Accelerated Discovery of Solar Hydrogen Photocatalyst

December 6th, 2021

R&D Focus Areas:
Photochemical and photocatalytic processes, Thermal water splitting, Materials modelling

Lead Organisation:
University of New South Wales (Sydney)

Partners:
City University of Hong Kong

Status:
Completed

Start date:
May 2020

Completion date:
December 2023

Key contacts:
Scientia Professor Rose Amal: r.amal@unsw.edu.au

Funding:
AUD$540,000 – Australian Research Council (Discovery Project)

Project total cost:
AUD$1.129 million – combined cash and in-kind contributions

Project summary description:
Hydrogen is a desirable energy carrier which will be produced sustainably through solar photocatalysis, contributing to priority area of ‘Energy’ by meeting the challenge ‘New clean energy sources and storage technologies that are efficient, cost-effective and reliable’. The discovery of cost effective and active photocatalysts will promote environmental sustainability; extensive understanding of structure-property-activity mapping will enable process optimisation through efficient pathways leading to sizeable economic impact. Successful implementation of augmented intelligence will reduce decision-making errors facilitating chemical/process industries in waste management and preventing threats to human health and global resources. The adaptation of sophisticated machine learning to innovate solar photocatalysis hydrogen evolution is under question.

The aim of this project is to develop a novel hybrid photocatalyst design and discovery system, combining knowledge on photocatalysis (domain knowledge) with data-driven processing, as a rational and robust platform to accelerate the discovery of solar hydrogen photocatalysis. We aim to harvest scientific principles and integrate with robust protocols to obtain a machine-augmented rational workflow guiding and accelerating discovery of optimal catalysts for solar hydrogen production, solving a major bottleneck.

The project will contribute largely to Australia’s renewable energy sector; fundamental knowledge-based cognitive photocatalysis platform would be conveniently scalable and transferable to mechanistically relevant processes, such as ammonia synthesis and greenhouse gas reduction.

Related publications and key links:

  • Jing L., Zhu R., Ng Y.H., Hu Z., Teoh W.Y., Phillips D.L., Yu J.C. Visible-light photocatalysis and charge carrier dynamics of elemental crystalline red phosphorus. (2020) Journal of Chemical Physics, 153 (2), art. no. 024707. DOI: 10.1063/5.0013142
  • Wang C.-T., Chen J., Xu J., Wei F., Yam C.Y., Wong K.M.-C., Sit P.H.-L., Teoh W.Y. Selective visible light reduction of carbon dioxide over iridium (III)-terpyridine photocatalysts (2021) Materials Today Chemistry, 22, art. no. 100563.DOI: 10.1016/j.mtchem.2021.100563
  • Naveenan S., Teoh W.Y. Chemical fuel cell reactor as the ultimate green reactor (2021) Current Opinion in Chemical Engineering, 34, art. no. 100740. DOI:10.1016/j.coche.2021.100740
  • Vega-Poot A., Rodriguez-Perez M., Becerril-Gonzalez J., Rodriguez-Gutierrez I., Su J., Rodriguez-Gattorno G., Teoh W.Y., Oskam G. Charge Dynamics at Surface-Modified, Nanostructured Hematite Photoelectrodes for Solar Water Splitting (2022) Journal of the Electrochemical Society, 169 (5), art. no. 056519. DOI: 10.1149/1945-7111/ac700b
  • Shi J.-L., Feng K., Hao H., Ku C., Sit P.H.L., Teoh W.Y., Lang X.2D sp2 Carbon-Conjugated Covalent Organic Framework with Pyrene-Tethered TEMPO Intercalation for Photocatalytic Aerobic Oxidation of Sulfides into Sulfoxides (2022) Solar RRL, 6 (1), art. no. 2100608.DOI: 10.1002/solr.202100608
  • Haghshenas Y., Wong W.P., Gunawan D., Khataee A., Keyikoğlu R., Razmjou A., Kumar P.V., Toe C.Y., Masood H., Amal R., Sethu V., Teoh W.Y. Predicting the rates of photocatalytic hydrogen evolution over cocatalyst-deposited TiO2 using machine learning with active photon flux as a unifying feature (2023) EES Catalysis, 2 (2), pp. 612 – 623. DOI: 10.1039/d3ey00246b
  • Masood H., Sirojan T., Toe C.Y., Kumar P.V., Haghshenas Y., Sit P.H.-L., Amal R., Sethu V., Teoh W.Y. Enhancing prediction accuracy of physical band gaps in semiconductor materials (2023). Cell Reports Physical Science, 4 (9), art. no. 101555. DOI: 10.1016/j.xcrp.2023.101555
  • Gunawan D., Lau L.Y., Yuwono J.A., Kumar P.V., Oppong-Antwi L., Kuschnerus I., Chang S.L.Y., Hocking R.K., Amal R., Scott J., Toe C.Y. Revealing the activity and selectivity of atomically dispersed Ni in Zn3In2S6 for benzyl alcohol photoreforming (2024) Chemical Engineering Journal, 486, art. no. 150215. DOI: 10.1016/j.cej.2024.150215

Higher degree studies supported:
One PhD student based at University of New South Wales (Sydney)

 

Reviewed: July 2024