(6b) Analysis and Prediction of Reaction Kinetics Using the Degree of Rate Control | AIChE

(6b) Analysis and Prediction of Reaction Kinetics Using the Degree of Rate Control

Authors 

Campbell, C. - Presenter, University of Washington
“Degree of Rate Control” (DRC) analysis provides a quantitative approach for analyzing the kinetics of multi-step reaction mechanisms that has been widely applied to both heterogeneous and homogeneous catalysis research, as well as electrocatalysis. The DRC of any given transition state or intermediate is defined as a partial derivative such that it approximately equals the fractional increase in net rate to the product of interest per differential decrease in its standard-state free energy for that species (÷RT), holding constant the standard-state free energies of all other transition states and intermediates. Even very complex mechanisms usually have only a few species with non-zero DRCs and are thus the species whose interactions with the catalyst most strongly affect the net rate. These key DRC values thus offer a simple and intuitive route to optimize catalyst materials, especially with the assistance of computational methods like density functional theory (DFT). The apparent activation energy equals a weighted average of the standard-state enthalpies (relative to reactants) of all the species (intermediates, transition states and products) in the reaction mechanism, each weighted by its DRC (plus RT). (This also holds in electrocatalysis at fixed potential, where the transfer coefficient and Tafel slope are also directly related to DRC values.) The reaction orders with respect to fluid-phase concentrations of reactants, products and intermediates have also been proven to be directly related to DRCs. Thus, there are numerous experimental observables which equate to short linear combinations of DRCs, so that combinations of experimental measurements can also provide DRC values. These relationships provide new opportunities for using experiments earlier in the development and optimization of microkinetic models, minimizing the needed input from computational catalysis.