Prof. Kenji Katayama and a former group member, Makoto Eibihara at Chuo University have developed a new method for visualization of local charge transport in the process of photocatalytic water splitting. They studied a highly efficient photocatalytic sheet developed by Prof. Kazunari Domen at the University of Tokyo and Shinshu University and Dr. Hiromasa Tokudome and colleagues at TOTO Ltd. This technology is based on the combination methodology of the image analysis in informatics and the time-resolved microscopic imaging developed by Prof. Katayama and colleagues. This research could lead us to clarify the fundamental processes of photocatalytic water splitting materials and devices.
Photocatalytic water splitting is a reaction where hydrogen and oxygen are generated simply from water by using solar energy. This solar hydrogen has been expected to be a next-generation renewable energy source, and a large-scaled pilot plant has been demonstrated and developed in progress. In this research, the transport process of the photo-excited charges was visualized for an up-to-date photocatalytic sheet, which was designed to deploy on a large scale by TOTO Ltd. and the University of Tokyo.
So far, it has been difficult to detect the photo-generated charges for the generation of hydrogen and oxygen by photocatalytic reactions. However, Prof. Katayama and colleagues has made it possible by developing new time-resolved phase microscopy and further analyzing the behavior based on informatics theory. Based on the distinction of the charges could reveal the local reaction activities.
This methodology can be utilized for the optimization of materials via the catalytic activity analysis for various photocatalytic materials for water splitting. They expect to commercialize the equipment and the method in five years by further improving it for large-scale (m2
) and automatic measurements.
The contents will be published online in Nature Communications on June 17, 2021.
“Charge Carrier Mapping for Z-scheme Photocatalytic Water-Splitting Sheet via Categorization of Microscopic Time-resolved Image Sequences”
Springer Nature, Nature Communications, 12, 3716 (2021) DOI: 10.1038/s41467-021-24061-4
If you are interested in the research, please click the below link:
Katayama Group, Chuo University: Spectroscopy and Photochemistry