Hyppää sisältöön
    • Suomeksi
    • In English
  • Suomeksi
  • In English
  • Kirjaudu
Näytä aineisto 
  •   Etusivu
  • 3. UTUCris-artikkelit
  • Rinnakkaistallenteet
  • Näytä aineisto
  •   Etusivu
  • 3. UTUCris-artikkelit
  • Rinnakkaistallenteet
  • Näytä aineisto
JavaScript is disabled for your browser. Some features of this site may not work without it.

Trickle bed reactor technology for propylene epoxidation with extrudates – Catalyst characterization, kinetic studies and modelling

Staglich, Christopher; Alvear, Matias; Schmidt, Christoph; Angervo, Ilari; Russo, Vincenzo; Haase, Stefan; Salmi, Tapio

Trickle bed reactor technology for propylene epoxidation with extrudates – Catalyst characterization, kinetic studies and modelling

Staglich, Christopher
Alvear, Matias
Schmidt, Christoph
Angervo, Ilari
Russo, Vincenzo
Haase, Stefan
Salmi, Tapio
Katso/Avaa
1-s2.0-S0009250925003938-main.pdf (15.68Mb)
Lataukset: 

Elsevier BV
doi:10.1016/j.ces.2025.121570
URI
https://doi.org/10.1016/j.ces.2025.121570
Näytä kaikki kuvailutiedot
Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe2025082789454
Tiivistelmä
Titanium silicate (TS-1) extrudates were prepared, characterized and tested in a trickle bed reactor (TBR) for selective epoxidation of propylene to propylene oxide. Hydrogen peroxide was used as the epoxidation agent. A preliminary study was conducted with extrudates with a diameters 1.5-3 mm. The smallest extrudate showed the highest propylene conversion and was used for an extensive screening of the reaction conditions (temperature, pressure, liquid and gas flow rates, composition of the educt solution). A dynamic multiphase reactor model was developed based on the steady state reaction kinetics approach. The internal mass transfer effects inside the extrudates were described with a reaction-diffusion model and the backmixing effects inside the catalyst bed were modelled with the axial dispersion concept. The mass balances of the components in the gas, liquid and solid catalyst phases were solved numerically with gProms ModelBuilder. The prediction of the model was for the most experimental data within +/- 10 %. The model was used to the simulate the concentration profiles of the participating molecules in time and space.
Kokoelmat
  • Rinnakkaistallenteet [27094]

Turun yliopiston kirjasto | Turun yliopisto
julkaisut@utu.fi | Tietosuoja | Saavutettavuusseloste
 

 

Tämä kokoelma

JulkaisuajatTekijätNimekkeetAsiasanatTiedekuntaLaitosOppiaineYhteisöt ja kokoelmat

Omat tiedot

Kirjaudu sisäänRekisteröidy

Turun yliopiston kirjasto | Turun yliopisto
julkaisut@utu.fi | Tietosuoja | Saavutettavuusseloste