将着眼于实现更大、更粗尺度的模拟，使用从更小、更详细的模拟中收集的结果，以确定这些局部特性如何影响原位性能。该博士与我们小组的其他博士生紧密结合，也得到了大众的支持，大众将提供实验支持。他们将能够为模型生成关键输入数据，并测试任何预测和设计标准，模拟生成的结果可以反馈到模型中。

The focus of this work will look at simulating the response from different magnetic materials and include effects such as diffusion, grain boundaries and grain shape. Furthermore, we shall combine the results with machine learning in order to map out possible optimised structures with a focus on volume fraction, geometrical configuration and desired material properties, in order to provide design criteria. Finally, we shall look towards implementing larger, coarser scale simulations, using the results gather from the smaller, detailed ones, to identify at how these local properties effect in-situ performance. The PhD is strongly aligned to other PhD students in our group, also supported by VW, who will be providing experimental support. They will be able to generate key input data for the models as well as test any predictions and design criteria the simulations generate results of which can be fed back into the models.