US scientists have developed a new phase field model to describe nucleation and growth in a material’s microstructure.
The properties of most engineered materials are highly-dependent on their initial microstructure or nanostructure, and on how they evolve during processing. From thin-films to high-strength alloys, developing an understanding of phase transitions, nucleation and growth mechanics, is step one in the design of new materials. And for this, a range of theoretical and numerical tools are needed.
One route that has been widely used to describe everything from decomposition to solidification, is the phase field approach. In it, the entire microstructure is represented by one or more continuous variables, and nucleation can either be homogeneous or heterogeneous (using noise-based methods), or stochastic (by introducing a nuclei into the simulation).
In this latest work, researchers at the Idaho National Laboratory and the University of Michigan refined the existing stochastic algorithm to produce a method that is not only easier to implement, but also naturally satisfies the conservation law. Because only the nonconserved order parameter is modified, this new method, highlighted as Editor’s Choice in the October issue of Computational Materials Science [DOI: 10.1016/j.commatsci.2015.10.009], has been dubbed order-parameter-only, or OPO, seeding.
A zirconium/zirconium hydride model was used to test OPO’s applicability and to compare it an existing method which varies both the order parameter and the solute concentration (this approach is called OPC seeding). The evolution of nucleation and growth in the system were studied, and fitted to the Avrami equation (for phase transitions). The analysis found that OPO nucleation yields similar precipitate growth characteristics to that of the existing OPC model, but that it was more computationally efficient. In addition, while OPO was implemented here in a finite element framework, it is also compatible with finite difference, and could model a broad range of nucleation conditions in materials systems.
The study’s lead author Prof Katsuyo Thornton said:
“When and where precipitates form determines a material’s microstructure, and this significantly influences its properties and performance. Therefore, it is critically important to capture the underlying mechanism. This new algorithm provides an easier method for implementing the detailed physics of nucleation in various simulation tools. And this in turn enhances our ability to predict microstructure evolution.”
A.M Jokisaari, C. Permann, K. Thornton - Computational Materials Science 112 (2016) 128–138, “A nucleation algorithm for the coupled conserved–nonconserved phase field model” DOI: 10.1016/j.commatsci.2015.10.009