Hostname: page-component-586b7cd67f-l7hp2 Total loading time: 0 Render date: 2024-11-30T07:29:45.990Z Has data issue: false hasContentIssue false
  • English
  • Français

Stable Pt clusters anchored to monovacancies on graphene sheets

Published online by Cambridge University Press:  09 October 2017

Bharat K. Medasani Open the ORCID record for Bharat K. Medasani [Opens in a new window] ,
Jun Liu  and
Maria L. Sushko
Bharat K. Medasani
Affiliation:
Physical and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland WA 99354, USA
Jun Liu
Affiliation:
Energy and Environment Directorate, Pacific Northwest National Laboratory, Richland WA 99354, USA
Maria L. Sushko*
Affiliation:
Physical and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland WA 99354, USA
*
Address all correspondence to Maria L. Sushko at [email protected]
Get access

Abstract

First principles simulations and global optimization predict new mode of binding of Pt clusters with defects on graphene that significantly enhances their stability. Pt clusters were found to firmly bind to monovacancies in configuration transacting the vacancy site, while retaining the integrity of the cluster. Diffusion calculations support tight anchoring of Pt cluster to monovacancy. Pt cluster adsorbed on pristine graphene or other common defects exhibit a different mode of adsorption and only decorate one side of graphene. This study reveals strong influence of defect chemistry on the structure and mobility of Pt nanoclusters adsorbed on graphene and have important implications for catalytic and gas sensing applications.

Type
Research Letters
Information
MRS Communications , Volume 7 , Issue 4 , December 2017 , pp. 891 - 895
Check for updates
Copyright
Copyright © Materials Research Society 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Georgakilas, V., Otyepka, M., Bourlinos, A.B., Chandra, V., Kim, N., Kemp, K.C., Hobza, P., Zboril, R., and Kim, K.S.: Functionalization of graphene: covalent and non-covalent approaches, derivatives and applications. Chem. Rev. 112, 6156 (2012).Google Scholar
2. Green, A., Isseroff, R., Lin, S., Wang, L., and Rafailovich, M.: Synthesis and characterization of iron nanoparticles on partially reduced graphene oxide as a cost-effective catalyst for polymer electrolyte membrane fuel cells. MRS Commun. 7, 166 (2017).Google Scholar
3. Cho, B., Yoon, J., Hahm, M.G., Kim, D.-H., Kim, A.R., Kahng, Y.H., Park, S.-W., Lee, Y.-J., Park, S.-G., Kwon, J.-D., Kim, C.S., Song, M., Jeong, Y., Nam, K.-S., and Ko, H.C.: Graphene-based gas sensor: metal decoration effect and application to a flexible device. J. Mater. Chem. C 2, 5280 (2014).Google Scholar
4. Ding, M., Sorescu, D.C., Kotchey, G.P., and Star, A.: Welding of gold nanoparticles on graphitic templates for chemical sensing. J. Am. Chem. Soc. 134, 3472 (2012).Google Scholar
5. Ding, M., Tang, Y., and Star, A.: Understanding interfaces in metal–graphitic hybrid nanostructures. J. Phys. Chem. Lett. 4, 147 (2013).Google Scholar
6. Wu, S.-Y. and Ho, J.-J.: Adsorption of a Pt13 cluster on graphene oxides at varied ratios of oxygen to carbon and its catalytic reactions for CO removal investigated with quantum-chemical calculations. J. Phys. Chem. C 118, 26764 (2014).Google Scholar
7. Fampiou, I. and Ramasubramaniam, A.: Binding of Pt Nanoclusters to point defects in graphene: adsorption, morphology, and electronic structure. J. Phys. Chem. C 116, 6543 (2012).Google Scholar
8. Padmanabhan, H. and Nanda, B.R.K.: Intertwined lattice deformation and magnetism in monovacancy graphene. Phys. Rev. B 93, 165403 (2016).Google Scholar
9. Zhang, C., Dabbs, D.M., Liu, L.M., Aksay, I.A., Car, R., and Selloni, A.: Combined effects of functional groups, lattice defects, and edges in the infrared spectra of graphene oxide. J. Phys. Chem. C 119, 18167 (2015).Google Scholar
10. Robertson, A.W., Lee, G.-D., He, K., Yoon, E., Kirkland, A.I., and Warner, J.H.: Stability and dynamics of the tetravacancy in graphene. Nano Lett. 14, 1634 (2014).Google Scholar
11. Kaloni, T.P., Singh, N., and Schwingenschlögl, U.: Prediction of a quantum anomalous Hall state in Co-decorated silicene. Phys. Rev. B 89, 035409 (2014).Google Scholar
12. Padilha, J.E. and Pontes, R.B.: Electronic and transport properties of structural defects in monolayer germanene: an ab initio investigation. Solid State Commun. 225, 38 (2016).Google Scholar
13. Singh, N., Kaloni, T.P., and Schwingenschlögl, U.: A first-principles investigation of the optical spectra of oxidized graphene. Appl. Phys. Lett. 102, 023101 (2013).Google Scholar
14. Piotrowski, M.J., Piquini, P., and Da Silva, J.L.F.: Density functional theory investigation of 3d, 4d, and 5d 13-atom metal clusters. Phys. Rev. B 81, 155446 (2010).Google Scholar
15. Wales, D.J. and Doye, J.P.K.: Global optimization by basin-hopping and the lowest energy structures of lennard-jones clusters containing up to 110 atoms. J. Phys. Chem. A 101, 5111 (1997).Google Scholar
16. Fernando, A., Weerawardene, K.L.D.M., Karimova, N.V., and Aikens, C.M.: Quantum mechanical studies of large metal, metal oxide, and metal chalcogenide nanoparticles and clusters. Chem. Rev. 115, 6112 (2015).Google Scholar
17. Medasani, B., Park, Y.H., and Vasiliev, I.: Theoretical study of the surface energy, stress, and lattice contraction of silver nanoparticles. Phys. Rev. B 75, 235436 (2007).Google Scholar
18. Medasani, B. and Vasiliev, I.: Computational study of the surface properties of aluminum nanoparticles. Surf. Sci. 603, 2042 (2009).Google Scholar
19. Henkelman, G., Uberuaga, B.P., and Jónsson, H.: A climbing image nudged elastic band method for finding saddle points and minimum energy paths. J. Chem. Phys. 113, 9901 (2000).Google Scholar
20. Koh, Y.W. and Manzhos, S.: Curvature drastically changes diffusion properties of Li and Na on graphene. MRS Commun. 3, 171 (2013).Google Scholar
21. Kresse, G. and Hafner, J.: Ab initio molecular dynamics for liquid metals. Phys. Rev. B 47, 558 (1993).Google Scholar
22. Hutter, J., Iannuzzi, M., Schiffmann, F., and VandeVondele, J.: CP2K: atomistic simulations of condensed matter systems. Wiley Interdiscip. Rev. Comput. Mol. Sci. 4, 15 (2014).Google Scholar
23. Bahn, S.R. and Jacobsen, K.W.: An object-oriented scripting interface to a legacy electronic structure code. Comput. Sci. Eng. 4, 56 (2002).Google Scholar
24. Terrel, R., Chill, S., Xiao, P., Duncan, J., Stauffer, S., Bandy, R., and Henkelman, G.: TSASE: Transition State Library for ASE. Retreived Sept 18, 2017 from http://theory.cm.utexas.edu/tsase/.Google Scholar
25. Momma, K. and Izumi, F.: VESTA 3 for three-dimensional visualization of crystal, volumetric and morphology data. J. Appl. Crystallogr. 44, 1272 (2011).Google Scholar
Supplementary material: PDF

Medasani et al supplementary material

Medasani et al supplementary material 1

Download Medasani et al supplementary material(PDF)
PDF 430.5 KB