Our approach to material and manufacturing process development uses experimentally validated computational design codes to accelerate the insertion of new materials and components into advanced products and systems.
There is an ongoing global need for the development of new materials and with the rapid changes in technology the manufacturing process has not kept pace. New materials design and development is still being performed empirically which often requires thousands of individual experiments, resulting in high costs and long timeframes. Consequently, new models for materials design and processing are required to produce advanced materials quickly and inexpensively to keep up with global innovations.
Our research uses high performance computing and data science linking the material microstructure and properties to the manufacturing process, creating materials and components for specific applications. We use predictive modelling to rapidly focus the search for new and optimised materials and provide decision support to reduce empiricism. This is critical because materials problems are often non-linear, discontinuous and are dependent on the microstructure, which is consequent on interactions between composition and processing.