Aromatic compounds-mediated synthesis of anatase-free hierarchical TS-1 zeolite:Exploring design strategies via machine learning and enhanced catalytic performance  

作　　者：Chang’an Wang Guoqing An Jing Lin Xiaowei Zhang Zhiyuan Liu Yibin Luo Siqi Liu Zhixiang Cheng Tingting Guo Hongyi Gao Ge Wang Xingtian Shu 

机构地区：[1]Beijing Advanced Innovation Center for Materials Genome Engineering,Beijing Key Laboratory of Function Materials for Molecule and Structure Construction,School of Materials Science and Engineering,University of Science and Technology Beijing,Beijing,P.R.China [2]Institute of Advanced Materials,Beijing Normal University,Beijing,P.R.China [3]Research Institute of Petroleum Processing,SINOPEC,Beijing,P.R.China [4]SINOPEC Changling Branch Company,Yueyang,P.R.China [5]Shunde Graduate School,University of Science and Technology Beijing,Shunde,P.R.China

出　　处：《Aggregate》2023年第4期138-151,共14页聚集体（英文）

基　　金：National Key Research and Development Program of China,Grant/Award Number:2021YFB3500700;SINOPEC Research Institute of Petroleum Processing;Natural Science Foundation of Guangdong Province of China,Grant/Award Number:2022A1515011918;Scientific and Technological Innovation Foundation of Shunde Graduate School;University of Science and Technology Beijing,Grant/Award Number:BK20AE003;Fundamental Research Funds for the Central Universities,Grant/Award Number:FRF-IDRY-20-004。

摘　　要：Simultaneous achievement of constructing mesopores and eliminating anatase is a long-term pursuit for enhancing the catalytic performance of TS-1.Here,we developed an aromatic compounds-mediated synthesis method to prepare anatase-free and hierarchical TS-1 for olefin epoxidation.A series of hierarchical TS-1 zeolites were prepared by introducing aromatic compounds containing different functional groups via the crystallization process.The formation of intercrystalline mesopores and insertion of titanium into framework were facilitated at different extent.The synergistic coordination of carboxyl and hydroxyl in aromatic compounds with Ti(OH)4 realizes the uniform distribution of titanium species and eliminates the generation of anatase.Noteworthily,eight machine learning models were trained to reveal the mechanism of additive functional groups and preparation conditions on anatase formation and microstructure optimization.The prediction accuracy of most models can reach more than 80%.Benefiting from the larger mesopore volumes(0.37 cm3⋅g−1)and higher content of framework Ti species,TS-DHBDC-48h samples exhibit a higher catalytic performance than other zeolites,giving 1-hexene conversion of 49.3%and 1,2-epoxyhenane selectivity of 99.9%.The paper provides a facile aromatic compounds-mediated synthesis strategy and promotes the application of machine learning toward the design and optimization of new zeolites.

关 键 词：1-hexene epoxidation aromatic compounds machine learning SELECTIVITY TS-1 zeolites 

分 类 号：TQ426[化学工程]