Nucleation of Graphene Precursors on Transition Metal Surfaces

Article pubs.acs.org/JPCC

Nucleation of Graphene Precursors on Transition Metal Surfaces: Insights from Theoretical Simulations Alister J. Page,†,‡,# Ying Wang,§,∥,# Hai-Bei Li,† Stephan Irle,*,§ and Keiji Morokuma*,†,⊥ †

Fukui Institute for Fundamental Chemistry, Kyoto University, Kyoto 606-8103, Japan Discipline of Chemistry, School of Environmental and Life Sciences, The University of Newcastle, Callaghan 2308, Australia § WPI-Institute of Transformative Bio-Molecules and Department of Chemistry, Graduate School of Science, Nagoya University, Nagoya 464-8602, Japan ∥ State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, China ⊥ Cherry L. Emerson Center for Scientific Computation and Department of Chemistry, Emory University, Atlanta, Georgia 30322, United States ‡

S Supporting Information *

ABSTRACT: We present quantum chemical simulations demonstrating graphene precursor formation on bcc (111) transition metal surfaces during the chemical vapor deposition process. We observe that the experimentally reported positive curvature of graphene precursors is a consequence of the natural tendency toward pentagon formation during the precursor selfassembly process. Density functional theory calculations reveal that the stability of these precursors is driven by the dominance of metal−carbon σ bonding over metal−carbon π bonding at the precursor edge. These simulations show that Fe(111) catalysts facilitate precursor formation at lower carbon densities and increase precursor stabilities. However, the stronger catalyst−carbon interaction strength in the case of Fe(111) significantly promotes catalyst surface degradation. The use of more weakly interacting catalysts, such as Ni(111) and Cu(111), circumvents this issue. However, QM/MD simulations of Ni(111)-catalyzed chemical-vapor deposition (CVD) show that graphene nucleation requires a significantly higher carbon density, compared to the case of Fe(111). We propose that the performance of different transition metals with respect to catalyzing graphene growth, akin to carbon nanotube growth, correlates with the catalyst−carbon interaction strength.

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INTRODUCTION Graphene is heralded as “the ultimate material” due to its remarkable electronic, thermal, and mechanical properties.1−3 It is these properties that are the basis for many proposed graphene-based devices on the nanoscale. Earlier reports of graphene synthesis consisted of techniques such as mechanical exfoliation of highly oriented pyrolytic graphite (the “scotchtape method”4). However, chemical-vapor deposition (CVD) synthesis of graphene, typically using transition or noble metal catalysts, is increasingly becoming the most likely candidate by which large-area graphene will be manufactured on a commercial scale.5,6 In this respect, the Ni(111) surface exhibits particular notoriety, with a number of experimental demonstrations of graphene growth on Ni(111) reported in the literature.7−12 Cu is also an increasingly popular catalyst,13−21 due to the fast growth rates and large domain sizes that can be obtained by its use. Presumably the latter phenomena are driven by the relatively weak carbon−metal interaction and poor bulk carbon solubility in the case of Cu. The former is also true, although to a lesser extent, in the case of Ni. On the other hand, metal surfaces such as Fe(111) exhibit notably less catalytic activity in the context of graphene nucleation13 and also yield smaller © XXXX American Chemical Society

domain sizes. A relationship between the carbon−metal interaction strength, catalyst activity, and the mechanism/ kinetics of graphene growth is therefore implicated by these CVD studies. Similar relationships have previously been observed in the context of carbon nanotube growth on transition metal catalysts.22 Despite the depth of current experimental and theoretical23−27 literature concerning CVD graphene synthesis, relatively little atomistic information regarding the graphene nucleation process has yet been reported. Only recently has the role of graphene “island precursors” in the graphene formation process been demonstrated experimentally on Ir(111),28 Ru(0001),29 and Rh(111)30 and subsequently investigated theoretically on a number of catalysts.9,31 Such precursors have also been implicated in the formation of graphene quantum dots on Ru(0001).32 The absence of such precursors has recently been shown to favor the formation of Haeckelitean intrinsically metallic, 2D relative of grapheneinstead of graphene itself.33 Other recent works have shown that Received: May 1, 2013 Revised: June 18, 2013

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dx.doi.org/10.1021/jp404326d | J. Phys. Chem. C XXXX, XXX, XXX−XXX

The Journal of Physical Chemistry C

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processes of the graphene growth process while maximizing the efficiency of the MD simulation. It also allows the influence of carbon density on the reaction mechanism of graphene precursor formation to be assessed. We note here that conditional MD is possible only by virtue of the fact that sp2hybridized network formation is characterized entirely by the rapid coalescence of short polyyne fragments.36 We have recently used an analogous approach in modeling CVD phenomena on Si-based nanoparticles in the context of CNT growth.44 Our density functional theory (DFT) calculations use the Perdew−Burke−Ernzerhof45 form of the generalized gradient approximation, in conjunction with the projector augmented wave method as implemented in the VASP software package.46−48 A plane wave cutoff energy of 400 eV was employed for all DFT calculations. The σ- and π-bonding interactions between graphene and Fe(111), Ni(111), and Cu(111) surfaces employed the model systems depicted in Figure 1.

subsurface nucleation of such precursors is possible at high carbon densities.34 The mechanism by which discrete graphene precursor islands are converted into large-area graphene is itself unknown at present. In this work, we aim to address this shortcoming by presenting quantum chemical simulations of acetylene CVD on transition metal catalyst surfaces. By doing so, we will demonstrate the natural, atomistic mechanism by which graphene precursors form. We will also propose a mechanism to explain the precursor → graphene transformation on transition metal catalyst surfaces. Directly comparing various metal catalyst surfaces enables us also to demonstrate the effect of the carbon−catalyst interaction strength on the mechanism and kinetics of the precursor formation process. We further corroborate this analysis using density functional theory calculations of graphene−metal interaction strengths. It is demonstrated that this single parameter can be used to rationalize the differences observed in graphene formation on transition metal surfaces.

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COMPUTATIONAL METHODS Our QM/MD methodology has been extensively applied in the context of fullerene formation and CNT/graphene growth33,35−37 with success. This methodology consists of integrating the classical equations of motion in conjunction with a quantum chemical potential. In our case the equations of motion were integrated using the velocity-Verlet scheme.38 The quantum chemical potential was evaluated “on-the-fly” at each MD iteration using the self-consistent-charge density-functional tight-binding (DFTB) method39,40 in conjunction with a finite electronic temperature41,42 (Te = 3000 K). The occupancy of each molecular orbital was therefore described by a Fermi− Dirac distribution function of its energy (and therefore varied continuously over the interval [0, 2] near the Fermi level). The use of a finite electronic-temperature approach accounts for the open-shell nature of carbon atoms possessing dangling bonds and the numerous near-degenerate d-orbitals present in the metal catalyst . In a recent investigation,33 we reported on the “template effect” induced by a coronene-like fragment during graphene nucleation on Ni(111). In these simulations the carbon density on the Ni(111) surface was held at a rather high 83 mol %, compared to that of pristine epitaxial graphene. In light of recent experiments that demonstrate the role of graphene precursors, these previous simulations seem somewhat unrealistic, if one’s interest is to understand the precise mechanism of graphene nucleation on a metal surface. To this end, we consider here the nucleation of graphene under much lower, more realistic carbon density conditions. Our model CVD process consists of adsorbing C2 moieties on pristine (111) surfaces, C2 being chosen as it is increasingly viewed as the active species in CVD synthesis of graphene.43 Following the equilibration of bcc Fe(111)/Ni(111) metal terraces, this is achieved via the following algorithm: first, a new C2 moiety was adsorbed onto the surface at a randomly chosen position; the system was then annealed with MD for 0.5 ps at 1180 K, after which the population of Cn chains for all n was computed; if the average length of all Cn chains was less than a prechosen threshold value of two (we ultimately considered several values for Ni(111); in each case 10 trajectories were computed), a new C2 moiety was adsorbed onto the metal terrace, otherwise the system was annealed for a further 0.5 ps; and so on. Such “conditional MD” enables us to capture the essential chemical

Figure 1. Model systems employed for the calculation of graphene− M(111) (a) σ- and (b) π-bond interaction strengths, depicted here in the case of Fe(111). Brown and cyan spheres represent Fe and C atoms, respectively.

The bcc (111) metal surface in each case was modeled using a 4 × 4 × 4 slab with periodic boundary conditions, with each surface separated by a 50 Å vacuum region. A k-point sampling of 2 × 2 × 1 using the technique of Monkhorst and Pack49 was found to provide sufficient accuracy in this case.

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RESULTS AND DISCUSSION We will initially discuss our QM/MD simulations of Fe(111)catalyzed CVD graphene growth. We believe that the simulations reported here are the first to be reported in the literature. Upon adsorption of C2 moieties onto the Fe(111) surface, two primary phenomena were observed, viz, sp2network formation and Fe(111) surface degradation by adsorbed carbon (see Figure S1, Supporting Information). The former path, which resulted in graphene precursor formation, occurred in more than 50% of all computed trajectories. Moreover, the formation of these precursors took place within 100−150 ps, reflecting the remarkable catalytic activity of Fe(111). Typically these sp2-networks consisted of 15−30 carbon atoms and were composed entirely of pentagons and hexagons (we discuss the exact formation mechanism of one such precursor below). Contrary to recent theoretical investigations,9,31 however, these as-formed graphene precursors obtained here do not correspond to those with the highest symmetry or greatest thermodynamic stability. Considering that barriers associated with structural transformations in carbon structures (such as Stone−Wales transformations) exhibit barriers in excess of 5 eV,50 the formation of these precursors may be kinetically, and not thermodynamically, B



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controlled. However, results obtained here do not rule out the transformation from pentagon to hexagon (so-called defect healing51) over longer time scales, which would result in more thermodynamically stable species of higher symmetry. However, since the kinetics of graphene precursor formation are so favorable, even at low carbon density, it is likely that the precursor → graphene transformation takes place before these defects can be removed from the precursor. Generally most, if not all, carbon on the Fe(111) surface was sequestered into the precursor as it formed. In each case, the precursors formed were isolated on the Fe(111) surface (i.e., they were not connected artificially due to the periodic boundary conditions enforced on the simulations), and generally exhibited little diffusion across the Fe(111) surface due to the relatively strong C−Fe interaction. Therefore, island diffusion does not drive the subsequent coalescence of these precursors, and thus graphene growth, in this case. However, the existence of “tendril”-like extended polyyne chains at the precursor edge suggests an alternative mechanism by which the precursor → graphene transformation takes place. That is, two neighboring, isolated sp2-hybridized structures may be joined via the interaction of these polyyne chains in a manner akin to the cross-linking mechanism of SWCNT growth suggested by Eres et al.52 It is also likely that the strength of the carbon−catalyst interaction plays a decisive role in the precise mechanism of the precursor → graphene transformation; further simulations to this effect are currently being performed and will be reported elsewhere. We return to a general discussion of the impact of carbon−catalyst interaction strength on graphene growth below. An explicit example of graphene precursor formation on Fe(111) is depicted in Figure 2. The formation mechanism of this structure is almost identical in nature to that of singlewalled carbon nanotube (SWCNT) nucleation36 and fullerene formation.35,37 In both the latter cases, nucleation begins with the formation of a “Y”-junction structure, which results from the coalescence of two adjacent extended polyyne chains on the catalyst surface. These chains in turn were previously formed by repeated additions of carbon feedstock species, in this case C2 (however, an equivalent process is also observed using individual carbon atoms). This Y-junction structure then naturally isomerizes to form a pentagon on the catalyst surface. Van Wesup et al.53 have recently demonstrated that such a pentagon structure is thermodynamically less favorable on Cu(111) compared to a hexagon; thus, this pentagon first mechanism appears to be kinetically driven. The intrinsically positive curvature of the pentagon-first structure (Figure 2a, 30 ps) is mismatched with that of the surface, which has zero curvature. In a recent investigation,33 we found that on Ni(111) extended sp2-networks similar to graphene and Haeckelite also formed via this pentagon-first mechanism. However, it was suspected that this mismatched curvature induced was due to the high carbon density employed in that simulation. Results presented here however confirm that this is not the case. Following the formation of the initial pentagon, subsequent ring condensation proceeded in a manner analogous to that observed in SWCNT and fullerene formation. Figure 2a shows that the subsequent ring condensation took place in a seemingly random fashion, with no clear preference for pentagons or hexagons. In this particular case (Figure 2b), the populations of these two ring structures were almost equal at 130 ps, which lead to a noticeable curvature in the sp2hybridized network in agreement with experimental observa-

Figure 2. (a) Graphene precursor formation observed on Fe(111) using ρC = 30 atom %. (b) Polygonal carbon ring addition during graphene precursor formation on Fe(111). QM/MD simulations show that graphene precursor formation requires a localized high carbon density and is defined primarily by hexagon/pentagon formation following polyyne chain coalescence, as with the case with fullerenes and CNTs. Brown and cyan spheres represent Fe and C atoms, respectively. See also movie M1 (jp404326d_si_002.qt) in the Supporting Information.

tions.28 No particular epitaxial relationship between the precursor and the catalyst surface is evident from these simulations. Instead, the growing precursor is, at this stage, stabilized via terminal C−Fe σ bonding and results in the deformation of the upper layers of the Fe(111) surface. Such σ bonding is a mild example of a more severe phenomenon, that of Fe(111) surface degradation. Degradation of the Fe(111) surface in the current simulations was the result of two phenomena, viz., the formation of surface vacancy defects and Cn−Fe−Cn bridging structures. Such bridging structures on Cu(111) have been investigated previously by Wu et al.54 and were also recently observed during graphene formation on Ni(111).55 Figure 3a demonstrates the three trajectories with the most extensive degradation of the Fe(111) surface. However, of all trajectories C



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dimensional carbon structures on the Ni(111) surface at low carbon density (see Figure 4). This was presumably due to the greater mobility of carbon on the Ni(111) surface, which in turn arose from the weaker C−Ni interaction strength.22

Figure 3. (a) Three examples of Fe(111) surface degradation after 130 ps observed using (from left to right) ρC = 22, 19, and 22 atom %. Surface degradation consists of vacancy defect and Cn−Fe-Cn bridging structure formation. (b) Mechanism of Fe(111) surface degradation observed using ρ C = 16 atom %. See also movie M2 (jp404326d_si_003.qt) in Supporting Information.

Figure 4. Outcomes of simulated CVD on Ni(111) using (from left to right) ρC = (a) 7, (b) 24, and (c) 66 atom %, following 200 ps. At low and intermediate values of ρC, surface carbon species result only in polyyne chains bound to the Ni(111) surface through terminal C−Ni σ-bonds. The formation of a graphene precursor, or extended sp2 carbon network, is only observed at substantially higher values of ρC. The evolution of (c) is depicted in Figure 5.

computed, 80% showed the presence of such surface degradation, indicating that this is an extremely common phenomenon. This is also consistent with the relatively small domain size and poor quality of graphene produced when using Fe(111) as a catalyst in experimental graphene synthesis.13 The evolution of one trajectory is shown in greater detail in Figure 3b and movie M2 (jp404326d_si_003.qt), from which it is immediate that the degradation of the surface could take place more quickly than graphene precursor formation, within the first ca. 10 ps in this case. By this time three surface vacancy defects had been formed. While the formation of these vacancy defects and Cn−Fe−Cn bridging structures was extremely labile, they were nonetheless stable as is evident by their formation at ca. 10 ps and the persistence for the remainder of the simulation. This is in agreement with the remarkable thermodynamic stability of these Cn−Fe−Cn bridging structures, as demonstrated by Wu et al.54 Following their removal from the Fe(111) lattice, the coordination sphere of these Fe atoms was filled either by carbon atoms or by extended polyyne chains, with σ C−Fe bonding dominating. The vacancy defects thus formed were subsequently filled by either lone carbon atoms or short polyyne chains (predominantly C2). The existence of the former species highlights the ability of the Fe(111) surface to cleave C−C bonds. More generally, however, this phenomenon suggests a tendency toward surface carbide formation in the case of Fe(111), instead of graphene nucleation, as has also been suggested from recent experiments. This tendency is solely due to the strength of the C−Fe interaction, as opposed to C−Ni interaction, for example,22,56 and the preference for σ C−Fe bonding, as opposed to π C−Fe bonding. We turn now to QM/MD simulations of graphene precursor formation on Ni(111). Graphene precursor formation on Ni(111) bears a striking resemblance to precursor formation on Fe(111), discussed above. The same two primary phenomena were observed, viz., carbon chain formation (leading to graphene precursor formation) and C n −Ni−C n bridge formation (leading to surface degradation). In the case of Ni(111), however, the former was overwhelmingly dominant over the latter, particularly at higher carbon densities. At carbon densities equivalent to that employed in the Fe(111) simulations, the coalescence of C2 and larger Cn was remarkably limited over comparable time scales (see Figures S2 and S3, Supporting Information). Moreover, C2/Cn coalescence more typically resulted in the formation of amorphous three-

Nucleation of an extended sp2 structure was only observed on Ni(111) on this time scale using a carbon density typically double that employed for Fe(111). One such case of precursor formation at high carbon density is depicted in Figure 5; further examples are depicted in Figure S4 (Supporting Information). Graphene precursor formation in this case is, however, remarkably different from that observed on Fe(111). Of particular note is the tendency of the extended Cn chains to diffuse away from the catalyst surface in this case; i.e., the role of the Ni(111) surface is merely to anchor these polyyne chains in place by terminal C−Ni σ-bonds. In this sense, precursor formation on Ni(111) does not resemble a surface-mediated process, as in the case of Fe(111). It is only once a threshold carbon density is reached that random ring condensation occurs on Ni(111) via polyyne chain cross-linking (Figure 5).52 This latter stage in precursor formation takes place relatively quickly, as does further ring condensation and the formation of an extended sp2 structure akin to graphene. Prior to this, however, the initial sp2 precursor is stabilized on the catalyst surface, as in the case of Fe(111), via terminating C−Ni σbonds. Graphene precursor formation on Ni(111) has in common with formation on Fe(111) a predominance of pentagons in the precursor structure, and the lack of any noticeable epitaxy between the catalyst surface and the precursor. Carbon dissolution into the Ni(111) subsurface layers was not observed in these simulations. However, considering the barriers associated with this process57 and the necessity for surface defects in the Ni structure (such as stepedge defects),43 this is not surprising over these time scales. These simulations therefore suggest that optimal conditions for graphene precursor formation, and more generally CVD graphene growth, on different metal catalysts vary substantially. We have further elucidated these differences using DFT calculations of σ- and π-interactions between graphene and various transition metal catalyst surfaces (Table 1 and Figure 1). It is noted that these interactions computed using DFTB, provided in Table 1 for comparison, reproduce qualitative trends between σ- and π-interactions observed with DFT. The observed dynamics of graphene precursor formation observed on Fe(111) and Ni(111), discussed above, correlate exactly D



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This is consistent with the observed formation of extended polyyne chains that are bound to the Ni(111) catalyst surface solely by terminating C−Ni σ-bonds. The subsequent formation of the precursor structure parallel to the metal surface therefore arises purely due to the interaction of the polyyne chains away from the Ni(111) surface, not due to any attractive C−Ni(π) interaction. On the other hand, the C− Fe(π) interaction is 0.27 eV, and perhaps more importantly, the optimal graphene−Fe(111) distance resulting from π-bonding is 2.04 Å (compared with 3.58 and 3.76 Å for Ni(111) and Cu(111), respectively). This immediately accounts for the enhanced surface mediation of precursor formation in the case of Fe(111). It also explains the tendency toward Fe(111) surface degradation observed in these QM/MD simulations, discussed above, and the stability of carbon-filled surface vacancy defects and Cn−Fe−Cn bridging structures.

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CONCLUSION We have presented here theoretical simulations of the early stages observed during CVD graphene growth on transition metal surfaces. These simulations establish a natural mechanism toward the experimentally observed60 positive, “domelike”, curvature of graphene precursors. Furthermore, these simulations demonstrate that such precursors, and more generally the graphene growth process itself, cannot be explained with recourse only to thermodynamic factors. For instance, QM/ MD simulations show no evidence of epitaxy between the nascent graphene precursor and the catalyst surface during the earliest stages of graphene growth, due to the prevalence of defective pentagon rings in the precursor structure. We note also that precursor structures formed in these simulations rarely, if ever, coincided with the most thermodynamically favorable structures for a given size. Considering the high kinetic barriers associated with structural transformation in carbon nanostructures,50 graphene formation may potentially be kinetically controlled. These two observations are the consequence of the relative strengths of the carbon−catalyst σbonding interaction over the carbon−catalyst π-interaction, the former of which was shown to be invariably stronger, irrespective of the catalyst metal. The tendency for σ-bond formation was found to stabilize these (relatively) unfavorable precursor structures on the Fe(111) and Ni(111) surfaces, via the formation of terminating C−Ni(σ) bonds at the edge of the precursor. The relatively large magnitude of the C−Fe(π) interaction was shown to drive precursor formation on Fe(111) toward a surface-mediated process. The same cannot be said of precursor formation in the case of Ni(111) catalysts, for which precursor formation was driven by polyyne chain crosslinking52 divorced from the catalyst surface. However, the magnitude of the C−Fe σ/π interaction promoted an alternative, unwanted, chemical processthat of Fe(111) surface degradation. The use of more weakly interacting catalyst species, such as Ni(111), circumvented this problem, at

Figure 5. (a) Graphene precursor formation observed on Ni(111) using ρC = 66 atom %. (b) Polygonal carbon rings addition during graphene precursor formation on Ni(111). QM/MD simulations show that graphene precursor formation, unlike in the case of Fe(111), is not a surface-mediated process. Instead, polyyne chain cross-linking away from the surface leads to sp2 network formation. See also movie M3 (jp404326d_si_004.qt ) in the Supporting Information.

with the relative magnitudes of the σ- and π-interactions between pristine graphene and these respective metal surfaces. Table 1 shows that C−M(π) interactions are either negligible or an order of magnitude weaker compared to the respective C−M(σ) interaction. For example, while the C−Ni(π) interaction is effectively negligible (a fact that has been established previously using a number of DFT functionals58,59), ), the C−Ni(σ) interaction is 2.76 eV per carbon−metal bond.

Table 1. Comparison of σ- and π-Bonding between Graphene and Fe(111), Ni(111), and Cu(111) Surfaces in Terms of Binding Energy (eV/carbon atom) and Metal−Carbon Bond Distances (Å, in Parentheses)a σ DFT DFTB a

π

Fe

Ni

Cu

Fe

Ni

Cu

2.94 (1.91) 2.68 (2.13)

2.76 (1.86) 2.96 (2.10)

2.13 (1.95) 1.82 (2.26)

0.27 (2.04) 0.14 (2.75)

0.00 (3.58) 0.05 (3.03)

0.00 (3.76) 0.06 (3.11)

Binding energy is defined here as (E[M(111)−graphene] − E[M(111)] − E[graphene])/n, for n C atoms. E



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the cost of using a significantly higher carbon density to observe graphene precursor formation. The performance of different transition metals with respect to catalyzing graphene growth, and the mechanism of graphene growth itself, therefore correlate with the catalyst−carbon interaction strength. This proposal is akin to contemporary theories of carbon nanotube nucleation and growth.22

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ASSOCIATED CONTENT

S Supporting Information *

Figures showing further examples of graphene precursor formation on Fe(111), Ni(111) simulations with various ρC; QuickTime movies M1 (jp404326d_si_002.qt ), M2 (jp404326d_si_003.qt), and M3 (jp404326d_si_004.qt). This material is available free of charge via the Internet at http:// pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]; [email protected]. Author Contributions #

These authors contributed equally to this work.

Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The authors wish to thank Prof. Stephan Hofmann, University of Cambridge, for informative discussions. This work was in part supported by CREST (Core Research for Evolutional Science and Technology) grants in the areas of i) High Performance Computing for Multiscale and Multiphysics Phenomena and ii) of Synthesis and Novel Functions of Soft π-materials from JST. A.J.P. acknowledges a Fukui Fellowship from Kyoto University and a University Fellowship from The University of Newcastle. Y.W. acknowledges the support of the National Youth Fund (No. 21203174). We are grateful for generous supercomputer time at the Institute for Molecular Science (IMS) in Okazaki, Japan.

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Nucleation of Graphene Precursors on Transition Metal Surfaces

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