Atomic Scale Identification of Coexisting Graphene Structures on Ni(111)

Letter pubs.acs.org/JPCL

Atomic Scale Identification of Coexisting Graphene Structures on Ni(111) Federico Bianchini,†,# Laerte L. Patera,†,‡ Maria Peressi,*,†,§,∥ Cristina Africh,*,‡ and Giovanni Comelli†,‡,⊥ †

Department of Physics, Università degli Studi di Trieste, via Alfonso Valerio 2, 34127 Trieste, Italy IOM-CNR Laboratorio TASC, Area Science Park, s.s. 14 km 163.5, Basovizza, 34149 Trieste, Italy § IOM-CNR DEMOCRITOS Theory@Elettra Group, Sincrotrone Trieste, Area Science Park, s.s. 14 km 163.5, Basovizza, 34149 Trieste, Italy ∥ Consorzio Interuniversitario Nazionale per la Scienza e la Tecnologia dei Materiali (INSTM), Unità di ricerca di Trieste, piazzale Europa 1, 34128 Trieste, Italy ⊥ Center of Excellence for Nanostructured Materials (CENMAT), Università degli Studi di Trieste, via Alfonso Valerio 2, 34127 Trieste, Italy ‡

S Supporting Information *

ABSTRACT: Through a combined scanning tunneling microscopy (STM) and density functional theory (DFT) approach, we provide a full characterization of the different chemisorbed configurations of epitaxial graphene coexisting on the Ni(111) single crystal surface. Topfcc, top-hcp, and top-bridge are found to be stable structures with comparable adsorption energy. By comparison of experiments and simulations, we solve an existing debate, unambiguously distinguishing these configurations in high-resolution STM images and characterizing the transitions between adjacent domains. Such transitions, described in detail through atomistic models, occur not only via sharp domain boundaries, with extended defects, but predominantly via smooth in-plane distortions of the carbon network, without disruption of the hexagonal rings, which are expected not to significantly affect electron transport. SECTION: Surfaces, Interfaces, Porous Materials, and Catalysis

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he discovery of the unique properties of graphene1 has triggered an overwhelming interest from the scientific community, concerning both fundamental issues and possible applications. One of the most used methods to produce graphene is chemical vapor deposition (CVD) on metal substrates, yielding large-scale production of high quality films.2,3 CVD graphene growth involves exposure of the substrate, kept at a specified temperature, to a hydrocarbon atmosphere; the adsorbed molecules dissociate, forming H atoms that desorb as H2 and C atoms arranged in the graphitic honeycomb network. The carbon−metal surface interaction therefore plays a fundamental role both for the formation of the graphene layer, and in determining its properties.4 Among the various metal substrates used for CVD graphene growth, nickel raised particular attention. Indeed, the lattice constant of the Ni(111) surface is very close to that of graphene,5,6 allowing for epitaxial growth of large homogeneous domains.7 Furthermore, hydrocarbon decomposition barriers are quite small on Ni, permitting graphene growth at reasonably low temperatures. Finally, Ni substrates can be easily etched to isolate the sp2 carbon layer, thus making CVD growth on nickel one of the most interesting routes for graphene large-scale production. © 2014 American Chemical Society

The atomic structure of graphene on Ni(111) has been thoroughly investigated, with several possible configurations proposed. Pioneering experiments by Rosei et al. suggested an hcp-fcc configuration for the C atoms,8 later ruled out by lowenergy electron diffraction (LEED)-IV experiments,9 which first suggested top-fcc and top-hcp arrangements. These and other alternative structures were proposed as the most stable ones in many experimental and theoretical investigations, without reaching a general consensus. In particular, top-fcc, top-hcp, and hcp-fcc structures have all been proposed in a work based on density functional theory (DFT), neglecting dispersion forces and using generalized gradient approximation (GGA) for the exchange correlation functional.10 In this context, FuentesCabrera et al. found that the top-bridge configuration is the most stable by using the local density approximation (LDA) and showing that there are significant discrepancies between GGA and LDA results, pointed out the need to include van der Waals interactions.11 Recently, DFT-GGA calculations with semiempirical corrections for dispersion interactions finally Received: December 2, 2013 Accepted: January 13, 2014 Published: January 13, 2014 467

dx.doi.org/10.1021/jz402609d | J. Phys. Chem. Lett. 2014, 5, 467−473

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established that graphene chemisorbs on Ni(111) only in two possible stable configurations (top-bridge and top-fcc), while in other high symmetry arrangements (including top-hcp) it does not have a stable chemisorbed minimum or can only physisorb.12,13 Still, all the high symmetry structures studied in ref 13 display very similar adsorption energies, and therefore could coexist on the surface. Indeed, scanning tunneling microscopy (STM) images by Lahiri et al.14 demonstrated the coexistence of top-fcc and top-hcp graphene, evidenced by the formation of an extended defect at the boundary. In addition, ref 12 corroborated the coexistence of the top-bridge and topfcc geometries by comparing calculated and measured C1s core level shifts. More recently, DFT-GGA calculations using a slightly different dispersion force correction term, confirmed top-fcc as the energetically most favorable geometry, followed by top-bridge, top-hcp, and hcp-fcc, without clarifying though their stability toward lateral displacements.15 Other DFT-GGA calculations performed to study the adsorption of porphyrins on graphene on Ni(111) yield the lowest energies for the topbridge, top-fcc, and top-hcp geometries.16 In conclusion, despite some consensus on these three structures as the lowest energy ones, their stability, and ordering in energy are still under debate. Moreover, a direct microscopic experimental evidence for the coexistence of all proposed structures, and an atomic level description of their transition regions are still missing. We use STM and DFT-GGA calculations including dispersion forces correction to clarify the overall picture of the different configurations of epitaxial graphene coexisting on a Ni(111) single crystal. We confirm that top-fcc, top-hcp, and top-bridge are chemisorbed structures with comparable adsorption energies, finding that they are all stable. We prove, for the first time, that the three structures can be distinguished in high-resolution STM images based on their different appearance, both in simulated images of local density of states (LDOS) isosurfaces and in experimental data. We find that the transition between different configurations can occur either sharply, via extended defects, or smoothly, via regions of compressed graphene. As highlighted in Figure 1, in our high-resolution STM images, the atomic-scale features of graphene on Ni(111) significantly vary in distinct areas of the same region, unambiguously indicating the coexistence of different configurations. The STM contrast of graphene overlayers on Ni(111) is discussed in a few DFT papers,12,14,17,18 presenting though only a limited comparison with experiments, not sufficient for a safe interpretation of our images, while in literature experiments graphene/Ni(111) usually appears as a homogeneous triangular array of bright protrusions. To obtain specific fingerprints of different graphene configurations, we thus investigate in more detail by DFT the energetics, the electronic structure, and the STM images of some selected arrangements. We concentrate on the top-fcc, top-hcp, and top-bridge adsorption configurations, yielding the lowest chemisorption energies according to refs 12, 13, and 15. The stick-and-ball models of the optimized structures are shown in Figure 2a,b. Our calculations clearly establish that, using DFT-GGA with dispersion forces corrections, in all three cases stable chemisorbed structures are obtained, with a graphene-metal surface distance of about 2.1 Å and a small reduction of the interplanar distance between the two outermost Ni planes. Details about the electronic charge rearrangement are reported in the Supporting Information (SI). The chemisorption energy

Figure 1. Graphene on Ni(111). (Top) atomically resolved STM image showing the coexistence of different contrasts. (Bottom) Zoom on the regions highlighted with squares in the top image [V = +3 mV, I = 0.7 nA].

per C atom is −0.16, −0.14, and −0.15 eV in top-fcc, top-hcp, and top-bridge configurations, respectively, basically equivalent within our numerical accuracy of ∼0.02 eV. Notably, the three configurations are not stable for DFT-GGA without dispersion interaction corrections. Our findings are consistent with the available experimental data9,12 and, extending the conclusions of ref 19, reconcile most of other previous theoretical results based on different techniques.10−14,18,20 Figure 2c shows the simulated constant current STM images of filled states close to the Fermi level, at small tip−sample distances; specifically, we mapped an integrated local density of states (ILDOS) iso-surface lying ∼2−3 Å above graphene. The top-fcc structure exhibits a triangular array of bright spots (above fcc C atoms) and gray spots (above top C atoms), as already shown by Zhao et al.,12 Kang et al.,17 and Dzemiantsova et al..18 The appearance of the STM image for top-hcp structure, which to our knowledge was never simulated before, is very similar: bright spots corresponding to hcp C atoms form a triangular arrangement, with gray features in on-top sites. The top-bridge geometry, conversely, gives a completely different simulated image: zigzag bright stripes along a Ni close-packed crystallographic direction alternate to lines of “holes” almost centered on hcp Ni sites, as previously suggested.12 The detailed features of the simulated STM images can be explained by the atomic projected density of states, as reported in the SI. The three different contrasts obtained in simulated STM images nicely correspond to those highlighted in Figure 1, typically characterizing our experimental images. To facilitate the comparison, experimental high-resolution images acquired at high tunneling current and close to the Fermi level are reported in Figure 2d next to simulations. It is clear that (i) a triangular array of protrusions, with gray features in the center of each triangle pointing toward the top of the image is associated to top-fcc graphene domains; (ii) a triangular array of protrusions with gray shadows in the center of each triangle pointing toward the bottom of the image represents top-hcp regions;21 (iii) zigzag stripes oriented along one of the closepacked directions of the underlying substrate correspond to top-bridge areas. 468



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Figure 2. Different graphene/Ni(111) configurations. Stick-and-ball models: (a) top-view and (b) side-view. Corresponding STM simulated (c) and experimental (d) STM images. Adsorption energies are indicated in brackets below the name of each configuration. Computational parameters: ILDOS iso-surface lying ∼1−2 Å above graphene and with an ILDOS value of 7 (top-fcc), 6 (top-hcp), and 2 (top-bridge) 10−5 |e|/a03. Scanning parameters: top-fcc [V = −0.3 V, I = 2 nA], top-hcp [V = −100 mV, I = 20 nA], and top-bridge [V = −10 mV, I = 25 nA].

graphene properties, mainly leading to self-doping24 and enhancement of the electron scattering across domain boundaries.25 When a variety of different graphene rotational domains are present, as typically occurs for CVD growth on most transition metal surfaces, the domain boundaries are usually complex 2D structures.24,26 Conversely, on substrates where graphene can grow epitaxially, with only translational domains, 1D defects can form. Topological defects of this kind deserve particular interest also in freestanding graphene for their exceptional electronic properties.27−31 Indeed, 1D extended defects have already been observed by Lahiri et al.14 in epitaxial graphene on Ni(111), at sharp boundaries between top-fcc and top-hcp domains, and can be considered metallic nanowires. Figure 3 demonstrates that the connection of top-fcc and top-hcp domains can actually occur in-plane both via the formation of 1D defects and via a gradual distortion of the C network. Indeed, the defect line crossing almost vertically in the middle the image in Figure 3a is a sharp boundary: on the right we recognize top-fcc graphene; proceeding toward the left, we observe sequentially top-hcp in a very thin stripe (approximately two unit cells wide), a region of distorted graphene, where complete carbon rings are visible, and finally another top-fcc domain. The sharp boundary appears as an extended defect with a quite regular structure. The zoom in Figure 3b shows the boundary at the atomic scale, remarkably similar to the structure already observed by Lahiri et al.14 We studied the atomic scale structures of the sharp boundaries by DFT. The model for top-hcp/top-fcc is shown in Figure 3c. The positions of the carbon atoms have been obtained by relaxing the structure derived from the experimental image of Figure 3b. Although in our calculations the small size of the simulation cell affects the description of the two different domains causing a small fictitious distortion of the graphene, the simulated image in Figure 3d shows a remarkable resemblance with the experimental one, strongly supporting the validity of the structural model. The few dark features

We highlight that discrimination between top-fcc and tophcp depends on our capability to image on top C atoms appearing as gray features, as predicted by DFT. Joining adjacent on top C atoms, we can mark the same unit cell for both structures, thus identifying the position of the second C atom within it. Notably, the top C atoms, and therefore the differences between the two configurations, are visible in our images only for scanning parameters corresponding to a short tip−sample distance, estimated in ∼2 Å for typical scanning values of It = 30 nA and Vb = 10 mV.22 At larger distances, only the usual triangular array or faint stripes are observed, as expected by analyzing the calculated ILDOS iso-surfaces (see SI). Our results demonstrate the possibility of identifying the actual graphene geometry by its STM contrast, thus allowing for a statistical analysis of the surface distribution of its different configurations. By examining about 60 high-resolution images, we found the top-fcc as the statistically most abundant configuration (∼65%), in agreement with the results of the LEED I−V study on epitaxial graphene grown by ethylene CVD in UHV,9 even though in that case a higher growth T was used. A smaller contribution is given by top-bridge (∼22%) and top-hcp (∼13%) configurations. Nicely, the relative order of the calculated adsorption energies follows that of the observed coverage: stronger adsorption corresponds to larger coverage. However, the three configurations are practically equivalent from DFT predictions, and reasonably also factors other than thermodynamics, such as growth kinetics from graphene nuclei with different configurations, influence the observed coverage. Having demonstrated the existence and stability of different adsorption geometries for epitaxial graphene on Ni(111), we investigate their physical connection on the surface. The transition from domains with different configurations can in principle occur in-plane following two different routes: a sharp domain boundary or a distortion of the C network.23 Sharp domain boundaries lead to topological defects, with the formation of nonhexagonal carbon rings that largely affect 469



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SI), transforms into top-fcc geometry. This relaxation is profoundly different from the alternative transition behavior observed in ref 14. In that case, the local detaching of graphene from the Ni(111) substrate and its slight curvature away from the substrate allow accommodating the matching of the fcc and hcp graphene/Ni(111) configurations by a continuous graphene layer, without the formation of a topological defect. Here the mismatch is accommodated in-plane by a local compression of the carbon network. Figure 4 shows three coexisisting domains. In Figure 4a (top and bottom left corner), the triangular arrangement of

Figure 3. Transition between top-fcc and top-hcp domains. (a) STM image showing both a sharp domain boundary and a smooth distortion. On the left of the sharp boundary, a thin top-hcp region (highlighted by the dark blue rectangle) extends for 2−3 nm and then stretches into top-fcc via distortion of the C-rings. On the right of the boundary, an undistorted top-fcc domain is imaged. [V = −100 mV, I = 30 nA]. (b) Zoom on the yellow square in (a). The positions of C atoms in the top-hcp (blue dots) and top-fcc (red dots) domains close to the boundary are highlighted. (c) Stick-and-ball model of the relaxed boundary. (d) Simulated constant current STM image, with an ILDOS value of 9 × 10−5 |e|/a03. (e) Zoom on the light blue square in (a), highlighting the position of a C vacancy at the boundary in the top-hcp domain.

Figure 4. Transition between top-hcp and top-bridge and between top-bridge and top-fcc domains. (a) STM image showing three coexisisting domains: top-fcc (top), top-bridge (center/bottom-right), and top-hcp (bottom-left). A sharp domain boundary joins the tophcp and top-bridge regions, while the latter converts into a top-fcc flake toward the top of the image, with a distortion of the C network. (b) A grid intersecting the Ni on top positions is drawn on (a). (c) Zoom on the sharp domain boundary between top-hcp and top-bridge regions. Green and blue dots indicate the positions of C atoms [V = −10 mV, I = 25 nA]. (d) Stick-and-ball model of the relaxed boundary and (e) corresponding simulated STM image at constant current, with a ILDOS value of 9 × 10−5 |e|/a03.

interrupting the domain boundary in the experimental image are C vacancies in hcp position on the top-hcp side, located where the pentagons-octagon regular arrangement along the extended defect gets out of phase (see Figure 3e). On the left side of the boundary, the top-hcp structure after two-three unit cells starts compressing along the direction of two parallel C−C bonds of the graphenic hexagon, as indicated by the arrow in Figure 3a, and in ∼4 nm (corresponding to 8 graphene rings), with an average normal strain of ∼3.5% (see

protrusions suggests the presence of either top-fcc or tophcp. Unfortunately, in this case a slight asymmetry in the scanning tip prevents us to image dark shadows between bright spots and thus to unambiguously discriminate between the two at a first glance, while the third domain (bottom-right) has clearly the appearance of the top-bridge configuration. The coexistence of different configurations in the same image, 470



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however, helps us to discriminate also the triangular protrusions. Indeed, on the basis of the known position of C atoms in the top-bridge domain, in Figure 4b, we can draw a grid joining the Ni atoms. As shown in Figure 2, the position of the bright protrusion with respect to neighboring Ni atoms allows for a safe identification of the different graphene configurations, as top-fcc (top of the image) and top-hcp (bottom left corner). Again, the transition between different domains follows two distinct routes: a sharp boundary between top-bridge and top-hcp, and a small distortion of the carbon network between top-bridge and top-fcc occur. The zoom in Figure 4c allows us to propose a tentative structure for the sharp boundary. We marked the position of the carbon atoms starting from the known atomic arrangement and extended the structure up to the boundary to have a guess of the atomic positions. The boundary seems to be formed by eptagonpentagon pairs with alternate orientation, forming a chain of Stone-Wales defects. The model for the corresponding DFT investigation of the top-hcp/top-bridge boundary is described in Figure 4d. Analogously with the model for the top-hcp/topfcc boundary, the carbon atoms have been initially positioned according to the experimental image of Figure 4c and then relaxed. The simulated STM image reported in Figure 4e shows the main features of the experimental one, although the agreement is not perfect. Discrepancies may be related to the asymmetric tip shape (see above) or to the limited size of our model, which cannot completely catch the progressive distortion of the top-bridge domain approaching the boundary. From the top-bridge domain, the C network converts within a narrow transition region to the top-fcc configuration without any topological defect. The smooth transition occurs via distortion of the graphene rings in a region ∼2 nm wide, due to a shear strain in the C-network of about 1° (see SI). Notably, in all our images, as in Figure 1, smooth transitions between adjacent domains are more frequent than sharp domain boundaries. In conclusion, we demonstrated the coexistence of different stable chemisorbed graphene configurations on Ni(111). By comparison of experimental and simulated STM images, we unambiguously discriminate between top-fcc, top-hcp, and topbridge graphene, inferring in all cases a general predominance of top-fcc. The transition between the different structures occurs sharply, via 1D domain boundaries, or smoothly, via a gradual in-plane compression or distortion of the graphene rings. The latter transition type, predominant in our images, is likely not to influence significantly electron transport, since no scattering centers are formed.

Waals interactions, which are essential to study the system,12,13,34 were included with the DFT-D approach,35 as in ref 15, and with some difference from the approach used instead in refs 12 and 13. Integration over the Brillouin zone was performed using the Methfessel−Paxton smearing technique36 and the Monkhorst−Pack mesh of k-points37 dependent on the size of the simulation cell. For a perfect infinite graphene layer with 23 Å of vacuum, a 12 × 12 × 1 kpoint grid centered on the Gamma point was used. Convergence tests indicated the use of a kinetic energy cutoff of 30 Ry for the plane wave basis set and an energy broadening of 0.01 Ry. We obtained an equilibrium lattice parameter of 3.52 Å for Ni and 2.46 Å for graphene, in remarkable agreement with the experimental values, indicating that our calculations were performed on a realistic ground. To simulate the graphene adsorption on Ni surface, we used a periodically repeated supercell with a five-layer Ni slab, thick enough to reproduce the bulk Ni features in the third layer from the surface, and with in-plane periodicity dependent on the configuration (simply 1 × 1 for the adsorption of a perfect infinite graphene layer). To simulate sharp domain boundaries, because of the constraints imposed by the use of periodic boundary conditions, we found it convenient to use a graphene nanoribbon with a domain boundary along the central backbone. The ribbon was hydrogen terminated in order to avoid a strong binding of the edges with the metallic surface and consequently a fictitious curvature of the graphene due to the small width of the ribbon. Constant-current STM images were simulated within the Tersoff-Hamann approximation,38 according to which the tunneling current is proportional to the energy-ILDOS. The latter is the real-space density of electronic states which participate in the tunneling process, having an energy between εF and εF ± |e|Vb. Specifically, we mapped an ILDOS iso-surface lying within a certain height range over the graphene. This approach does not coincide with the usual cutting of the ILDOS at a constant height, and mimics more accurately the formation of a constant-current experimental STM image. Ball models were rendered with the XCrySDen software.39 The adsorption energy per C atom was computed as Eads = (E(graphene/Ni) − E(graphene) − E(Ni))/N, where the three terms are, respectively, the total energy of the entire system, the energy of the graphene, and that of the Ni slab in the same simulation cell. With this definition, a negative value indicated that the adsorption was favored.

EXPERIMENTAL AND COMPUTATIONAL DETAILS The experiments were performed in a UHV system (base pressure 1 × 10−10 mbar) equipped with standard sample preparation facilities and with an Omicron VT-STM. Epitaxial graphene was prepared by exposure of a Ni(111) single crystal to ethylene (p = 2 × 10−7 mbar) at 400−500 °C. In-situ highresolution STM images were acquired at room temperature with typical scanning parameters I = 0.5/30 nA and Vb = −300/ −3 mV (filled states). Images of empty states do not show significant differences. DFT calculations were performed with the plane-wave-based suite Quantum ESPRESSO32 employing the Generalized Gradient Approximation for the exchange-correlation functional in the Perdew-Burke-Ernzerhof parametrization (GGAPBE).33 Semiempirical corrections accounting for the van der

The analysis of the charge density and projected density of states has been performed to clarify the bonding character of the adsorbed configuration. Models of strained continuous boundaries between different adsorption domains have been studied. This material is available free of charge via the Internet at http://pubs.acs.org.

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ASSOCIATED CONTENT

S Supporting Information *

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AUTHOR INFORMATION

Corresponding Authors

*E-mail: [email protected] (experiments). *E-mail: [email protected] (theory). Present Address

# (F.B.) Physics Department, King’s College London, Strand, London, WC2R 2LS, United Kingdom.

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Functional Theory Calculations with a Semiempirical Long-Range Dispersion Correction. J. Appl. Phys. 2013, 114, 143713. (16) Hermanns, C. F.; Tarafder, K.; Bernien, M.; Krüger, A.; Chang, Y.-M.; Oppeneer, P. M.; Kuch, W. Magnetic Coupling of Porphyrin Molecules through Graphene. Adv. Mater. 2013, 25, 3473−3477. (17) Kang, M.; Jung, S.; Park, J. Density Functional Study of the AuIntercalated graphene/Ni (111) Surface. Phys. Rev. B 2010, 82, 085409. (18) Dzemiantsova, L.; Karolak, M.; Lofink, F. Multiscale Magnetic Study of Ni (111) and Graphene on Ni (111). Phys. Rev. B 2011, 84, 205431. (19) Mittendorfer, F.; Garhofer, A.; Redinger, J.; Klimeš, J.; Harl, J.; Kresse, G. Graphene on Ni(111): Strong Interaction and Weak Adsorption. Phys. Rev. B 2011, 84, 201401. (20) Hamada, I.; Otani, M. Comparative van Der Waals DensityFunctional Study of Graphene on Metal Surfaces. Phys. Rev. B 2010, 82, 153412. (21) It has to be noted that all our images are oriented along the same crystallographic direction, as determined by the sample mounting. (22) Kolb, D. M.; Simeone, F. C. Electrochemical Nanostructuring with an STM: A Status Report. Electrochim. Acta 2005, 50, 2989− 2996. (23) Sicot, M.; Leicht, P.; Zusan, A.; Bouvron, S.; Zander, O.; Weser, M.; Dedkov, Y. S.; Horn, K.; Fonin, M. Size-Selected Epitaxial Nanoislands Underneath Graphene Moiré on Rh(111). ACS Nano 2012, 6, 151−158. (24) Tapasztó, L.; Nemes-Incze, P. Mapping the Electronic Properties of Individual Graphene Grain Boundaries. Appl. Phys. Lett. 2012, 100, 053114. (25) Koepke, J.; Wood, J.; Estrada, D.; Ong, Z. Atomic-Scale Evidence for Potential Barriers and Strong Carrier Scattering at Graphene Grain Boundaries: A Scanning Tunneling Microscopy Study. ACS Nano 2012, 7, 75−86. (26) Sutter, E.; Albrecht, P.; Sutter, P. Graphene Growth on Polycrystalline Ru Thin Films. Appl. Phys. Lett. 2009, 133109, 5−8. (27) Pelc, M.; Chico, L.; Ayuela, a.; Jaskólski, W. Grain Boundaries with Octagonal Defects in Graphene Nanoribbons and Nanotubes. Phys. Rev. B 2013, 87, 165427. (28) Lin, X.; Ni, J. Half-Metallicity in Graphene Nanoribbons with Topological Line Defects. Phys. Rev. B 2011, 84, 075461. (29) Kou, L.; Tang, C.; Guo, W.; Chen, C. Tunable Magnetism in Strained Graphene with Topological Line Defect. ACS Nano 2011, 5, 1012−1017. (30) Kan, M.; Zhou, J.; Sun, Q.; Wang, Q.; Kawazoe, Y.; Jena, P. Tuning Magnetic Properties of Graphene Nanoribbons with Topological Line Defects: From Antiferromagnetic to Ferromagnetic. Phys. Rev. B 2012, 85, 155450. (31) Dai, Q. Q.; Zhu, Y. F.; Jiang, Q. Electronic and Magnetic Engineering in Zigzag Graphene Nanoribbons Having a Topological Line Defect at Different Positions with or without Strain. J. Phys. Chem. C 2013, 117, 4791−4799. (32) Giannozzi, P.; Baroni, S.; Bonini, N.; Calandra, M.; Car, R.; Cavazzoni, C.; Ceresoli, D.; Chiarotti, G. L.; Cococcioni, M.; Dabo, I.; et al. QUANTUM ESPRESSO: A Modular and Open-Source Software Project for Quantum Simulations of Materials. J. Phys.: Condens. Matter 2009, 21, 395502. (33) Perdew, J.; Burke, K.; Ernzerhof, M. Generalized Gradient Approximation Made Simple. Phys. Rev. Lett. 1996, 77, 3865−3868. (34) Cheng, D.; Barcaro, G.; Charlier, J. Homogeneous Nucleation of Graphitic Nanostructures from Carbon Chains on Ni (111). J. Phys. Chem. C 2011, 115, 10537−10543. (35) Grimme, S. Semiempirical GGA Type Density Functional Constructed with a Long Range Dispersion Correction. J. Comput. Chem. 2006, 27, 1787−1799. (36) Methfessel, M.; Paxton, A. High-Precision Sampling for Brillouin-Zone Integration in Metals. Phys. Rev. B 1989, 40, 3616− 3621.

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS L.L.P. acknowledges funding from Area di Ricerca Scientifica e Tecnologica of Trieste and from MIUR through Progetto Strategico NFFA. C.A. acknowledges support from MIUR (PRIN 2010−2011 No. 2010N3T9M4). Computational resources have been partly obtained through Italian SuperComputing Resource Allocation (ISCRA) grants of the Consorzio Interuniversitario CINECA, partly within the agreement between the University of Trieste and CINECA. L.L.P. and C.A. thank Cinzia Cepek for continuous fruitful discussions.

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Atomic Scale Identification of Coexisting Graphene Structures on Ni(111)

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