Photocatalysis offers a promising pathway for the direct conversion of solar energy into valuable chemical feedstocks, such as hydrogen and (oxy)hydrocarbon products. However, progress in the field is hindered by the slow discovery of efficient photocatalysts, a limited understanding of structure-activity relationships, and the lack of rapid and reliable tools for assessing photocatalyst performance under realistic operating conditions.
The project will develop and integrate high-throughput photocatalytic screening methods to evaluate photocatalyst properties and performance for hydrogen production and selective organic synthesis. Key variables, including semiconductor materials, cocatalysts, and organic substrates, will be systematically investigated to identify performance descriptors that govern photocatalytic activity and selectivity. By combining rapid photocatalytic testing with data-driven machine learning analysis, the project aims to establish a robust methodology for accelerating the discovery of efficient solar photocatalysts.
School
Chemical Engineering
Research Area
Chemical engineering | Photocatalysis | Renewable energy | Solar fuels
Suitable for recognition of Work Integrated Learning (industrial training)?
No
- Research environment
- Expected outcomes
- Supervisory team
- Reference material/links
The student will have the opportunity to join the Particles and Catalysis Research Group (PartCat) under the supervision of Dr. Denny Gunawan, Dr. Jodie Yuwono, and Prof. Rose Amal. The student will have access to state-of-the-art laboratories equipped with advanced experimental facilities and computational tools for photocatalysis research. This project offers a multidisciplinary research environment where the student will develop a broad set of technical and professional skills, supporting future career opportunities in both academia and industry.
- The student is expected to gain hands-on experience in photocatalyst synthesis, characterisation, activity measurement techniques, and the application of machine learning. The project will also allow the student to work with other research students to gain valuable interdisciplinary experience. The generated knowledge and data will result in a scientific journal publication. Continuation of the research as an Honours thesis project is possible.
- Gunawan, D. et al. (2024). Materials Advances in Photocatalytic Solar Hydrogen Production: Integrating Systems and Economics for a Sustainable Future. Adv. Mater. 36, 2404618.
- Toe, C. Y. et al. (2021). Advancing Photoreforming of Organics: Highlights on Photocatalyst and System Designs for Selective Oxidation Reactions. Energy Environ. Sci. 14, 1140-1175.
- Masood, H. et al. (2019). Machine Learning for Accelerated Discovery of Solar Photocatalysts. ACS Catal. 9, 12, 11774-11787.