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Screening microkinetic modeling

Motivated by the idea of rational catalyst design, we take advantage of the computational efficiency of DFT methods to examine a variety of Ag-containing bimetallic catalysts. We focus initially on the branching reactions of the OME since these have been shown to control selectivity [9]. Initial screening based solely on OME reactions suggests several promising bimetallic combinations. However, if one considers a more complete microkinetic model, copper stands out for its ability to enhance the selectivity of silver-based bimetallic catalysts. [Pg.266]

Recently, semiempirical methods based on DFT calculations have been developed for catalyst screening. These methods include linear scaling relationships [41, 42] to transfer thermochemistry from one metal to another and Brpnsted-Evans-Polanyi (BEP) relationships [43 7]. Here, these methods and also methods for estimation of the surface entropy and heat capacity are briefly discussed. Because of their screening capabilities, semiempirical methods can be used to produce a first-pass microkinetic model. This first-pass model can then be refined using more detailed theory aided by analytical tools that identify key features of the model. The empirical bond-order conservation (BOC) method, which has shown good success in developing microkinetic models of small molecules, has recently been reviewed [11] and will not be covered here. [Pg.178]

In the first chapter, Lars Grabow (University of Houston) discusses the screening of catalysts through the use of first-principles methods. Using density functional theory (DFT), key descriptors and scaling relationships can be identified and incorporated with an appropriate microkinetic model. Such an approach allows for the rapid screening of materials based on DFT calculations. [Pg.5]

The microkinetic modeling procedure for catalyst screening will be illustrated for the CO oxidation example, which is the prototype reaction in heterogeneous catalysis. The same four-step mechanism used in the Sabatier example will be used here and the net rates of the elementary steps are given by ... [Pg.37]

With eqns (1.52) and (1.53) there are four equations for the four unknown coverages 0q2> o, dco, and 0 and the system of nonlinear algebraic equations may be solved numerically. With currently available CPU speeds numerical solutions to microkinetic models for catalyst screening studies are generally preferred because they avoid the need to make any additional assumptions regarding the mechanism. [Pg.38]


See other pages where Screening microkinetic modeling is mentioned: [Pg.178]    [Pg.14]    [Pg.28]    [Pg.37]    [Pg.39]    [Pg.55]    [Pg.56]    [Pg.5]    [Pg.236]   
See also in sourсe #XX -- [ Pg.27 , Pg.28 ]




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Microkinetic model

Microkinetic modeling

Screening microkinetic model

Screening microkinetic model

Screening microkinetics

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