Grant: Strategic Projects - Group

This joint UBC-McMaster project brings together a group of Canada's leading Computational Materials Scientists with the goal of developing new process models based on computer modelling techniques spanning the atomistic to the macroscopic materials length-scales. Specifically, this project deals with the austenite-to-ferrite transformation in steels. This transformation constitutes the primary metallurgical tool used to generate the complex microstructures giving the superior properties of advanced high-strength steels. These new steels are primarily of significance for automotive applications where they enable the design of light-weight and, therefore, more fuel efficient vehicles. Similar developments in developing new steel grades are seen for pipelines and in the construction sector. These new steels require an increased level of alloying addition (e.g. Mn, Cr) to tailor the phase transformation and, as a value-added product, they require a significantly increased control of processing windows (e.g. in a hot mill) as compared to conventional steels. Thus, process models are critical to reduce property variability and to increase productivity that Canada's steel producers and users remain globally competitive. A particular challenge in developing a reliable process model for these new steels is that the effect of alloying elements on the austenite-to-ferrite transformation is poorly understood from a fundamental perspective. Thus, the proposed modelling approach employs an innovative methodology by modelling across different length scales. Process models are formulated on a macroscopic length scale while underlying physical parameters result from phenomena on the atomistic scale. Thus, modelling tools will be combined that cover different length scales, i.e. starting from ab-initio atomistic modelling of the interaction of alloying elements with the moving transformation front the modelling length scale will be gradually increased via the scale of the microstructure (i.e. so-called meso-scale) to the macro-scale of the industrial product. An integral part of the proposed approach is to validate the models with experimental and industrial data.