Zeolite Catalysts for Selective Hydrocracking of Polycyclic Aromatic Hydrocarbons – Structures and Mechanisms.
Published In: ChemCatChem, 2024, v. 16, n. 21. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Dong, Qi; Li, Ruifeng; Jiao, Haijun 3 of 3
Abstract
Selective hydrocracking of polycyclic aromatic hydrocarbons (PAHs) from heavy oils and tar to high‐value chemicals such as benzene, toluene, and xylene (BTX) is a promising technology. Due to the lack of comprehensive and rational understanding of the reaction mechanisms, the development and preparation of catalysts and the improvement of catalysis technology are rarely carried out. Since zeolites as crucial solid acid catalyst components in catalytic hydrocracking of PAHs are indispensable, this review systematically analyzed the mechanisms and research advances in hydrogenation, isomerization, and ring‐opening (cracking) on zeolite catalysts. Efficient zeolite catalysts for hydrocracking should have appropriate pore structures for the required diffusivity for reactants and products to avoid secondary polymerization and coke formation, an ideal distribution and strength of acid sites for the formation of the desired carbocation intermediates to achieve the selectivity of products and precisely tunable metal to acid functions to control the competition between (de)hydrogenation and ring‐opening reactions leading to the facilitation of the reaction mechanisms for the desired products. This poses challenges for the research and development of industrial relevant zeolite catalysts. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:ChemCatChem. 2024/11, Vol. 16, Issue 21, p1
- Document Type:Article
- Subject Area:Chemistry
- Publication Date:2024
- ISSN:1867-3880
- DOI:10.1002/cctc.202400117
- Accession Number:180827061
- Copyright Statement:Copyright of ChemCatChem is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.