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Predicting the Effect of Dopants on CO2Adsorption in Transition Metal Carbides: Case Study on TiC (001)

  • Martí López
  • , Francesc Viñes
  • , Michael Nolan
  • , Francesc Illas

    Research output: Contribution to journal › Article › peer-review

    245 Downloads (Pure)

    Abstract

    A previous work has shown that doping the TiC (001) surface with early transition metals significantly affects CO2 adsorption and activation, which opens up a possible way to control this interesting chemistry. In this work, we explore other possibilities, which include nontransition metal elements (Mg, Ca, Sr., Al, Ga, In, Si, and Sn) as well as late transition metals (Pd, Pt, Rh, and Ir) and lanthanides (La and Ce), often used in catalysis. Using periodic slab models with large supercells and state-of-the-art density functional theory (DFT) based calculations, we show that, in all the studied cases, CO2 appears as bent and, hence, activated. However, the effect is especially pronounced for dopants with large ionic crystal radii. This can increase desorption temperature by up to 230 K, almost twice the value predicted when early transition metals are used as dopants. However, a detailed analysis of the results shows that the main effect does not come from the electronic structure perturbations but from the distortion that the dopant generates into the surface atomic structure. A simple descriptor is proposed that would allow predicting the effect of the dopant on CO2 adsorption energy in transition metal carbide surfaces without the need for DFT calculations.

    Original languageEnglish
    Pages (from-to)15969-15976
    Number of pages8
    JournalJournal Of Physical Chemistry C
    Volume124
    Issue number29
    Early online date26 Jun 2020
    DOIs
    Publication statusPublished (in print/issue) - 23 Jul 2020

    Funding

    The research carried out at the Universitat de Barcelona has been supported by the Spanish MICIUN/FEDER RTI2018-095460-B-I00 and Marı́a de Maeztu MDM-2017-0767 grants and, in part, by Generalitat de Catalunya 2017SGR13 grant and by the COST Action 18234, supported by the COST (European Cooperation in Science and Technology). M.N. acknowledges support from the Science Foundation Ireland and the Horizon 2020 M-ERA.net 2 cofund program, through grant agreements No 685451 and 16/M-ERA/3418. M.L acknowledges the HPC-EUROPA3 (INFRAIA-2016-1-730897) project supported by the EC Research Innovation Action under the H2020 Programme, the Tyndall National Institute and the Irish Centre for High-End Computing (ICHEC) for supporting his stay in Cork. F.V. thanks the Spanish MINECO for postdoctoral contracts under the Ramón y Cajal Program (RYC-2012-10129) and F.I. acknowledges additional support from the 2015 ICREA Academia Award for Excellence in University Research.

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