Abstract
Structured microchannel H-ZSM-5 catalysts containing up to 80 wt% zeolite (balance bentonite) were fabricated by unit operations of paste preparation, extrusion, drying and firing. The structured catalysts, called miniliths due to their micrometre-range dimensions, were composed of parallel cylindrical channels with a wall thickness of 200 – 300 μm, density of 2.1 channels/mm2 and a channel diameter of 300 μm. These miniliths were characterised by X-ray diffraction, scanning electron microscopy, energy dispersive X-ray analysis, N2 physisorption and thermogravimetric analysis. For the first time, these miniliths were tested for the conversion of methanol to gasoline at 370 °C, 3 bar and a weight hourly space velocity (WHSV) of up to 1170 h-1. A gasoline product yield of 53% was obtained at a methanol conversion of 74% over the ZSM-5 miniliths. The pressure drop at the same conversion over a packed-bed reactor of equal ZSM-5 content was 2 orders of magnitude higher than that of the minilith. Reducing the amount of ZSM-5 catalyst in the packed bed, to obtain similar inlet pressure as the ZSM-5 minilith gave the same product yield at a much higher conversion (81%) demonstrating the potential of these structured microchannel reactors.
Original language | English |
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Article number | 131 |
Pages (from-to) | 137-143 |
Number of pages | 7 |
Journal | Chemical Engineering & Processing: Process Intensification |
Volume | 131 |
Early online date | 26 Jul 2018 |
DOIs | |
Publication status | Published - Sept 2018 |
Keywords
- Gasoline
- Methanol
- Methanol-to-gasoline
- Methanol-to-olefin
- Micromonolith
- Minilith
- Structured reactor
- ZSM-5
ASJC Scopus subject areas
- General Chemistry
- General Chemical Engineering
- Energy Engineering and Power Technology
- Industrial and Manufacturing Engineering
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Dataset for "Zeolite Minilith: A Unique Structured Catalyst for the Methanol to Gasoline Process"
Omojola, T. (Creator), Cherkasov, N. (Creator), Rebrov, E. (Creator), Lukyanov, D. (Creator) & Perera, S. (Creator), University of Bath, 27 Jul 2018
DOI: 10.15125/BATH-00524
Dataset