Mu-PRO磁电材料微结构和性能相场模拟软件

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μ-PRO® is a software package, with user-friendly command line/ graphical interfaces* and manuals, for materials researchers    in academia and industry to model and predict the temporal evolution of materials internal local microstructures    and properties as well as overall responses of an entire microstructure under externally mechanical, electric or magnetic fields, and thus to guide the understanding of experimental observations on existing materials or the    design and discovery of new materials microstructures.

CURRENTLY AVAILABLE MODULES

01

Ferroelectric

For modeling 3D polarization domain structure evolution under external thermal, chemical, electrical, and mechanical stimuli in bulk single crystals, epitaxial thin films, and nanostructures.
1.1 Functionality: Establish Phase Diagrams
1.2 Functionality: Evolving Domain Structures1.3 Functionality:  Predict Various Domain Structures

1.4 Functionality: Domain under Tips

1.5 Functionality: Material Design

02

Ferromagnetic

  For modeling 3D temporal evolution of local magnetization in response to external mechanical, magnetic, current-induced spin torque stimuli  in bulk, thin film, nanostructural crystalline and amorphous magnetic materials. 
     2.1 Functionality: Establish Phase Diagrams
     2.2 Functionality: Evolving Domain Structures

2.3 Functionality: Modeling MOKE and Switching


     2.4 Functionality: Material Design

03

Properties

For computing  effective properties of arbitrary microstructure ranging from diffusivity, thermal conductivity, electrical conductivity, elastic stiffness, dielectric permittivity to coupled properties such as piezoelectric coefficients, magnetoelectric coefficients with experimentally characterized or computed microstructures as inputs.
3.1 Functionality: Calculate Local Electric Field Distributions
3.2 Functionality: Calculate current density distribution and effective electric conductivity.

3.3 Functionality: Calculate local electric and mechanical distribution and effective piezoelectriccoefficients.
3.4 Functionality: Calculate effective electric conductivity and design solid electrolyte.
3.5 Functionality: Calculate local concentration of ions and effective diffusion coefficients

扩展阅读

 npj: 机器学习的四个方面：神、人、用、梦
npj: 材料合成过程的半监督机器学习分类
npj: 机器学习—快速精确预测电子结构问题
npj: 分析机器学习模型-加速材料的基础认识

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