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Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
Published on: April 12, 2019
Parameter Estimation of Microkinetic Models for Heterogeneous Catalysis
M G Toufik Ahmed1, Bimol Nath Roy1, M M Faruque Hasan1,2
1Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, Texas 77843-3122, United States.
Industrial & Engineering Chemistry Research
|August 11, 2026
Summary
This study presents a robust method for estimating microkinetic model (MKM) parameters in heterogeneous catalysis. The approach improves numerical stability and efficiency for complex reaction systems.
Area of Science:
- Chemical Engineering
- Computational Chemistry
- Materials Science
Background:
- Microkinetic models (MKMs) are crucial for understanding surface kinetics and catalyst behavior in complex reactions.
- Estimating MKM parameters is challenging due to nonlinear optimization problems (NLPs) characterized by stiffness, ill-conditioning, and nonconvexity.
Purpose of the Study:
- To develop a robust numerical method for estimating microkinetic model parameters.
- To integrate diverse data sources, including experimental, computational, and DFT data, into the parameter estimation process.
Main Methods:
- Formulation of a nonlinear optimization problem (NLP) incorporating experimental, computational, and DFT data.
- Proposal of a robust NLP solver featuring adaptive feasibility restoration.
- Implementation of a minimum-norm least-squares search direction with projected backtracking line search to handle ill-conditioning and enforce physical bounds.
Main Results:
- The proposed method successfully estimates rate parameters for multitemperature experimental data across various reaction systems.
- Demonstrated improvements in numerical robustness, solution quality, and computational efficiency compared to existing methods.
- The developed algorithm provides a reliable approach for microkinetic parameter estimation in heterogeneous catalysis.
Conclusions:
- The developed robust method enhances the accuracy and efficiency of microkinetic model parameter estimation.
- This approach offers a significant advancement for the study of surface kinetics and catalyst design.
- The associated code is publicly available to facilitate further research and application.
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