Processes for fabricating carbon-based supports in Ru-based catalysts in ammonia decomposition: A state-of-art review

ABSTRACT In the ammonia decomposition reaction for hydrogen production, ruthenium is commonly used as a catalyst because of its excellent catalytic performance. Recent research has focused on the reaction mechanism of ruthenium-based catalysts, their microstructure and support, as well as the modulation of catalyst performance by various dopant elements, aiming to reduce ruthenium loading and enhance its catalytic efficiency for low temperature applications. This review summarizes the fundamental mechanisms of ruthenium-catalyzed ammonia decomposition and recent advances in catalyst preparation methods, with particular emphasis on the influence of carbon-based catalyst supports on ammonia decomposition activity. The impregnation method can enhance the dispersion of ruthenium on the support, thereby increasing the number of effective active sites. The precipitation deposition method controls the metal-support interactions during precipitation formation, contributing to the stability of the metal and the generation of active sites, thus improving the efficiency of ammonia decomposition reactions. The sol-gel method can produce catalysts support with surface features that can alter the electronic density of ruthenium, optimizing its interactions with ammonia molecules, thereby enhancing its catalytic activity. The high specific surface area and the optimized pore structure of the carbon-based support facilitates the adsorption or dispersion of Ru particles, thereby increasing the electronic density of Ru. A higher electronic density could enhance the attraction between the electrons on the Ru surface and ammonia molecules, thereby promoting the adsorption and dissociation of ammonia molecules. At the same time, a higher electronic density may lower the binding energy of the nitrogen-nitrogen bond, facilitating its cleavage and accelerating the ammonia decomposition process. In discussing emerging directions for development in ruthenium-based ammonia decomposition catalysts, we also introduced the emerging research trends in ammonia decomposition catalysts, including: (1) component prediction and optimization using high-throughput screening strategies, and (2) combined machine learning and computational simulations for kinetic process analysis.