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The potential of MXenes for catalyzing dissociation reactions José R. B. Gomesa, José D. Gouveiaa, Á. Morales-Garcíab, Francesc Viñesb, Francesc Illasb a CICECO-Aveiro Institute of Materials, Department of Chemistry, University of Aveiro, Campus de Santiago, 3810-193 Aveiro, Portugal. bDepartment of Materials Science and Physical Chemistry, University of Barcelona, c/Martí i Franquès 1-11, 08028 Barcelona, Spain. E-mail: jrgomes@ua.pt
This communication focuses on the potential of two-dimensional pristine carbide or nitride MXenes (Figure 1) for dissociating water1, nitrogen2 and carbon dioxide3. The data arising from a multiscale modeling approach, coupling calculations carried out in the framework of density functional theory, microkinetic modelling and kinetic phase diagrams, suggest that bare MXenes can be highly active catalytic materials for industrial and societal relevant processes as the water gas shift reaction, ammonia production or carbon capture and usage.
Figure 1. MXene bare surface models analyzed in our computational studies. References [1] Gouveia, J. D.; Morales-García, Á.; Viñes, F.; Illas, F.; Gomes, J. R. B.; Appl. Catal. B.: Environ., 2020, 260, 118191. [2] Gouveia, J. D.; Morales-García, Á.; Viñes, F.; Gomes, J. R. B.; Illas, F.; ACS Catal., 2020, 10, 5049. [3] Morales-Salvador, R.; Gouveia, J. D.; Morales-García, Á.; Viñes, F.; Gomes, J. R. B.; Illas, F.; ACS Catal., 2021, 11, 11248. Acknowledgments: The research carried out at the University of Aveiro was developed within the scope of the project CICECO-Aveiro Institute of Materials, Refs. UIDB/50011/2020 and UIDP/50011/2020, financed by national funds through the Portuguese Foundation for Science and Technology (FCT, MCTES). The research carried out at the University of Barcelona has been supported by the Spanish MINECO/FEDER CTQ2015-64618-R, MICIUN/FEDER RTI2018-095460B-I00 and María de Maeztu MDM-2017-0767 grant and, in part, by Generalitat de Catalunya 2017SGR13 and XRQTC grants. J.D.G. is thankful to project SILVIA, with references PTDC/QUI-QFI/31002/2017 and CENTRO-01-0145-FEDER31002, and also to Project HPC-EUROPA3 (INFRAIA-2016-1-730897), with the support of the EC Research Innovation Action under the H2020 Programme. A.M.-G. thanks the Spanish MICIUN for the Juan de la Cierva postdoctoral grant (IJCI-2017-31979), F. V. is thankful to Ministerio de Economía y Competitividad (MEC) for his Ramón y Cajal (RYC2012-10129) research contract, and F.I. acknowledges additional support from the 2015 ICREA Academia Award for Excellence in University Research. J.R.B.G. and J.D.G. thank FCT for granting access to national computing resources through project Ref. CPCA/A2/6817/2020. All authors are thankful to Red Española de Supercomputación (RES) for the supercomputing time in Marenostrum IV (QS-2019-2-0019), and to COST Action CA18234.
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