Solving the Puzzle of the Coexistence of Different Adsorption

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C: Surfaces, Interfaces, Porous Materials, and Catalysis

Solving the Puzzle of the Coexistence of Different Adsorption Geometries of Graphene on Ni(111) Sabine Charlotte Matysik, Christian Papp, and Andreas Goerling J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.8b09438 • Publication Date (Web): 19 Oct 2018 Downloaded from http://pubs.acs.org on October 19, 2018

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The Journal of Physical Chemistry

Solving the Puzzle of the Coexistence of Different Adsorption Geometries of Graphene on Ni(111) Sabine C. Matysik,† Christian Papp,‡ and Andreas Görling∗,† †Lehrstuhl für Theoretische Chemie, Department Chemie und Pharmazie, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Egerlandstrasse 3, 91058 Erlangen, Germany ‡Lehrstuhl für Physikalische Chemie II, Department Chemie und Pharmazie, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Egerlandstrasse 3, 91058 Erlangen, Germany E-mail: [email protected] Phone: +49 9131 85-27766. Fax: +49 9131 85-27736

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Abstract Graphene and the Ni(111) surface have almost identical unit cells enabling the synthesis of high-quality graphene layers in perfect registry with the Ni surface in simple 1×1 unit cells. The relative orientation of graphene to the Ni(111) surface, however, is an open puzzle: up to three different structures (top-fcc, top-hcp, bridge-top) have been found experimentally. The present dispersion-corrected ab initio density-functional theory study on the adsorption of graphene on Ni(111) reveals a dependence of the adsorption geometry on the concentration of subsurface interstitial carbon and presents a possible solution to this puzzle. At very high local interstitial carbon concentrations, we observe only physisorption. At intermediate concentrations, chemisorbed top-hcp graphene is energetically most favorable whereas at low concentrations bridge-top and top-fcc are the preferred chemisorbed structures.

Introduction Chemical vapor deposition (CVD) of hydrocarbons on a metal surface is one of the most promising approaches to synthesize graphene. 1 Controlled growth by CVD enables the production of high-quality, large area, well-ordered graphene sheets on a metal support. 2,3 Due to its outstandingly small lattice mismatch, the Ni-graphene interface has attracted particular attention in this context as very well-ordered epitaxial graphene layers can be grown in perfect registry with the Ni(111) surface. 4–7 Among the different possible high-symmetry adsorption geometries of chemisorbed graphene (see Figure 1), there is no consensus as to which represent the most stable ones, neither computationally nor experimentally. Early studies mainly named top-fcc (Figure 1a) to be the preferred adsorption geometry of graphene. 4,8 More recent studies identified top-fcc and bridge-top (Figure 1b) to be the most stable geometries and to coexist on Ni(111) surfaces. 6 Yet another study employing STM revealed top-fcc, bridge-top and top-hcp (Figure 1c) as being present simultaneously. 9 Thus, we are

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faced with the puzzle of why experiments reproducibly lead to different adsorption geometries for the same system. (a) top-fcc

(b) bridge-top

(c) top-hcp

Figure 1: Adsorption geometries of graphene on Ni(111) that enable chemisorbed graphene. Carbon atoms are depicted in black, nickel atoms in shades of blue with darker shades depicting nickel layers closer to the graphene layer. As far as the graphene growth mechanism on Ni has been elucidated up to now, there is experimental evidence that subsurface interstitial carbon atoms facilitate graphene nucleation and growth provided that there is no nickel carbide layer on the Ni surface, that is, above approx. 770 K. 3,10,11 Subsequent graphene growth is mainly governed by the surface diffusion of deposited carbon. Thus, it is reasonable to assume that some interstitial carbon is still present after the graphene sheet has formed. However, previous studies of the graphene adsorption geometry on Ni have only focused either on pristine Ni surfaces 4,6,8,9,12,13 or on Ni with a nickel carbide surface layer. 14,15 This report addresses the influence of near-surface interstitial carbon atoms on the adsorption behavior of graphene by means of density-functional theory calculations aiming to solve the puzzle of the coexistence of different graphene-Ni(111) adsorption geometries.

Computational Details All DFT calculations were performed with the VASP code (Version 5.4). 16–19 The generalized gradient approximation was employed using the Perdew-Burke-Ernzerhof exchangecorrelation functional (PBE). 20 The PAW method was applied 21,22 as provided in the default 3



library and a cut-off energy of 450 eV for the plane wave basis was used. To account for long-range intermolecular interactions, the dispersion force correction scheme D3BJ 23 was utilized. In geometry optimizations, the atomic positions were relaxed until the forces were smaller than 0.01 eV Å−1 for larger supercells or 0.001 eV Å−1 for small supercells (e.g. 1×1 Ni slabs). SCF iterations were considered converged if a change in energy at least smaller than 10−6 eV was reached. A Methfessel-Paxton smearing 24 of first order was employed with 0.15 eV half width. The calculations were performed spin-polarized. In order to test the robustness of our findings with respect to the choice of exchangecorrelation functional and the dispersion correction, we additionally carried out calculations with the combinations PBE/D3zero, PBE/TS, PW91/D3BJ and RPBE/D3BJ. D3zero refers to Grimme’s D3 method without Becke-Johnson damping 25 and TS to the dispersion correction method developed by Tkatchenko and Scheffler. 26 As additional exchange-correlation functionals PW91 27 and a revised PBE (RPBE) 28 were used. For k-point sampling Monkhorst-Pack grids 29 were employed. For a 1×1 Ni(111) surface supercell 21×21×1 k-points were used after testing the convergence; the number of k-points was scaled down for larger cells accordingly. The Ni(111) surface was modelled via a 3+3 slab approach with 3 layers fixed to bulk positions and 3 layers free to relax; for 9 layercalculations (see text) a 3+6 slab approach was used. The experimental Ni lattice constant of 3.52 Å 30 was used for the bulk geometry. Supercells included 20 Å of vacuum between adjacent slabs. Adsorption energies were defined as

f ree Eads = EGr/N i − (EN i + EGr )

with EGr/N i as the total energy of graphene adsorbed on the Ni surface, EN i as the total f ree energy of the geometry-optimized Ni slab and EGr as the total energy of the geometry-

optimized free-standing graphene. Thus, larger negative values for Eads represent stronger

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adsorption. The adsorption energy was divided by the number of carbon atoms in the respective graphene sheet to yield an adsorption energy per carbon atom.

Results and discussion Similar to the adsorption of aromatic, organic molecules on metals, the adsorption of graphene on metal surfaces is strongly influenced by long-range dispersive forces. 31–33 Standard densityfunctional methods using semilocal exchange-correlation functionals cannot describe such forces. Therefore, density-functional methods have to be supplemented with van der Waals corrections in order to describe the complex adsorption behavior of graphene on Ni accurately. Several theoretical studies have addressed this issue in the past 12,34–37 but no mutual consent on the best method could be established. Among previous computational studies of the graphene adsorption on Ni, Bianchini et al. 9 used the early Grimme DFT+D method D2 38 to identify top-fcc, bridge-top and top-hcp as almost equally stable geometries while Zhao et al. 6 found top-fcc and bridge-top to be more stable than top-hcp employing the OBS scheme. 39 Several dispersion correction schemes, namely Grimme’s D2, D3zero 25 and D3BJ, 23 and two methods by Tkatchenko and Scheffler, TS 26 and TS-SCS, 40 have been tested in this report before interstitial carbon was introduced into the Ni surface. Our criteria for an adequate description included a comparison of the adsorption energy and the Ni-graphene top-fcc chemisorption distance to experimentally obtained values 4,41–43 and an evaluation of the respective potential energy surface. The potential energy surface of graphene adsorbed top-fcc on pristine Ni(111) should exhibit both a chemisorption and a physisorption minimum according to RPA results as well as several DFT+D and vdW-DFT studies. 13,35,37,44 Chemisorption is characterized by a Ni-graphene distance of about 2.1 Å, whereas physisorbed graphene exhibits a distance of about 3.2 Å from the Ni surface. 13 For top-fcc adsorption, the adsorption energy of chemisorbed graphene should be larger than that of physisorbed graphene. According to these criteria, we found that D3BJ is the

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most accurate dispersion correction for the Ni-graphene interface yielding adsorption energies per C atom of 9.4 and 9.0 kJ/mol and Ni-graphene distances of 2.04 and 2.12 Å for bridge-top and top-fcc, respectively, which are reasonably close to the experimental values of 9.2 kJ/mol 41–43 (for details see Ref. 12) and 2.11 Å, 4 and to RPA results of 6.5 kJ/mol and 2.17 Å. 37 Chemisorption in top-hcp geometry with an adsorption energy of 7.7 kJ/mol is energetically less favorable in the case of adsorption on pristine Ni(111) surfaces. Thus, without interstitial carbon in the Ni surface a preference for bridge-top and top-fcc adsorption is concluded in agreement with experimental and computational findings of Ref. 6. Note that the rather small adsorption energy differences per C atom give rise to large energy differences with respect to graphene domains even if these consisted of only several hundred carbon atoms. Further details about the different dispersion corrections can be found in the SI. In order to study the influence of interstitial carbon in Ni on the adsorption of graphene, the preferred position of interstitial carbon atoms in close proximity to the surface has to be deduced. We observed that octahedral vacancies are strongly favored over tetrahedral vacancies, which has also been found in several previous DFT studies 45–47 where an energy difference of 1.6 eV between carbon atoms in octahedral and tetrahedral vacancies was calculated. In the following, interstitial carbon atoms have therefore only been considered in octahedral vacancies. Furthermore, the energies of interstitial carbon atoms at different distances from the surface have been computed in a 9-layer slab with the 3 bottom layers fixed to their bulk positions corresponding to the experimental Ni lattice constant and the top 6 layers free to relax. These geometry optimizations revealed that interstitial carbon atoms between the topmost and the second Ni layer are more stable than carbon atoms further down in the Ni slab. This is likely to be caused by the fact that an interstitial carbon atom close to the surface perturbs a smaller number of Ni atoms than if the interstitial carbon is further away from the surface and surrounded in all three dimensions by an increasingly

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bulk-like environment. Moreover, nickel atoms in the topmost layer can most easily move in order to adapt to the presence of interstitial carbon. This is in line with previous results. 48

Figure 2: Ni(111) surfaces with (left) 0.33 ML, (middle) 0.25 ML and (right) 0.11 ML of interstitial carbon before graphene adsorption. The interstitial carbon atoms (depicted in orange) are located in octahedral vacancies between the first and second Ni layer. The size of the calculated surface unit cell is indicated by black lines. The influence of subsurface carbon atoms on the graphene adsorption geometry on Ni(111) was now investigated by introducing varying amounts of interstitial carbon into the Ni surface (see Figure 2 for three examples, namely a surface with 0.33 ML of interstitial carbon in the left panel, with 0.25 ML in the middle panel and with 0.11 ML in the right panel, and Figure S3 in the SI for the other surface unit cells) and by considering the adsorption of graphene in top-fcc, top-hcp and bridge-top geometry on those surfaces. Local and global energetic minima of chemisorption and physisorption of graphene on Ni(111) surfaces with interstitial carbon are shown in Figure 3. Figure 3 reveals that above 0.33 ML of interstitial carbon in all three adsorption geometries either physisorption is energetically favored over chemisorption (top-hcp at 0.5 ML) or there is no stable chemisorbed structure at all (top-fcc and bridge-top at 0.5 and 1 ML, top-hcp at 1 ML). Between 0.33 and 0.18 ML top-hcp chemisorption is most favorable and only below contents of 0.18 ML interstitial carbon bridge-top and top-fcc chemisorption become more stable than top-hcp. In Figure 4 the region between 0 and 0.33 ML of interstitial carbon is displayed in more detail showing the contribution of the dispersion correction besides the total chemisorption energy and the remainder, which represents the DFT contribution. Figure 4 shows that the dispersion contribution is almost identical for all three adsorption geometries with the 7



−7 −7.5 Eads [kJ/mol]

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−8 −8.5 −9 Top-fcc Top-hcp Bridge-top

−9.5 −10

1

0.8

0.6

0.4

0.2

0

Interstitial Carbon Content Figure 3: Adsorption energy per carbon atom Eads for the three adsorption geometries topfcc, bridge-top and top-hcp versus interstitial carbon content (defined as the number of interstitial carbon atoms per Ni(111) surface atom). Continuous lines refer to chemisorbed structures, dashed lines to physisorbed ones. At 0.33 ML bridge-top chemisorbed graphene was observed to be unstable and relax to the top-hcp geometry. bridge-top dispersion contribution being slightly more attractive. The change in relative stability of the three adsorption geometries is therefore due to the DFT contribution to the adsorption energy. This change in stability is due to the changes in the electronic structure introduced by the interstitial carbon. A Bader charge analysis reveals an electron transfer of 0.78 electrons from the surrounding Ni atoms to the interstitial carbon. The interstitial carbon atom causes a repulsive interaction with the graphene carbon atom at the fcc position directly above it, significantly destabilizing top-fcc adsorption and causing a small vertical displacement (5 pm) of that carbon atom away from the Ni surface. This can be seen in the left panel of Figure 5 by the charge depletion (green) between the Ni surface and the graphene atom located above

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Top-fcc Edisp EDFT Top-hcp Bridge-top

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5 Energy [kJ/mol]

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


0

−5 −10

0.3

0.2

0.1

0

Interstitial Carbon Content Figure 4: Chemisorption energy, dispersion and DFT contributions per carbon atom for the three adsorption geometries top-fcc, bridge-top and top-hcp versus interstitial carbon content. The total chemisorption energy is displayed as a continuous line, DFT and dispersion contributions as dotted and dashed line, respectively. the fcc hole and thus above the interstitial carbon, and the charge accumulation (red) above this graphene atom. The charge accumulation below carbon atoms located on top of Ni and thus not above the interstitial carbon atom is caused by a donation of electrons from Ni to the π-band of graphene whereas the charge depletion between the graphene carbon atoms corresponds to the back-donation from graphene’s σ-band to the Ni d-band, as has been described previously. 13 In the left panel of Figure 5 this back-donation is also diminished around the carbon atom that is directly above the interstitial carbon atom. This is further evidence for the unfavorable interaction between top-fcc graphene and a Ni surface that contains subsurface carbon.

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Figure 5: Charge density difference plots upon chemisorption of graphene on Ni(111) with 0.33 ML of interstitial carbon. Red color represents electronic density accumulation, green color electronic density depletion. A value of ±0.0032 a.u. is used for the isosurfaces. Graphene carbon atoms are depicted in black, interstitial carbon atoms in orange and Ni atoms in blue. (Left) Top-fcc adsorption. (Right) Top-hcp adsorption. Both effects are not observed at all for the top-hcp adsorption geometry, in which no graphene atoms are directly above the interstitial carbon atom (right panel of Figure 5). Therefore, it is inferred that the presence of subsurface carbon destabilizes top-fcc adsorption up to a point where physisorption is energetically favorable over chemisorption (see Figure 3). A similar behavior is observed for bridge-top adsorption at high interstitial carbon contents. In contrast to that, top-hcp is stabilized in a certain range of interstitial carbon concentration compared to adsorption on a pristine Ni surface. In order to verify that our findings are robust with respect to the choice of the dispersion correction and the exchange-correlation functional, we combined the PBE functional with the D3 dispersion correction without Becke-Johnson damping (D3zero) and with a dispersion correction by Tkatschenko and Scheffler (TS) instead of taking into account dispersion interactions via the D3BJ correction. Furthermore, we replaced the PBE exchange-correlation functional by the PW91 and the RPBE functionals while keeping the D3BJ dispersion correction, see SI for the detailed results. In all cases the qualitative behavior of the top-fcc and the top-hcp chemisorption energies with respect to the amount of subsurface carbon and their relative energetic ordering remains as discussed above for the PBE/D3BJ setup. This is true even for the combinations PBE/TS and RPBE/D3BJ, which yield an unrealistically

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high adsorption energy and a too small adsorption distance. The behavior of the bridge-top chemisorption energy as function of subsurface carbon content is also the same in all cases. However, for the setups PBE/TS and RPBE/D3BJ, the bridge-top chemisorption energies are somewhat shifted to lower values (stronger chemisorption) due to artificially increased dispersion interactions caused by the too small adsorption distance for these setups, which are known to lead to too small bulk Ni-Ni distances and are not appropriate for the considered systems. In summary, all key results presented here are robust with respect to the choice of exchange-correlation functional and dispersion correction. Table 1: Total energies in eV of calculated unit cells of slabs representing Ni(111) surfaces with graphene adsorbed in the indicated geometry with varying amounts of interstitial carbon (Cint ) at different distances from the surface. The size of the calculated slab unit cells differs with the amount of Cint , see Figure 2. Most stable structures at different amounts of interstitial carbon are marked in bold. Adsorption geometry

Cint below nth Ni layer

Interstitial Carbon Coverage [ML] 0.33 0.25 0.11 0 -70.568

Topfcc

first second third

-661.992 -661.926 -661.896

-291.057 -290.672 -291.062

-643.923 -643.933 -643.917 -70.540

Tophcp

first second third

-662.171 -661.733 -661.589

-291.114 -290.458 -290.938

-643.847 -643.671 -643.847 -70.576

Bridgetop

first second third

-662.169 -662.073 -661.967

-291.073 -291.105 -291.100

-643.958 -644.009 -643.975

As pointed out earlier, interstitial carbon atoms prefer near-surface positions when there is no graphene adsorbed. To investigate the influence of graphene adsorption on the preferred position of interstitial carbon, further calculations were performed with interstitial carbon at different distances from the surface, see Table 1. Interstitial carbon atoms were placed not only in octahedral vacancies below the first layer but also in those below the second or third 11



layer of the Ni slab, respectively. At interstitial carbon coverages as high as 0.33 ML, the positions below the first Ni layer are favored for all three adsorption geometries. At these quite high amounts of interstitial carbon, the demand for lattice relaxation and thus the preference for near-surface positions dominates over the above discussed repulsive interaction with topfcc and bridge-top graphene adsorption but renders these adsorption geometries energetically less favourable than the top-hcp arrangement, for which such repulsive interactions are not present. This preference for top-hcp adsorption and positions below the first Ni layer is also observed for an interstitial carbon coverage of 0.25 ML. For lower interstitial carbon coverages, a preference for carbon atoms in positions below the second Ni layer is observed for top-fcc and bridge-top adsorption in accordance with previous results. 48 This is attributed to the competing effects of the repulsive interaction between near-surface interstitial carbon and top-fcc or to a lesser extent bridge-top graphene and the energetically favored vacancies close to the surface to accommodate the lattice stress induced by the interstitial atom. Furthermore, top-fcc and bridge-top geometries are again favored over top-hcp adsorption when the interstitial carbon is positioned lower in the slab at all coverages as the resulting surface again resembles a pristine Ni(111) surface unperturbed by the interstitial carbon.

Conclusion It is concluded that interstitial carbon atoms have an impact on the energetically preferred adsorption geometry of graphene on Ni(111) surfaces. At higher interstitial carbon concentrations chemisorption in top-hcp geometry is more favorable than bridge-top and top-fcc adsorption which predominate at small interstitial carbon concentrations at the Ni surface. Our findings shed light on the open question of why different adsorption geometries were found experimentally: depending on the details of the experimental preparation procedure, different amounts of subsurface carbon atoms result. This leads to a different energetic ordering of the three possible chemisorption structures; therefore, depending on the experimental

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procedure different adsorption geometries are found. Indeed, assuming unevenly distributed interstitial carbon, i.e. some surface domains with larger amounts of near-surface interstitial carbon than others, experimental observations of all three chemisorbed structures coexisting on the Ni surface are explained with our findings. It would be highly interesting, though very challenging to experimentally prepare graphene on Ni(111) with different, well-defined, uniform amounts of subsurface carbon.

Acknowledgement This project was supported by the Deutsche Forschungsgemeinschaft (DFG) within the research unit SFB 953 “Synthetic Carbon Allotropes”.

Supporting Information Available The following files are available free of charge. • Ni_graphene_puzzle-SI.pdf: Comparative analysis of different dispersion correction schemes with regard to the adsorption of graphene on pristine Ni(111).

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Graphical TOC Entry Decreasing interstitial carbon content

Physisorption

Top-hcp

19

Bridge-top / top-fcc


Solving the Puzzle of the Coexistence of Different Adsorption

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