FEIT Research Project Database

From the atom to a turbine: Computational materials engineering of novel high-temperature materials

Project Leader: Christian Brandl
Collaborators: Ruth Schwaiger (Forschungszentrum J├╝lich, Germany)
Primary Contact: Christian Brandl (christian.brandl@unimelb.edu.au)
Keywords: computational materials science; deformability; machine learning; mathematical modelling
Disciplines: Mechanical Engineering

The future demand for higher energy efficiency in transportation and energy conversion hinges on the available high-temperature materials.

For the required significant increase in operating temperatures in energy conversion processes, new high-temperature alloys beyond tradition Ni-basis superalloys have to be explored.

Candidate materials that come to mind because of their high melting points are refractory metals. However, refractory elements typically brittle glass-like behaviour at low temperature, which jeopardises the structural integrity of turbines. Using atomistic simulations on high-performance computers, the candidate will identify and predict the key materials processes which classify metallic materials as brittle.

The goal is to develop a simulations-informed predictive design map of high-temperature materials.

The ideal candidate will have experience in materials. High-level computer skills, including MPI, and experience with various HPC platforms, is highly desirable.

The applicants must have a background in engineering or a relevant discipline in physics or chemistry. Applications from women are strongly encouraged.

Slip traces of a dislocation in atomistic simulations