FEIT Research Project Database

Materials for a safe hydrogen economy


Project Leader: Christian Brandl
Primary Contact: Christian Brandl (christian.brandl@unimelb.edu.au)
Keywords: computational materials science; machine learning; Nanostructures
Disciplines: Mechanical Engineering
Domains:

The future hydrogen roadmap for sustainable energy relies on the stability of metals against deteriorating effects of hydrogen. This hydrogen embrittlement happens at the nanometer scale. The failure, though, is manifested at the macroscopic scale by brittle glass-like failure.

The pathway of hydrogen into and through the materials is investigated using state-of-the-art atomistic simulations used for a machine-learning strategy for materials design. With the computed material’s behaviour, machine-learning algorithms can be trained to explore new and as-yet-unknown 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.