Biofuel Research Journal (Sep 2024)

Advanced computational modelling for biofuel catalyst optimization: enhancing beta zeolite acidity for oleic acid upgrading

  • Seba AlAreeqi,
  • Daniel Bahamon,
  • Ismail Alkhatib,
  • Kyriaki Polychronopoulou,
  • Lourdes F. Vega

DOI
https://doi.org/10.18331/BRJ2024.11.3.5
Journal volume & issue
Vol. 11, no. 3
pp. 2194 – 2210

Abstract

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We explore here, through reactive force field (ReaxFF) molecular dynamics simulations, oleic acid upgrading on beta zeolite (BEA) regulated with nine silica-to-aluminium ratios (SARs) to investigate their acid-catalyzed deoxygenation and coking susceptibility. The selected computational descriptors involved conversion, hydrodeoxygenation, and decarboxylation/decarbonylation selectivity, biofuels yield, and coke deposition characteristics. Simulations were validated by 20.3 SAR available experimental data and used for the systematic study. High deoxygenation selectivity was found to be related to the structural sensitivity of BEA(100) on the upgrading mechanism. ReaxFF simulations revealed that altering the Al-substitution could greatly promote biofuel formation. Specifically, SARs towards the mid-region (SAR 47) favored gasoline production, while 31 SAR exploited diesel-like hydrocarbons. An optimum ratio of 37.4 SAR achieved maximum oleic acid conversion (69.8%), with high yields of gasoline and diesel fuels (15.6 and 20.4 wt%, respectively) and moderate coking (8.6 wt%). Density functional theory screening of metallic dopants allowed investigating of their deoxygenation and coke susceptibility, obtaining that Cu-BEA structure favored the optimal carbon and O moiety adsorption (-3.89 and -1.8 eV, respectively). Furthermore, the economic and environmental analysis showed that Cu-dopped BEA displayed the lowest market price and global warming potential (71 USD/kg and 2.8 kg CO2-eq/kg).

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