You are cordially invited to attend MMRI Special Seminar
“Catalyst, Energy Conversion and Storage”
Dr. Sebastian Sprick
University of Liverpool / Materials Innovation Factory
Department of Chemistry,
Date: Friday 10th May 2019
Place: Meeting Room 12th Floor, Metallurgy and Materials Science Research Institute, Chulalongkorn University
Register at: https://tinyurl.com/mmri052019
MMRI Special Seminar “SOLAR FUEL PRODUCTION FROM WATER USING ORGANIC PHOTOCATALYSTS”
by Dr. REINER SEBASTIAN SPRICK
Department of Chemistry and Materials Innovation Factory, University of Liverpool, United Kingdom.
Photocatalytic hydrogen production from water is a research area of immense interest as hydrogen has been identified as a potential energy carrier of the future. Most of the studied photocatalysts are inorganic and organic materials have been far less studied, with the exception of carbon nitride materials. Here, I will present our work on the application of conjugated microporous polymers (CMPs),1-3 unbranched conjugated polymers,4,5 and covalent organic frameworks (COFs)6 as photocatalysts for hydrogen production from water. All photocatalysts were made from organic building blocks at low temperatures which allows for good control of their properties. I will discuss synthetic approaches in tuning of their light absorption and band alignment,7 crystallinity,6 particle size8 and wettability5,9 for improved photocatalytic activity.
Understanding of these systems was gained using transient absorption spectroscopy monitoring the temporal evolution of photogenerated reaction intermediates on slow and ultrafast timescales.5 This allowed us to draw a comprehensive picture of the processes that take place upon photoexcitation and to correlate the anion transient signal with the activity of the respective polymer. Furthermore, we used quasi-elastic neutron scattering to study water within the pores of CMP photocatalysts.3 We recently used automation to produce a large set of polymer photocatalysts that were studied for their performance. The data was then coupled with machine learning and we explored underlying factors beyond the ones previously considered by us in photocatalysis.