Advanced solution methods for microkinetic models of catalytic reactions: A methanol synthesis case study |
| |
| Authors: | Patricia Rubert‐Nason Manos Mavrikakis Christos T Maravelias Lars C Grabow Lorenz T Biegler |
| |
| Affiliation: | 1. Dept. of Chemical and Biological Engineering, University of Wisconsin–Madison, Madison, WI;2. Dept. of Chemical and Biomolecular Engineering, University of Houston, Houston, TX;3. Dept. of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA |
| |
| Abstract: | Microkinetic models, combined with experimentally measured reaction rates and orders, play a key role in elucidating detailed reaction mechanisms in heterogeneous catalysis and have typically been solved as systems of ordinary differential equations. In this work, we demonstrate a new approach to fitting those models to experimental data. For the specific example treated here, by reformulating a typical microkinetic model for a continuous stirred tank reactor to a system of nonlinear equations, we achieved a 1000‐fold increase in solution speed. The reduced computational cost allows a more systematic search of the parameter space, leading to better fits to the available experimental data. We applied this approach to the problem of methanol synthesis by CO/CO2 hydrogenation over a supported‐Cu catalyst, an important catalytic reaction with a large industrial interest and potential for large‐scale CO2 chemical fixation. © 2013 American Institute of Chemical Engineers AIChE J, 60: 1336–1346, 2014 |
| |
| Keywords: | density functional theory nonlinear programming parameter estimation parallel computing |
|
|
