Mechanistic analysis of perovskite degradation for stable photovoltaics

This project addresses the largest roadblock in perovskite research—stability—and aims to identify the most promising pathway(s) to enhance the stability. Powerful interpretable, quantitative materials analysis techniques will be developed via physics-based machine learning, leading to the discovery of degradation mechanisms and the extraction of dominant material parameters. With these insights, this project will deliver targeted strategies to enhance perovskite stability, accelerating the revolution of low-cost solar technology and decarbonising Australia’s economy. The new material analysis technique is adaptable to other materials and experiments, providing a new paradigm to the research community for developing novel semiconductors.

Funding

This project is funded by the Australian Research Council (DP260104659).

People

Dr Hualin Zhan

Theoretical physicist with expertise in machine learning since 2006.

Prof Kylie Catchpole

FAA, FTSE, ANU

Xin Wang

PhD student. Computer scientist.