Our team is developing a scalable and commercially viable photocatalyst for a standalone photoelectrochemical cell that can generate hydrogen directly from the sun. A major challenge is the time-consuming and labour-intensive process of manually analysing experimental data. We can overcome this challenge by automating our experiments. Machine learning (ML) can provide a robust framework for correlating the known properties of materials with the properties of interest. This can be done quickly and accurately using large datasets. However, it is critical to obtain consistent data from samples produced under controlled and reproducible conditions. This can be achieved using our automated deposition and characterization setups. Our goal is to augment ML with automation to develop a self-driving laboratory for material discovery. This will allow us to rapidly and efficiently identify new and improved photocatalysts.
To be eligible to apply you must have (or expect to gain):
* International applicants must be residing in Australia and have the appropriate immigration approvals to allow them to take up the scholarship.
How to apply:
You will be required to: