Improving the propylene selectivity in the methanol-to-olefins reaction over CIT-17, a SAT-type molecular sieve

CHEMICAL ENGINEERING JOURNAL(2024)

Cited 0|Views5
No score
Abstract
Small-pore, cage-containing molecular sieves exhibit high selectivities toward light olefins in the methanol-toolefins (MTO) reaction. However, the ability to alter the olefins product selectivities while achieving high carbon efficiency remains a challenge for this complex reaction network. Here, the synthesis, characterization, and catalytic testing of several SAT-type molecular sieves: SAPO (CIT-17), MgAPO (STA-2), and CoAPO (STA-2) are reported. Several CHA- (e.g., SAPO-34, MgAPO-34, and CoAPO-34) and AEI-type (e.g., SAPO-18, MgAPO-18, and CoAPO-18) molecular sieves are synthesized and tested for comparisons. The SAT materials exhibit high propylene selectivities ranging from approximately 35 % to 50 % in the MTO reaction. Remarkably high propyleneto-ethylene ratios (P/E) ranging from 1.64 to 4.17 are achieved, depending on the reaction conditions and molecular sieve properties. These P/E ratios are higher than those obtained from CHA- (P/E = 0.91-1.31) and AEI-type (P/E = 2.10-2.34) materials at complete or near-complete methanol conversion. The enhanced P/E ratios exhibited by the SAT-type catalysts with low silicon contents (e.g., CIT-17 (Si/T-atom = 0.083)) are ascribed to the time-on-stream delay in the maturation of aromatic species that are comprised primarily of triand tetra-methylbenzenes. The results from this study demonstrate the subtle cooperativity between the narrow SAT cage (cage-defining ring (CDR) size of 6.6 angstrom) and low acidity of CIT-17. These factors together create a conducive microenvironment that facilitates the conversion of methanol-to-propylene by promoting the olefins cycle, particularly in early stages of the reaction, and reducing the contribution of the aromatics cycle.
More
Translated text
Key words
CIT-17,Methanol -to -olefins,Silicoaluminophosphates,SAT,Selectivity,Propylene
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined