Predicting the rates of photocatalytic hydrogen evolution over cocatalyst-deposited TiO<sub>2</sub> using machine learning with active photon flux as a unifying feature-Reference-Cited by-同舟云学术

Predicting the rates of photocatalytic hydrogen evolution over cocatalyst-deposited TiO₂ using machine learning with active photon flux as a unifying feature

Published:2024 Issue: Volume: Page:
ISSN:2753-801X
Container-title:EES Catalysis
language:en
Short-container-title:EES. Catal.

Author:

Haghshenas Yousof¹,Wong Wei Ping²^ORCID,Gunawan Denny¹^ORCID,Khataee Alireza³,Keyikoğlu Ramazan³,Razmjou Amir⁴,Kumar Priyank Vijaya¹^ORCID,Toe Cui Ying¹⁵^ORCID,Masood Hassan¹,Amal Rose¹^ORCID,Sethu Vidhyasaharan⁶,Teoh Wey Yang¹²^ORCID

Affiliation:

1. School of Chemical Engineering, The University of New South Wales, NSW 2052, Australia

2. Department of Chemical Engineering, Sustainable Process Engineering Centre (SPEC), Universiti Malaya, 50603 Kuala Lumpur, Malaysia

3. Department of Environmental Engineering, Gebze Technical University, 41400 Gebze, Turkey

4. Mineral Recovery Research Center (MRRC), School of Engineering, Edith Cowan University, Joondalup, Perth, WA, 6027, Australia

5. School of Engineering, The University of Newcastle, Callaghan, New South Wales 2038, Australia

6. School of Electrical Engineering and Telecommunications, The University of New South Wales, NSW 2052, Australia

Abstract

An accurate model for predicting TiO2 photocatalytic hydrogen evolution reaction (HER) rates is hereby presented.

Funder

Australian Research Council

Universiti Malaya

Ministry of Higher Education, Malaysia

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/EY/D3EY00246B

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