Abstract
This manuscript discusses developing a model-based scale-up methodology for a successful technology transfer of gas-phase catalytic reactors from a lab-scale to a pilot-scale operation. The manuscript demonstrates the methodology for gas-phase dehydration of tetrahydrofurfuryl alcohol (THFA) to dihydropyran (DHP) process over commercial Al2O3 catalysts. A two-dimensional reactor model was developed using COMSOL Multiphysics 6.1 software. The model solves heat and mass transport equations in bed-scale and particle scales simultaneously. This powerful feature enables accurate prediction of the heat and mass transfer limitations in pilot-scale reactors, if any exists. The model uses isothermal lab-scale experimental data to derive and validate the reaction chemistry, flow fields and boundary conditions. The model was then scaled-up to project conversion, selectivity, yield and formation rate of DHP in a pilot-scale reactor. The results highlight the complex nature of chemistry, heat, and mass transfer effects in lab-scale and pilot-scale reactors. The model results inform the possible operational limitations of the pilot-scale reactor and design strategies to improve process efficiency. Although the scale-up approach is explained through the THFA dehydration process, the methodology is applicable to any catalytic packed-bed reactor models for a successful process scale-up.
| Original language | English |
|---|---|
| Pages (from-to) | 12961-12976 |
| Number of pages | 16 |
| Journal | Industrial and Engineering Chemistry Research |
| Volume | 63 |
| Issue number | 29 |
| DOIs | |
| State | Published - Jul 24 2024 |
Funding
This study is a part of recent collaborative efforts between Oak Ridge National Laboratory (ORNL) and Pyran Inc. (Pyran) to utilize modeling capabilities developed by the CCPC (Consortium for Computational Physics and Chemistry) to assist in scaling-up Pyran’s proprietary process for thermocatalytic conversion of furfural to 1,5-pentanediol (1,5-PDO). This manuscript has been authorized by UT-Battelle, LLC, under contract CRADA No. NFE-20-08393 with the US Department of Energy (DOE) in collaboration with the Consortium for Computational Physics and Chemistry (CCPC) and the Chemical Catalysis for Bioenergy Consortium (ChemCatBio) of Energy Office of Energy Efficiency and Renewable Energy’s Bioenergy Technologies Office (BETO). Funding was provided by the U.S. Department. We would acknowledge Pyran, Inc., for their support of this work and use of their experimental laboratory. This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan ( http://energy.gov/downloads/doe-public-access-plan ). Acknowledgments