9 research outputs found

    The influence of functionals on density functional theory calculations of the properties of reducible transition metal oxide catalysts

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    Reducible transition metal oxides (RTMOs) comprise an important class of catalytic materials that are used for the selective oxidation and electro- and photochemical splitting of water, and as supports for metal nanoparticles. It is, therefore, highly desirable to model the properties of these materials accurately using density functional theory (DFT) in order to understand how oxide structure and performance are related and to guide the search for materials exhibiting superior performance. Unfortunately, accurate description of the structural and electronic properties of RTMOs using DFT has proven particularly challenging. The M06-L density functional, which has been shown to be broadly accurate for calculations of gas phase clusters, has recently become available to researchers carrying out calculations in the solid state, but its performance in determining the properties RTMOs has been little investigated. The aim of this work was to assess the performance of the M06-L functional for describing the structural and electronic properties of a family of RTMOs: MoO , MoO , and Bi Mo O . Lattice constants, band gaps, and densities of states calculated using the M06-L functional are compared to those obtained from DFT+U. We have also used the M06-L functional to determine the reaction barrier for propene activation over Bi Mo O , the rate-limiting step in the oxidation of propene to acrolein. We find that while DFT calculations carried out with the M06-L functional are roughly five times more expensive computationally than those performed with DFT+U, the results obtained using the M06-L functional provide sensible results for all properties investigated, while avoiding the necessary trade-off between accurate electronic structure and accurate thermochemistry that occurs in DFT+U. © 2013 American Chemical Society. 2 3 2 3 12 2 3 1

    Theory-guided design of catalytic materials using scaling relationships and reactivity descriptors

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