Employing an Artificial Neural Network in Correlating a Hydrogen-Selective Catalytic Reduction Performance with Crystallite Sizes of a Biomass-Derived Bimetallic Catalyst

• Main Authors: Ibrahim, Yakub, Ahmad Kueh, Beng Hong, Md. Rezaur, Rahman, Mohamad Hardyman, Barawi, Mohammad Omar, Abdullah
• Format: Article
• Language: English
• Published: MDPI 2022
• Subjects: Q Science (General)
• Online Access: http://ir.unimas.my/id/eprint/38977/3/Employing%20an%20-%20Copy.pdf; http://ir.unimas.my/id/eprint/38977/; https://www.mdpi.com/2073-4344/12/7/779; https://doi.org/10.3390/catal12070779
• Institution: Universiti Malaysia Sarawak

A predictive model correlating the properties of a catalyst with its performance would be beneficial for the development, from biomass waste, of new, carbon-supported and Earth-abundant metal oxide catalysts. In this work, the effects of copper and iron oxide crystallite size on the performance of...