Graduate student Xiaohong Zhang’s research (along with her advisor Dr. Rachel Getman and collaborator Dr. Aditya Savara from the Oak Ridge National Laboratory) recently made the cover of the Journal of Chemical Theory and Computation. Their journal publication titled “A Method for Obtaining Liquid-Solid Adsorption Rates from Molecular Dynamics Simulations: Applied to Methanol on Pt(111) in H2O”, explains the new methods they developed to measure adsorption rates.
Industrial-scale chemical reactions routinely employ heterogeneous catalysts to more efficiently produce the desired chemical product(s). In these processes, the reactants adsorb on the catalyst surface and are converted to the desired products, which are later collected and purified. Thus, adsorption is an important step in heterogeneous catalysis as it predetermines how many reactant molecules can participate in a surface reaction, which directly impacts catalyst performance. While adsorption processes are well studied in both theory and experiment for systems with gaseous reactants (gas-solid adsorption), such processes are much less understood for systems having liquid phase reactants (liquid-solid adsorption). This is partly because of the difficulty in studying the ever-changing environment of the liquid reaction medium.
In this project, Zhang and her fellow researchers developed a method that combines molecular dynamics (MD) simulations and mathematical modeling to calculate adsorption rates for species binding to a solid catalyst surface from liquid solvent. These MD simulations explicitly model the liquid environment, enabling the trajectories of the reactant molecules to be followed as they adsorb on the catalyst surface. The mathematical modeling analyzes the essential behavior of the adsorbing process and provides quantitative studies of the adsorption rate. This combined model supplants the prior state-of-the-art, which was derived from ideal gas collision theory.
As the new methods developed by Zhang et al. take into account intermolecular forces from the liquid reaction medium, they are up to 4 orders of magnitude more accurate than the prior state-of-the-art models, providing an example of the importance of atomistic simulations in understanding adsorption and catalysis.
Overall, their approach turned out to be more accurate than the prior methods and can be expanded to arbitrary catalyst surfaces and liquid solvents, providing a useful tool for evaluating and screening catalysts.
The authors also provide methods for accurately estimating rates of adsorption in cases where access to molecular dynamics simulations is unavailable, expanding the impact of the manuscript.