Issue 1, 2023

Effect of Ni atomic fraction on active species of graphene growth on Cu–Ni alloy catalysts: a density functional theory study

Abstract

Cu–Ni alloys are promising catalysts for precisely controlling the number of graphene layers grown by chemical vapor deposition (CVD). However, the theoretical understanding of the effect of the Ni atomic fraction on the active species, which helps determine the mechanism of graphene growth, is still limited. Here, we examine the energetics, electronic properties, and populations of potential carbon source species (CH3, CH2, CH, C) on Cu–Ni alloy catalysts with various Ni atomic fractions under various CVD growth conditions using density functional theory combined with atomistic thermodynamics. An increased Ni atomic fraction of the Cu–Ni alloy catalyst increases the d-band center and d-orbital delocalization of the Ni atoms. Therefore, the stability of the carbon source adsorbed on the surface and subsurface of the catalyst increases. Relative population analysis shows that the CH and C monomers on the surface are the active species that drive surface-mediated growth on Cu–Ni catalysts with low Ni atomic fractions. The dominance of CH and C species can be further tuned by adjusting the growth temperature and partial pressure of H2. In contrast, in a Cu–Ni catalyst with a high Ni atomic fraction, the C monomer species on the subsurface has high stability and acts as an active species that controls the cooling-induced segregation growth mechanism. This study provides an essential insight into the atomistic mechanism of graphene growth in Cu–Ni alloy catalysts.

Graphical abstract: Effect of Ni atomic fraction on active species of graphene growth on Cu–Ni alloy catalysts: a density functional theory study

Supplementary files

Article information

Article type
Paper
Submitted
04 Oct 2022
Accepted
06 Dec 2022
First published
07 Dec 2022

Phys. Chem. Chem. Phys., 2023,25, 708-723

Effect of Ni atomic fraction on active species of graphene growth on Cu–Ni alloy catalysts: a density functional theory study

E. B. Yutomo, F. A. Noor and T. Winata, Phys. Chem. Chem. Phys., 2023, 25, 708 DOI: 10.1039/D2CP04621K

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