A possible approach to achieve quasi-freestanding graphene on a substrate for technological purpose is the intercalation of alkali metal atoms. Cs intercalation between graphene and Ni(111) therefore is investigated using density functional theory, incorporating van der Waals corrections. It is known that direct contact between graphene and Ni(111) perturbs the Dirac states. We find that Cs intercalation restores the linear dispersion characteristic of Dirac fermions, which agrees with experiments, but the Dirac cone is shifted to lower energy, i.e., the graphene sheet is n-doped. Cs intercalation therefore decouples the graphene sheet from the substrate except for a charge transfer. On the other hand, the spin polarization of Ni(111) does not extend through the intercalated atoms to the graphene sheet, for which we find virtually spin-degeneracy. Graphene is gaining attention for its unique two-dimensional structure and special electronic properties, which are interesting for many applications14π bands22Intercalation of noble metal atoms can restore the original band structure to give rise to quasi-freestanding graphene+1 state, so that it does not participate in chemical bonding but acts purely as spacer.In the following, we consider the structural, electronic, and magnetic properties of graphene on Ni(111), using density functional theory, and analyze the changes when intercalating the system with different concentrations of Cs atoms. By the large atomic radius of Cs a very efficient decoupling of graphene from the substrate can be expected. Cs is an alkali metal with one electron in its outer shell and thus strongly favors a CsThe 1 × 1 unit cell of the graphene on Ni(111) consists of 4 Ni layers and 1 C layer on top. To determine the favorable lateral shift between the two materials, we study four structural configurations: (i) Hollow, where each atom of the topmost Ni layer is in the center of a C honeycomb. (ii) Face centered cubic (fcc), where three of the C honeycomb atoms are located on top of atoms of the topmost Ni layer and the center of the C honeycomb is located on top of an atom of the second Ni layer. (iii) Hexagonal close packed (hcp), which is similar to the fcc case but with the center of the C honeycomb located on top of an atom of the third Ni layer. (iv) Bridge, where the center of the C honeycomb is located between two atoms of the topmost Ni layer. ENi is the total energy per atom in bulk Ni and EC is the total energy per C atom in graphene. The fact that the bridge configuration is only 10 meV higher in energy than the fcc configuration implies that it is accessible as well. Even the hcp configuration might be accessible with low probability. Indeed, these configurations experimentally can coexist25where dC/Ni, see dC/Ni. We obtain finite though small magnetic moments of −0.02 and 0.03 μB on the two C atoms due to Ni-C hybridization, in agreement with the results reported in ref. The C-C bond length in the fcc configuration is 1.44 Å, whereas it is 1.42 Å in pristine graphene. This small tensile strain corresponds to the mentioned small lattice mismatch. The obtained perpendicular distance between graphene and the Ni(111) surface, μB comes from the Ni atoms, where atoms in the first layer show magnetic moments of 0.67 μB and atoms in the other layers show 0.68 μB.We next consider a 2 × 2 supercell with graphene artificially placed in a distance of 6 Å from the Ni(111) substrate, see μB, which is close to the bulk Ni value of 0.67 μB, to values of 0.49 μB for the atom directly below Cs and 0.59 μB for the other atoms in the same layer.We find that intercalation of Cs enlarges the distance between the graphene sheet and the Ni(111) substrate to 6.0 Å post relaxation (3.1 Å from graphene to Cs and 2.9 Å from Cs to Ni). The in-plane Cs-Cs distance is 5.0 Å. We note that the graphene sheet shows no significant structural modification, see We next consider larger supercells, see As another ferromagnetic substrate we have also considered Co(0001) to check whether our results for Ni(111) are of general validity. The band structure of the 2 × 2 supercell, see We have investigated the effect of Cs intercalation on the structural, electronic, and magnetic properties of graphene on Ni(111) and Co(0001). An fcc configuration is found to be energetically favorable in agreement with previous experimental and theoretical results, and therefore is chosen for studying the intercalation. Different supercell sizes have been considered to examine the effect of the Cs concentration. In agreement with experimental results, the Cs intercalation restores the Dirac cone, since it decouples graphene from the substrate, resulting in n-doped quasi-freestanding graphene. Both for the Ni(111) and Co(0001) substrates the graphene sheet exhibits no trace of spin polarization.Density functional theory is employed using the Vienna Ab-initio Simulation PackageHow to cite this article: Alattas, M. and Schwingenschlögl, U. Quasi-freestanding graphene on Ni(111) by Cs intercalation. Sci. Rep.6, 26753; doi: 10.1038/srep26753 (2016).


Consequently, the external laser beam can control the propagation of the graphene SPP between the ON and OFF status. This all-optical modulation effect is still obvious when the spot size of the external laser is reduced to 400 nm while the modulation depth is as high as 114.7 dB/μm.We report a theoretical study showing that by utilizing the illumination of an external laser, the Surface Plasmon Polaritons (SPP) signals on the graphene sheet can be modulated in the sub-micron scale. The SPP wave can propagate along the graphene in the middle infrared range when the graphene is properly doped. Graphene's carrier density can be modified by a visible laser when the graphene sheet is exfoliated on the hydrophilic SiO The development of information technology requires the highly integrated signal processing circuits. Gradually, the evolution of signal processing systems was mainly separated into two directions, the electronic one and the optical one. The all-electronic processing technique is quite mature in now days and the feature size of the most advanced devices has been reduced to 14 nm according to Intel, which means the all-electronic signal processing circuits can be ultra-compactAs the carrier of the optical signals, the waveguide plays an important role in optical circuits. Silicon optical waveguides can be used as modulators to reach the speed as 100 GHz, but the thickness of the waveguide is as large as hundreds of nanometers456792111213142/Si substrate and the initial status of the graphene is p-doped2 layer is as thick as 290 nm. The SPP wave can propagate along such a graphene waveguide since its permittivity is suitable, which is demonstrated as Here we theoretically propose an all-optical modulation method for the SPP wave within the size of hundreds of nanometers. This modulator is based on the surface plasmonic wave, which is supported by the doped graphene sheet. The excitation of the graphene SPP has been discussed in lots of papers9102/Si substrate, is lower than the Dirac point as sn ≈ 4 × 1012 cm−2 according to Ref. cμ ≈ 0.217 eV. By bringing in an external visible laser illuminating on the graphene and gradually increasing the laser's power, the graphene is changed from the p-doped status to the light p-doped status, and finally to the quasi-neutral status. The wavelength of the external laser is 532 nm and a laser power as large as 0.6 mW can rise the graphene's Fermi energy to the Dirac point, which is shown as cμ = 0.001 eV.Graphene is a special two-dimensional material since its permittivity can be obviously changed when its chemical potential is varied. The chemical potential can be treated as the same value as the Fermi energy for the room temperature1217σ), is positiveσ) < 0. For the purpose of investigating the mode property of the SPP wave on the graphene, it is necessary to utilize the relation between the graphene's conductivity (σ) and the chemical potential (cμ), which is illustrated as the Kubo formulasε) of graphene should be obtained, so that its conductivity (σ) and thickness (Δ) are taken into the calculationWithin a certain range of wavelength, the TM polarized wave can be supported by a doped graphene once if the imaginary part of the graphene's optical conductivity, Im is almost zero in the infrared range when the graphene is in the quasi-neutral status (cμ = 0.001 eV). As ε) becomes larger as the doping level of the graphene becomes higher. So, the doped graphene plays the role as a thin layer of metal and it forms the Insulator-Metal-Insulator (IMI) structure together with the air and the SiO2/Si substrate. In order to give a better support for the SPP mode, the value of −Re(ε) needs to be larger so that the highly doped graphene should be chosen to form the IMI structure. Meanwhile, the loss of the SPP waveguide is another important parameter to be concerned, which is indicated by the imaginary part of the graphene's permittivity, Im(ε). ε) of the quasi-neutral graphene is always larger than that of the doped graphene, which means the propagation distance of the SPP is longer when the graphene is doped in a higher level. Within the range of 0.001 eV ≤ cμ ≤ 0.217 eV, we can draw the conclusion that the graphene SPP waveguide is in the ON status when the graphene's chemical potential is cμ = 0.217 eV while it is in the OFF status when cμ = 0.001 eV.From the analysis above, the graphene's permittivity is dispersive with different wavelengths and different chemical potentials. Since the external laser can change the graphene's carrier density from 4 × 102 layer is 290 nm, which is much larger than the lateral decay length of the graphene SPP so that we only consider about the dispersion of the SiO2 material in the simulation. The data of the silicon dioxide (glass) is obtained from Ref. 2 material is nearly lossless within 1 μm ≤ λ ≤ 7.634 μm, which oppositely indicates the SPP wave propagating along the graphene sheet may suffer from a severe loss when λ is larger than 7.634 μm.The permittivity of the air is always 1 for any range of wavelength. Apart from the dispersive permittvity of the graphene, the dispersive property of the substrate material is also necessary to be taken into consideration. The thickness of the SiOSPPk), which can be influenced by the chemical potential (cμ), the permittivity of the SiO2 substrate (subε) and the wavelength in free space (λ0) according to Ref. 2, which is shown in SPPδ = 1/2Im(SPPk). The propagation distance of the SPP wave is demonstrated in λ0) increased, SPPδ becomes larger until λ0 = 7.634 μm. For λ0 > 7.634 μm, SPPδ drops very quickly because the SPP energy penetrates inside the SiO2 substrate and it is lost severely due to the large Im(ε) of SiO2. The red, blue and green curves in SPPδ is as large as hundreds of nanometers when the graphene is doped. However, when the graphene is illuminated by the external laser and be tuned back to the quasi-neutral status, SPPδ is smaller than 1 nanometer, which is demonstrated as the insert diagram in SPPλ) is much smaller than λ0 since SPPλ = 2π/Re(SPPk). From the results shown in λ0 is hundreds of times larger than SPPλ when the graphene is doped. As the insert of λ0 is more than ten thousands times larger than SPPλ when the external laser makes the graphene be in the quasi-neutral status. Similarly, the lateral penetration depth of the SPP wave (iδ) shows the same trend since iδ = SPPλ/2π, which is demonstrated in One of the key parameter of the graphene's SPP wave is the wave vector  between the ON and OFF status as big as possible. part see . In this2-Ag nano-strcuture even confine the light energy within a feature size of several nanometers to design the sub-diffraction-limited lasers24As far as the diffraction limit is concerned, the spot size of the external laser can be only reduced to about half of its wavelength, which means the illumination length can only be reduced to the sub-micron scale. If the spot size of the laser is as small as several nanometers, the proposed SPP modulator may obtain a smaller feature size. Practically, some experimental data demonstrate that the mode size of the light emission can be reduced and break through the diffraction limit by the hybrid plasmonic structures232425λ0 = 7.634 μm and cμ = 0.217 eV, which indicates the device has to be very short. Being limited by the optical doping level, the chemical potential of graphene can just vary from 0 eV to 0.217 eV. If some other optical doping procedures, which can change the chemical potential in a larger range, are utilized, we may gain a longer propagation distance of the SPP wave. For instance, using the irradiation in the UV wavelength or replacing the SiO2/Si substrate by some other material may gain a better results. Here an assumption is made that the graphene can be optically doped from 0 eV to 0.8 eV. Then, the properties including SPPδ, iδ and λ0/SPPλ are demonstrated in cμ = 0.8 eV, the propagation distance can be increased by more than 10 times to 17000 nm, which will effectively benefit the construction of the optical circuits.Nevertheless, a general and significant problem of the SPP wave also remains in our proposed method: the loss. As the numerical analysis show, the propagation distance of the SPP wave is about 1260 nm for ε) of the graphene is a negative value. The tunability of the permittivity is of great importance in integrated optics but not only graphene possesses such a property. In the future, researchers can try looking for some material with such a tunability, such as some other two-dimensional or the photosensitive substance, to design the all-optical devices.In addition, the reason why we choose graphene to be the waveguide of this all-optical modulator is that the graphene's permittivity can be obviously modified by the external laser and Re(2/Si substrate and utilizing an external laser to illuminate a part of the graphene, a modulation method is proposed for the SPP wave with two specialties including all-optical and small feature size. The illumination length is as short as 400 nm and it obtains an extinction raito as high as 45.9 dB, which means the modualtion depth reaches 114.7 dB/μm. The all-opitcal modulation can be realized in some other silicon structures such as the micro-ring and the fiber but the footprint is in the scale of several microns, which cannot be equal in force with the all-electronic modulation. Based on the all-optical modulation of the surface plasmonic wave, our proposed method decreases the feature size into the sub-micron scale with a quite high modulation depth. Such kind of thoughts can be applied for designing the fundemental devices in the all-optical interconnection systems, which may progress the construction of the large-scale integration optical circuits in the future.In conclusion, by exfoliating the graphene sheet onto a hydrophilic SiOThe simulations are performed in the 2D type with the help of the finite-different time-domain method by using “Lumerical FDTD Solutions”. The effects shown in L.Z.Y. designed the work and wrote the manuscript. C.Y.P. and A.S. provide the optical doping method of the graphene. C.Y.Z. and X.L. discussed about the excitation of the SPP mode on graphene in the simulation. Y.L. and H.Y. performed theoretical analyses and simulations. Y.B.L. and X.Q.J. helped to plot all the figures. J.Y.Y. supervised the project. All authors discussed the results and commented on the manuscript.Supplementary information


Drosophila melanogaster genetic model system.One of the most notable recent advances in electron microscopy (EM) was the development of genetically-encoded EM tags, including the fluorescent flavoprotein Mini-SOG (Mini-Singlet Oxygen Generator). Mini-SOG generates good EM contrast, thus providing a viable alternative to technically-demanding methods such as immuno-electron microcopy (immuno-EM). Based on the Mini-SOG technology, in this paper, we describe the construction, validation and optimization of a series of vectors which allow expression of Mini-SOG in the Drosophila (DMS tag) using PCR-mediated gene assembly. The photo-oxidation reaction triggered by DMS was then tested using these vectors in Drosophila cell lines. DMS tag did not affect the subcellular localization of the proteins we tested. More importantly, we demonstrated the utility of the DMS tag for EM in Drosophila by showing that it can produce robust photo-oxidation reactions in the presence of blue light and the substrate DAB; the resultant electron micrographs contain electron-dense regions corresponding to the protein of interest. The vectors we generated allow protein tagging at both termini, for constitutive and inducible protein expression, as well as the generation of transgenic lines by P-element transformation.We constructed a Mini-SOG tag that has been codon-optimized for expression in Drosophila. The constructed vectors will no doubt be a useful molecular tool for genetic tagging to facilitate high-resolution localization of proteins in Drosophila by electron microscopy.We demonstrated the feasibility of Mini-SOG tagging in The online version of this article (doi:10.1186/s12575-016-0034-1) contains supplementary material, which is available to authorized users. Arabidopsis phototropin 2. Mini-SOG creates EM contrast by generating oxygen singlets when activated by light, which in turn catalyze the conversion of diaminobenzidine (DAB) to a localized osmiophilic polymer [C. elegans cells [Drosophila, and validated and optimized its use in this model organism.The recent development of genetically-encoded tags for electron microscopy such as Mini-SOG  and APEX polymer   was amplified from cDNA prepared from Drosophila embryos. Mitochondrial-targeting sequence corresponding to the N-terminal 31-amino acid mitochondrial import signal of cytochrome c oxidase subunit VIII (CG7181) [Drosophila genome. The DNA sequence of Mini-SOG , with codon frequency threshold set to 20 %. The DMS gene was synthesized by a two-step PCR method [Open reading frame of ne2Av CG599 was amR method  . The reDrosophila cell lines were maintained according to standard protocols. Cells were transfected with 0.1–0.3 ug DNA using Effectene Transfection Reagent (QIAGEN) according to the manufacturer’s protocol. For induction of the metallothionein promoter, 0.2–0.5 mM copper sulphate  was added 24 h post-transfection. Two days following transfection, the cells were harvested for confocal microscopy and photo-oxidation.Cells were incubated with 250 nM of Mitotracker Red (Molecular Probes) in culture medium for 30 min at room temperature, washed once with medium and immediately observed under a microscope.Transfected cells were plated onto gridded 35 mm glass-bottom dishes  for 30 min, and observed under the microscope, either directly or after fixation (as described below). Confocal images were taken using LSM 780 .Photo-oxidation by Mini-SOG was performed essentially as described by Shu et al., 2011 [4) in 0.1 M sodium cacodylate buffer for 30 min, and then washed with pure water three times. The samples were subsequently dehydrated by ethanol series. A 1:1 ethanol:epoxy resin mix was then added to the samples and incubated on a mixer for 30 min. Afterwards, the resin mix was replaced by pure resin and incubated overnight, and an extra change of pure resin was performed. The resin was then allowed to polymerize in a 60 ° C oven for two days. The resin block was trimmed to 0.5 mm cubes, which were further sliced to 50 nm sections using a microtome. These sections were mounted onto copper grids  without any stain and observed by a JEM-1230R microscope (JEOL), at an accelerating voltage of 100 keV, using bright field imaging.Samples were prefixed with 2.5 % glutraldehyde in 0.1 M sodium cacodylate buffer, postfixed with 1 % osmium tetroxide  and inducible . The ubiquitin promoter is derived from the Ubqi-p63E gene (CG11624), which drives high level expression in cell lines and tissues in la flies . We alsola flies . In addiNext we set out to test whether the DMS tags affect protein localization in Clone-8 cells. We generated DMS fusion to histone 2Av (a nuclear marker ), a chimDrosophila cells, using histone2Av fusion. We found that the bleaching of mCherry occurs after around 1 min of reaction, while the photo-oxidation reaction continues to be very robust 4 min after the reaction started, as judged by the continuous increase in the darkness of the osmium deposit in the nucleus (Fig. We subsequently investigated the time dependence of the photo-oxidation reaction by DMS in Next we looked at mCherry-DMS-histone2Av and mito-DMS cells under the electron microscope. It can be clearly seen (Fig. Drosophila tissues. A transgenic line was made by transgenesis using the pUAST-mCherry-DMS-his2Av construct. This line expresses mCherry-DMS-his2Av in the salivary gland and wing discs when crossed to the MS1096 GAL4 driver. Salivary glands from L3 larvae expressing mCherry-DMS-his2Av were dissected, fixed and stained with DAPI. As can be seem from Fig. Drosophila tissue is by DMS tag is robust.Lastly we checked if the DMS tag works in Over-expression sometimes leads to the mis-localization of the tagged protein. Reducing expression levels may be done in several ways. For the MT promoter, reducing the amount of copper added by titration may be enough to reduce expression levels for correct localization. Another way to get around this is to switch existing promoters with a weaker substitute.Expression level:Enough time should be left for a suitable amount of oxidation product to form However, bear in mind that overly extended reactions lead to excessive buildup of free radicals, damaging the internal cellular structure.Reaction time:As with any other exogenous protein tagging method, there is a chance that the DMS tags will affect trafficking and localization of the proteins being investigated. Hence, it is advisable to make both N-terminal and C-terminal tagged fusions, then to choose constructs yielding the most natural expression and trafficking. We created vectors for fusion at both ends for this purpose. Typically, the localization of the endogenous protein could be investigated in a separate immunolabelling control experiment under light microscopy to check for proper localization of the fusion protein before starting the EM experiment.Terminal fusion site:A number of factors should be kept in mind while using of vectors described in this report:Drosophila cells for high resolution EM detection of proteins. These vectors are inducible and can be used for cell culture as well as transgenic preparations. We believe that this vector set will prove to be a useful resource not only to the Drosophila community, but also to anyone interested in using Drosophila as a disease model system in general.In conclusion, we constructed a set of vectors for optimized Mini-SOG mediated photo-oxidation in


The results of the thorough analysis are in agreement with the calculated number of graphene layers from Raman spectra C-peak position values and indicate that the graphene samples studied are few-layered.A model consisting of an equation that includes graphene thickness distribution is used to calculate theoretical 002 X-ray diffraction (XRD) peak intensities. An analysis was performed upon graphene samples produced by two different electrochemical procedures: electrolysis in aqueous electrolyte and electrolysis in molten salts, both using a nonstationary current regime. Herein, the model is enhanced by a partitioning of the corresponding 2θ interval, resulting in significantly improved accuracy of the results. The model curves obtained exhibit excellent fitting to the XRD intensities curves of the studied graphene samples. The employed equation parameters make it possible to calculate the  Graphene, the atom thick material that is the 2D building unit of all carbon allotropes , having jth layer region occupancies and jth layer coverages, for each j ≥ 1, allow for the calculation of the average number of layers of the graphene samples. The calculations are compared to the results obtained by other methods and are in accordance with them.As the characterization protocol that usually follows after graphene production is an important activity, the ultimate aim of this study was to define a reliable model and thus provide a method for determining the number of graphene layers and their distribution by XRD data. To date, XRD data have been used by some authors to determine the distribution of graphene layers or their average number –12. ThisLa for the studied samples, provides a better overall picture with regard to their size and thickness. The nomenclature of the samples presented in this work is the following: graphene samples obtained by electrolysis in molten salts are denominated GMSE1, GMSE3 and GMSE4, and graphene samples produced by electrolysis in aqueous electrolyte are denominated GAE1 and GAE2.Having obtained the number of layers, together with the determined mean crystallite size . It was done using the Laue functions model presented by The XRD pattern of each of the samples was analyzed around the 002 peak, with the attention strictly focused on the line shape. Therefore, the fitting was operated in the range of In The simple model includes graphene thickness distribution and certain parameters, providing calculations of XRD intensities of the theoretical curves:F is a structure factor, N is the maximum number of layers, |f(θ)| is an atomic scattering factor which varies from 6.00 to 6.15 eV/atom with incident radiation ranging from 2 to 433 keV, kaj = (4πdj sin θ)/λ, where dj is the lattice spacing between the jth and the (j − 1)th layer, θ is an angle between the incident ray and the scattering planes, λ is the X-ray wavelength, and βj, having a value between 0 and 1, is the occupancy of jth graphene layer.where Bj = 100βj is the occupancy of the jth layer in percent, and Dj = Bj – Bj+1 is the jth-layer coverage in percent, for each j = 0,1,…,N, assuming β0 = 1 and βN+1 = 0, where N is the total number of layers in the studied sample, regardless of the distribution. Thus, the average number n of graphene layers may be calculated by the following formula:Hence, The simple model  is conves is the parameter that represents the share of each simulating curve, having values between 0 and 1, and M is the number of simulating curves. Through where αs, we propose the partitioning of the 2θ interval [a,b) around the 002 peak. , a1 = a, bs = as+1, s = 1,2,…,s − 1, bM = b and   is few-layered, and the average value for the number of graphene layers is calculated as C-peak. Its position, Pos(C)N, is directly related to the number of graphene layers, N, and it varies with N as given by the following The graphene sample GMSE4 has an asymmetrical experimental 002 XRD peak, as shown in 18 N·m−3 is the interlayer coupling, and μ = 7.6 × 10−27 kg·Å−2 is the graphene mass per unit area.where α = 12.8 × 10j-layer region coverages according to the analysis of the XRD 002 peak with the model in NGL = 3.1 for the dominant structure and NGL = 9.57 for the overall structure. The calculated value of La for the sample GMSE4 was 2.85 nm.The C-peak position at 32.46 cm−1, the number of graphene layers for sample GMSE4 is calculated as N = 2.13. Later within this article this graphene sample is analyzed using the enhanced model and that result is closer to the C-peak position method of calculation.According to the Graphene samples GAE1 and GAE2 produced by electrolysis in aqueous solution from two different raw graphite materials, using nonstationary current regime, are analyzed here. Typical TEM micrographs of the graphene sample GAE1 material are shown in C-peak positions for GAE1 and GAE2, respectively.In The widest blue dotted line in NGL = 2.57 for the dominant graphene structure and NGL = 4.25 for the overall graphene structure. According to the C-peak positions at 33.28 cm−1  and I2 = [27,36) as shown in C-peak.The graphene samples produced by electrolysis in molten salts that are considered and discussed using the enhanced model are sample GMSE3 and GMSE4. Considering GMSE3, the partitioning of the interval [17,36), is done in the following way: jth layer occupancy (Bj) and therefore the coverages of j-layer graphene regions (Dj) in percent for each part of the structure on the whole interval provide the analysis and results shown in The red curve in NGL = 3.13 for the dominant graphene structure and NGL = 8.87 for the overall graphene structure, whereas according to the C-peak position at 39.1 cm−1 and N = 3.3. The calculated value of La for the sample GMSE3 was 2.36 nm.The average value for number of graphene layers according to XRD 002 peak analysis according to I1 = [17,26.75) and I2 = [26.75,36) make the partitioning of the interval [17,36). The coverage of each jth layer of GMSE4 is given in Considering the sample GMSE4 and the enhanced model  as shownNGL = 2.14 for the dominant graphene structure, which is about 80% of the whole graphene sample, and NGL = 8.68 for the overall graphene structure. One could notice that the average graphene layers number calculated using the enhanced model , I2 = [20,23.84), I3 = [23.84,24.84), I4 = [24.84,26.52) and I5 = [26.52,35). The calculations and corresponding curves obtained with the enhanced model  = [16,35) already shown in ed model  are showjth layer occupancy (Bj), and therefore the coverages of j-layer graphene regions (Dj) in percent for each part of the structure over the whole interval are summarized in The black curve in NGL = 2.07 for the dominant graphene structure and NGL = 3.06 for the overall graphene structure.The graphene structure is few-layered, as nearly 95% of the overall structure consist of eight layers or less. The average value for number of graphene layers is calculated as j-layer occupancies and coverages of graphene samples. The enhanced model is suggested to be generally used, because graphene sheets that are subject of research may have highly asymmetrical 002 XRD peaks. Such peaks are inconvenient to be analyzed by the simple model . The study was done at temperatures between 400 and 600 °C in molten salt, and 25 °C in aqueous solution. It should be underlined that, during the electrolysis, the cations reduced at the electrode intercalate at the graphite surface and generate a high mechanical stress that causes exfoliation of the cathode. This phenomenon enables the electrochemical synthesis of graphene to be performed. The electrochemical route also offers the possibility for accurate control of various parameters, such as applied voltage, current density, temperature and morphology of starting material. The morphological structures of the obtained graphene samples were investigated by TEM analysis using a FEI Tecnai G2 Spirit TWIN with a LaB6 cathode. XRD spectra were recorded using a PAN-analytical X’Pert Pro diffractometer (Cu Kα radiation). Raman spectra were recorded using LABRAM ARAMIS-HORIBA JOBIN YVON system with 532 nm wavelength incident laser light, hole 250 μm, slit of 250 μm.


Graphene oxide (GO) is hydrophilic and swells significantly when in contact with water. Here, we investigate the change in thickness of multilayer graphene oxide membranes due to intercalation of water, via humidity-controlled observation in an environmental scanning electron microscope (ESEM). The thickness increases reproducibly with increasing relative humidity. Electron energy loss spectroscopy (EELS) reveals the existence of water ice under cryogenic conditions, even in high vacuum environment. Additionally, we demonstrate that freezing then thawing water trapped in the multilayer graphene oxide membrane leads to the opening up of micron-scale inter-lamellar voids due to the expansion of ice crystals. Graphene oxide (GO) is receiving increasing attention due to its dispersibility in water4In particular, the carboxylic acid groups also contribute to proton conductivity in graphene oxide121314171819graphite oxide has been studied in great detail over a much longer timescale2123242618Despite the wealth of recent papers published on graphene oxide, in-situ atomic force microscopyin-situ observation of a multilayer graphene oxide cross section over a range of relative humidities, using environmental scanning electron microscopy. Evidence for the existence of water ice intercalated in the multilayer GO membrane is provided by electron energy loss spectroscopy (EELS), even under high vacuum conditions.Direct microscopic observation of the interaction between GO and water has not been as extensively studied. The hydration of bilayer graphene oxide has been investigated by Free-standing multilayer GO paper was produced by vacuum filtration from water dispersion, followed by drying. A bespoke microscope stage was manufactured, allowing side-on observation of the sample . Figure in-situ ESEM. The thickness was first measured at a fixed point on the sample, which was used as a reference area at different relative humidity, under fixed focus conditions. The relative humidity was increased stepwise from 30% RH to 95% RH, then decreased following the same data points. This cycle was repeated twice. To ensure saturation between thickness measurements, images were taken 120 seconds after each step; response times of the order 10 to 20 seconds are reported in the literature19The effect of humidity on the membrane was measured by nd order fit (R2 = 0.983). The thickness of the multilayer GO membrane increases from 34.5 μm at 30% RH to to 43.5 μm at 95% RH, corresponding a total increase of around 26%. The thickness of bi-layer GO measured by atomic force microscopy has previously been measured to vary from 0.74 nm at 30% RH, to 0.85 nm at 90%RH; an increase of 14.9%The variation in thickness of the multilayer graphene oxide cross-section with relative humidity is plotted in 25Bound water is relatively immobile and is strongly adsorbed to the adjacent GO by hydrogen bonds, forming a surface monolayer. This may be the only state of water present under “dry” conditions. Confined water is more mobile and is free to move in two dimensions. Bulk water behaves like normal water without constraints and is likely to be present at high relative humidity. The non-linear dependence of the thickness on relative humidity may relate to the differences between these different states of water. Specifically in the case of bound water, the graphene oxide sheets are also expected to be more tightly bound. When bulk-type water is present in the interlayer region the interaction between individual graphene oxide sheets should be much weaker, allowing for more facile intercalation of water molecules under high humidity conditions. Step-wise increases in thickness with relative humidity associated with filling of the interlamellar spaces with discreet monolayers of water were not observed as in some previous studiesInterestingly, although a simple linear dependence of thickness on relative humidity might be expected, the thickness increase is more pronounced at higher relative humidity. This behavior is also seen in other studies on graphite oxide23The effect of cryogenically freezing the multilayer GO was also investigated by ESEM. The relative humidity was maintained at 80%, and the sample stage was rapidly cooled from 1 °C to −20 °C. Following this, the multilayer GO sample was quickly heated to 40 °C. Upon thawing, extensive changes in the morphology were observed . CorrugaThe low-loss region of EELS spectra is a direct measure of the dielectric response to external electromagnetic excitation. This was recorded at high vacuum, on a few-layer region of the multilayer graphene oxide membrane sample first at 28 °C, and then after cooling to −160 °C . The sam363738in-situ SEM and in-situ STEM characterization of multilayer graphene oxide (GO) at different temperatures and relative humidities. The thickness increased gradually with increasing relative humidity, and decreased with decreasing relative humidity. The rate of change in thickness was slower at low relative humidity, suggesting stronger interlayer bonding in drier conditions. Freezing and then thawing the membrane results in strong corrugation of the multilayer graphene oxide membrane as well as the introduction of micron-scale void throughout the cross section. EELS analysis of few-layer graphene oxide under cryogenic conditions revealed that water ice is present even after exposure to high vacuum, suggesting that obtaining completely “dry” graphene oxide is extremely challenging. Intercalation of water inside graphene oxide could be a significant advantage in applications such as fuel cell ionomer membranes, where water uptake even at high temperature is required.In conclusion, we performed Multilayer graphene oxide was prepared by vacuum-filtration of GO dispersion , Oxygen (20%); Flake size: 0.5–5 μm; Thickness: 1 atomic layer - at least 60%; Hummers Method) onto PTFE Millipore filters . The retentate was dried at room temperature for 48 hours and then peeled-off the filter, resulting in a freestanding multilayer grapehen oxide paper-like membrane. The cross section for SEM investigation was prepared by shearing a thin strip GO paper using a tensile strength test machine (SHIMPO FGO-C-TV), resulting in a clean fracture. Simply cutting the membrane with a scalpel generally does not result in a clean cross section, due to extensive slipping of the GO sheets.SEM images were acquired using a dual-beam focused ion beam system , equipped with a cold stage and a humidifier. The acceleration voltage was 20 kV. Samples were mounted on sticky-coated copper tape  which was then attached to a bespoke sample stage, allowing the sample edge to be tilted towards the electron gun in order to be able to observe the cross-section. A schematic image of the set-up is shown in in-situ EELS experiment was performed after 1 hour at room temperature and 1 × 10−5 Pa, then after 1 hour at −160 °C.STEM images were acquired using a Cs-corrected STEM , equipped with a liquid nitrogen cryo-holder (JEOL). The acceleration voltage was limited to 80 kV to avoid knock-on damage of the GO specimen. A spectrometer  attached to the microscope was used for EELS analysis. The energy resolution is 0.5 eV at the full-width half-maximum (FWHM) of the elastic peak. The samples were mounted on double folding grids . The How to cite this article: Daio, T. et al.In-Situ ESEM and EELS Observation of Water Uptake and Ice Formation in Multilayer Graphene Oxide. Sci. Rep.5, 11807; doi: 10.1038/srep11807 (2015).


In this report, by combining particle-swarm optimization method with first-principles calculations, we present a detailed study of structural, electronic, mechanical, and dielectric properties of Al2O3 monolayer. We predict that planar Al2O3 monolayer is globally stable with a direct band gap of 5.99 eV and thermal stability up to 1100 K. The stability of this high-κ oxide monolayer can be enhanced by substrates such as graphene, for which the interfacial interaction is found to be weak. The band offsets between the Al2O3 monolayer and graphene are large enough for electronic applications. Our results not only predict a stable high-κ oxide monolayer, but also improve the understanding of interfacial properties between a high-κ dielectric monolayer and two-dimensional material.The miniaturization of future electronic devices requires the knowledge of interfacial properties between two-dimensional channel materials and high- BN11131416181920sp3 covalent bonds. Furthermore, 2D structures based on binary compounds of the group IV or group III–V elements, have been predicted to be stable by first-principles calculations22232423Two-dimensional 2D) materials present exceptional electronic, optical, mechanical, and thermal properties, as well as a high surface/volume ratio, all of which make them promising for applications ranging from electronics to energy storage. The discovery of graphene, a single layer of carbon atoms arranged in planar honeycomb lattices, has stimulated dramatic research interest on other 2D materials in order to realize novel functionalization and also further miniaturization of electronic devices1D materia345782 have been proposed by first-principles calculations2 with desirable reduced band gap can be formed on a rutile TiO2 (011) surface, for which the corresponding atomic structure has been refined by subsequent theoretical studies3132κ dielectric monolayers have also been found. A Y2O3 monolayer with a hexagonal lattice has been deposited on graphene2, Co3O4, and WO3, have been synthesized by rationally employing lamellar reverse micelles methodκ dielectrics based 2D structures. Al2O3 is an excellent electrical insulator, which has been widely used in current electronic devices. Thus, it is highly desired to explore the stability of its 2D form, and understand the related physical properties. In this study, via density-functional theory (DFT) based first-principles calculations, we predict that planar Al2O3 monolayer with a hexagonal lattice is stable. This oxide monolayer is found to be an insulator with a direct gap of 5.99 eV and a dielectric constant of 2.51. It is further found that the interaction between Al2O3 monolayer and graphene is weak, which leads to band offsets larger than 1 eV.More recently, many efforts have been made to realize oxide based crystalline 2D sheets. For example, a stoichiometric silica 2D sheet with bi-layer tetrahedral configuration has been grown using a Ru (0001) substrate as the support282O3 monolayer with the constrained stoichiometric formula of Al2O3. This method has been used to predict a number of 2D materials successfullyThe particle swarm optimization (PSO) method implemented in the CALYPSO372O3 monolayer, α-Al2O3 bulk, and hybrid structures of Al2O3 monolayer on the substrates of graphene and Al (111) was sampled by Γ centered 18 × 18 × 1, 12 × 12 × 4, 6 × 6 × 1, and 9 × 9 × 1 κ-point meshes, respectively. A vacuum layer with 15 Å thickness has been inserted normal to the Al2O3 surface for all slab structures to minimize the interaction between neighboring image surfaces. In order to get an improved electronic structure, the Heyd-Scuseria-Ernzerhof hybrid functionals (HSE06) were used−6 eV and 0.01 eV/Å, respectively. To explore thermal stability of Al2O3 monolayer, ab initio molecular dynamics (MD) simulations were performed with a time step of 1 fs, canonical ensemble (NVT), and Nosé heat bath on the 5 × 5 × 1 supercell. The dynamic stability was studied by calculating the phonon dispersion using density functional perturbation theory implemented in VASP with a higher electronic convergence criterion of 10−8 eV and analyzed by using the PHONOPY codeα-Al2O3 bulk are in good agreement with previous studies and experimental results48First-principle calculations, using DFT based VASP code40422O3 monolayer predicted by the PSO simulation is shown in h-BN monolayer and graphene. This honeycomb structure is a global minimum in the space of all possible 2D arrangements of Al2O3. Then, the predicted Al2O3 monolayer structure was optimized using first-principle calculations. The equilibrium configuration of Al2O3 monolayer can be obtained from the energy minimum in the equation of state curve in 2O3 monolayer with the optimized lattice constant of 5.84 Å and the Al-O bond length of 1.69 Å α-Al2O3 bulk. The contour plot of ELFs for the Al2O3 monolayer and α-Al2O3 bulk are visualized along the Al-O bond plane, as shown in 2O3 bulk, suggesting dominant ionic bonding character. In contrast, the electron density in the Al2O3 monolayer is slightly more delocalized. This indicates that the ionic bonding is still dominant in the Al2O3 monolayer, but it is weaker than that of α-Al2O3 bulk, consistent with the shorter bond length in the Al2O3 monolayer. The enhanced in-plane covalent bonding character can be seen also from the Bader charge analysis2O3 monolayer, less than To investigate the bonding character of the Al2O3 monolayer, its cohesive energy Ec can be calculated by the following equation:The stability of a material is indicated by the related cohesive energy, and a structure with negative cohesive energy is stable or metastable. For Al2O3 monolayer, and EAl and EO are the energy of isolated single Al and O atom, respectively. The calculated cohesive energy of Al2O3 monolayer is −5.97 eV/atom, which is slightly higher than that of the Al2O3 bulk (−6.56 eV/atom), but it is lower than that of recent experimentally confirmed 2D materials such as silicene (−5.16 eV/atom) and germanene (−4.15 eV/atom)192O3 is promising for an experimental realization.where 2O3 monolayer can also be examined from the calculated phonon spectra. As shown in 2O3 monolayer is dynamically stable and can exist as a free standing 2D structure.The structural stability of the Al2O3 monolayer, ab initio molecular dynamics simulation has been conducted at the temperature of 300 K with a time length of 10 ps. A (5 × 5 × 1) supercell of the Al2O3 monolayer is used to minimize constraints induced by periodic boundary condition. The averaged total energy of the monolayer is nearly constant, and the variation of the Al-O bond length is within 0.1 Å with respect to the average value at 300 K during the simulated time period, as shown in 2O3 monolayer is thermally stable at room temperature. Ab initio MD simulations were also carried out at higher temperatures of 800 and 1100 K, respectively, which show that this monolayer is still stable at the temperature of 1100 K . For the deformed state of Al2O3 monolayer, it is assumed that the contribution of bending to the strain energy density is insignificant, thus the vertical weight of elastic constants is zero. For all the deformed configurations, the positions of all atoms were optimized and the related energies were calculated. In this way, for each type of distortion, we could obtain the strain dependent energy. Then, the in-plane Young’s modulus Ys and Poison’s ratio v were calculated from the following relationship: h-BN monolayer and ZnO monolayer were calculated and summarized in 2O3 monolayer is 47.6 N/m, very close to that of ZnO monolayer (~47 N/m), but much smaller than that of graphene (~342 N/m), BN monolayer (~274 N/m), and Al2O3 bulk (~230 GPa). This clearly shows the relative softness of the Al2O3 monolayer. The softness of the Al2O3 monolayer is also reflected by the flat slope of the acoustic branch at the Γ point in the phonon dispersion2O3 monolayer is susceptible to external influence, with greater tendency to form ripples or out-of-plane deformations, as supported by the above MD simulation results , one of the most promising high-κ dielectrics. Thus, we believe that the band gap of the Al2O3 monolayer is large enough to be used as a dielectric material. From the PDOS and partial charge density . The formation of π bonds is believed favorable to stabilize the 2D planar structure, as shown in other 2D structuresAlsity see , we find2O3 monolayer is shown in εxx and εzz, the total dielectric constant ε can be determined by A dielectric material with high dielectric constant is preferred in order to achieve larger capacitance density. The dielectric constant decreases with the decrease of thickness, and thus it is important to study dielectric properties for a dielectric material with one atomic thickness. The calculated dielectric function of the Al2O3 monolayer is determined by the zero energy limit from the real dielectric function, which is about 1.27. With the inclusion of the ionic vibration contribution (~1.24), the overall dielectric constant is about 2.51. This value is much smaller than that of α-Al2O3 bulk (~10.5) due to the reduced thickness, changed bonding character, and also decreased band gap, but comparable to that of SiO2 bulk (~3.9). It is noted that the calculated dielectric constant of α-Al2O3 bulk is consistent with the experiment value (~9.0). From the imaginary part the dielectric function  graphene supercell matches 2O3 monolayer well. Since the Al2O3 monolayer is relatively soft, it was compressed by about 2.88% and placed on graphene supercell. This small strain on the Al2O3 monolayer yields a 0.18 eV increase in the band gap, but does not alter the electronic properties significantly, as shown in the 2O3 monolayer still favors planar structure, and becomes more stable as its energy is lowered by 0.19 eV per unit cell, compared with free standing Al2O3 monolayer.Experimentally, various substrates have been proposed for growing oxide monolayer such as SiO2O3 monolayer on graphene is shown in 2O3 monolayer, β-Si3N4, and g-C3N3 on graphene, and HfO2 on MoS2 monolayer255455562O3 monolayer planes remain planar. The shortest distance between Al2O3 monolayer and graphene is 3.26 Å, indicating weak interaction between them. The calculated adsorption energy is 13.62 meV/Å2, smaller than that of graphene on Al2O3 (0001) surface2O3 monolayer and graphene.The most stable configuration of the Al2O3 monolayer. From the charge density difference projected on graphene plane  and conduction band offset (CBO), respectively, as shown in 2O3 monolayer. Thus, the real VBO and CBO should be larger than the values in current studies.Due to the weak interaction, the charge inhomogeneity in graphene is insignificant with the presence of the Alne plane , we can 2O3 monolayer, thus it is a potential substrate to grow Al2O3 monolayer, similar to the growth of Y2O3 monolayer on graphene2O3 monolayer, the interface between the Al2O3 monolayer and Al (111) surface has been studied also , forming interfacial Al-O bonds with bond length of 1.9 Å. The strong interaction is also confirmed by the large adsorption energy (2.2 eV per Al2O3 unit) and significant charge transfer (see 2O3 monolayer on Al (111), and it can be expected that the 2D growth of Al2O3 monolayer is difficult on Al (111) substrate by a direct thermal oxidation process. Therefore, inert substrates with weak interaction, same surface symmetry, and small lattice mismatch such as graphene are favored to realize the 2D growth of Al2O3 monolayer via sputtering or other advanced deposition techniques.From the above discussions, we can see that graphene has same surface symmetry, small lattice mismatch, and weak interaction with Alsfer see . This st2O3 monolayer with a direct band gap of 5.99 eV and dielectric constant of 2.51. This Al2O3 monolayer can be further stabilized by the support of graphene. For the interface between Al2O3 monolayer and graphene, we find that the interaction between them is weak and band alignments are much larger than 1 eV. Moreover, the presence of the Al2O3 monolayer does not introduce interface states and electron-hole puddles in graphene. Together with high thermal stability, the Al2O3 monolayer might be a potential dielectric for future electronic applications. Due to similar surface chemistry between graphene and other 2D channel materials such as transposition metal dichalcogenide or phosphene, these results might be applicable to the interface between the Al2O3 monolayer and other 2D materials.In conclusion, based on PSO method and first-principles calculations, we find a stable AlHow to cite this article: Song, T. T. et al. The stability of aluminium oxide monolayer and its interface with two-dimensional materials. Sci. Rep.6, 29221; doi: 10.1038/srep29221 (2016).


Hexagonal boron nitride (hBN) is drawing increasing attention as an insulator and substrate material to develop next generation graphene-based electronic devices. In this paper, we investigate the quantum transport in heterostructures consisting of a few atomic layers thick hBN film sandwiched between graphene nanoribbon electrodes. We show a gate-controllable vertical transistor exhibiting strong negative differential resistance (NDR) effect with multiple resonant peaks, which stay pronounced for various device dimensions. We find two distinct mechanisms that are responsible for NDR, depending on the gate and applied biases, in the same device. The origin of first mechanism is a Fabry-Pérot like interference and that of the second mechanism is an in-plane wave vector matching when the Dirac points of the electrodes align. The hBN layers can induce an asymmetry in the current-voltage characteristics which can be further modulated by an applied bias. We find that the electron-phonon scattering suppresses the first mechanism whereas the second mechanism remains relatively unaffected. We also show that the NDR features are tunable by varying device dimensions. The NDR feature with multiple resonant peaks, combined with ultrafast tunneling speed provides prospect for the graphene-hBN-graphene heterostructure in the high-performance electronics. Graphene, a two-dimensional material with unique mechanical, thermal and electronic transport properties3567891011121314NDR in double barrier resonant tunneling diodes (DB-RTD), appears when the quasi-bound levels can no longer enhance the tunneling resonantly19202122242728313334The NDR features in multilayer based devices are to be investigated by exploring current-voltage characteristics as a function of (i) number of hBN layers, (ii) lateral dimensions in determining both the voltage location of NDR peaks and the peak-to-valley ratio, which are essential in the device design, (iii) the role of the asymmetric band offset between hBN and graphene, and (iv) defects and scattering. This, however, necessitates further research to rationalize the underlying physics of the NDR effect and gain insight on how to control its critical properties mentioned above.In this work, we focus on a prototypical multilayer device shown in Next, section 2 defines our method by discussing the underlying Hamiltonians and the methodology for the computation of quantum transport. Section 3 discusses the results including the two underlying mechanisms with the role of electron-phonon scattering included. Section 4 presents the size scaling analysis followed by section 5 concluding the work.heterostructure/multilayer region stacked in AB order . The lattice constant mismatch between hBN and graphene is negligibly small, 1.8%, therefore, we build the device structure with the uniform lattice constant of graphene (2.46Å) only. The system Hamiltonian is constructed using the nearest neighbor tight binding approximation, with the parameters11pz orbitals are considered here; so that the Hamiltonian has the same dimension as the total number of atoms simulated. The effect of number of tunneling hBN layers (Nz), the system width (Nx) and the length of the multilayer stacking region (Ny), where units of Nx and Ny are number of atoms, on the device performance is investigated. The nanostructure thickness is (Nz+2) in units of atomic layers, which includes the two monolayer graphene sheets at the ends.A prototypical heterostructure consists of two semi-infinitely long monolayer armchair-edged graphene nanoribbon (AGNR) electrodes sandwiching an ultra-thin hBN film, with a vertically applied external gate electric field as shown in U = −eVb, where Vb is the applied bias, and the electrostatic potential of the top graphene layer remains zero. The electrostatic potential at each of the sandwiched hBN layers are determined by linearly increasing/decreasing the potential from top to the bottom graphene layer, because the c-axis (out of plane) conductivity of hBN is orders of magnitude smaller than the in-plane conductivity of graphene. The chemical potential of contacts are controlled by bias voltage, namely μB = −eVb and μT = 0 for bottom and top graphene leads respectively. The gate voltage is modeled by shifting the electrostatic potential at the bottom electrode by ΔU = −0.01 eVg, where Vg is the gate voltage. We choose Nx equal to 3n+2, where n is an arbitrary positive integer37The bias across the heterostructure is applied by rigidly shifting the electrostatic potential of the bottom graphene electrode by the amount equal to the applied bias as the metallic graphene layers have much higher conductivity than hBN. The electrostatic potential energy of the bottom layer is E is the electrons energy, I denotes the identity matrix, H is the system Hamiltonian matrix, and i can be calculated subsequently byWe simulate the transport properties of the device by using the state of the art Green’s function (NEGF) formalismf(E) is the Fermi function and μL/R represent the Fermi level of the left (top) and right (bottom) graphene monolayer electrode. In Nx = 200, Ny = 32, and with three hBN layers Nz = 3, at zero bias. The bandgap of hBN is found to be around 4.72 eV, and the valence band offset between hBN and graphene is around 1.38 eV, which is consistent with the prior workThe transmission coefficient is then calculated using the expression,Traditionally, the recursive Green’s function (RGF) approach is applied to solve for the retarded Green’s function. Here, an algorithm named HSC-extension is developed, which is more efficient and is based on the nested dissection method, so that the requisite large scale systems can be simulatedNx = 62 (7.6 nm), stacking length Ny = 32 (6.8 nm) and three hBN layers (1.4 nm) serving as the tunneling barrier. First we consider the highlighted curve with Vg = 0, in which case two NDR peaks emerge at Vb = 0.3 V and 0.66 V, respectively. We attribute the formation of these multiple NDR peaks to the Fabry-Pérot like interference in the multilayer region (mechanism 1), as rationalized below.g and DOShBN) at Vb = 0.3 V, 0.46 V and 0.66 V, corresponding to the first peak, the first valley and the second peak in the current-voltage characteristics. In the DOSg curves . The transmission and DOSg show a strong Fabry-Pérot like resonant feature in the low energy window. The semi-infinite top and bottom AGNRs couple with hBN at the central heterostructure (multilayer) region. The potential discontinuity caused by the interaction between the hBN cut-ends and the graphene layers create a resonant cavity in the overlapping region at both the top and bottom graphene layer. When electrons transport across the boundaries between graphene monolayer and hBN multilayer regions, partial reflections occur at the interfaces. As a result, the transmission is oscillatory with peaks and valleys corresponding to constructive and destructive interferences.To understand the multiple NDR peaks, we calculate the transmission and the average density of states  at E = −0.3 eV in Vb < 0.18 V), we find that this transmission peak P is enhanced, resulting in the increase of current with applied bias. The resonant tunneling occurs when the constructive quantum interference assists the tunneling of electrons from the top to bottom electrodes at specific energies. When the bias is further increased (until 0.46 V), the transmission peak P is reduced due to destructive interference despite the fact that the energy window for carrying current enlarges. This transmission reduction begins to dominate after Vb = 0.3 V, which induces a drop in current. At Vb = 0.46 V, there is a large suppression of transmission within the bias window, which creates a large tunneling gap, leading to the current valley as reflected in the highlighted curve of Vb = 0.66 V due to the constructive interference.The current is determined from the area enveloped by the transmission curve in the energy window bounded by the Fermi levels of two electrodes, E = −0.3 eV (μT), while a symmetric peak at E = 0 eV (μB) is clearly absent. This is due to the fact that the presence of hBN layers break the symmetry. We could understand this from DOShBN plot at Vb = 0.3 V (hBN curve), which shows a peak near E = −0.3 eV but a valley at E = 0 eV. This means that electrons at E = 0 eV see a stronger barrier when tunneling between AGNR layers, and suggests the breaking of the π−π* symmetry. This argument is tested by considering a symmetric tunnel barrier, where such an asymmetry in transmission does not exist. In T) are observed. This significant tunneling enhancement results from the energy level alignment between the subbands of top and bottom graphene electrodes, as reflected in the corresponding DOSg features.An interesting feature of Vg). Vg ranging from −45 V to + 45 V for two devices with different sizes. Take the current-voltage curve at Vg = −45V as an example; At Vb = 0, the negative gate voltage shifts the energy of Dirac point in the bottom AGNR electrode to U = 0.45 eV at equilibrium, while preserving the chemical potentials from two contacts at μB = μT = 0. At Vb = 0.45 V (see mechanism 2) induces the resonant transmission and results in the large current peaks marked by solid arrows in Vb = −0.01Vg) based on mechanism 2 only. This occurs when the strength of mechanism 2 is comparable to that of mechanism 1, when the voltage at which the peak current occurs is influenced by the Fabry-Pérot like interference. The superposition of mechanisms 1 and 2 leads to the current peak displacement, which is larger at low gate voltage .We next discuss the second mechanism that leads to single intense NDR peak by investigating the operational behavior of the heterostructure in the presence of an external gate voltage  dimensions which defines the overlap area between hBN and graphene layers and the z-direction (number of hBN layers), is performed in this section. However, we do not consider the electron-phonon scattering effects during this analysis as they do not significantly alter the outcomes of the analysis.System dimensions are the key ingredients in engineering the device performance. In this particular multilayer heterostructure, for instance, the device width determines the number of subbands in ANGR electrodes and the heterostructure length determines the length of interference region. Based on the two distinct mechanisms responsible for the multiple NDR peaks, it is intuitive that the device dimensions have significant and non-trivial influence on the NDR features rather than simply tuning the current magnitude by following quantum mechanical rules or Ohm’s law. In order to comprehend such influences, the scaling analysis of the device dimensions, namely the lateral  is varied from 1 layer (0.6 nm) to 5 layers (2 nm), while both Nx and Ny are fixed. The magnitudes of current are scaled by a multiplicative factor to present results on the same plot for different values of Nz. The transmission versus energy , the density of subbands for the monolayer AGNR electrodes and the heterostructure region depends on the graphene nanoribbon width, i.e. the energy intervals between subbands for the structure with Nx = 200 are about three times smaller than that for the structure with Nx = 62. Therefore, a larger number of subbands contribute to current under lower biases, resulting in initial increase in current with Nx, as seen in Vb = 0.45 V for different Nx in μB and μT grows with the width of the AGNR electrode  to 64 (13.6 nm), the number of transmission peaks increase as shown in Vb =  0.38 V, 0.8 V for Ny = 32, which shifts to lower Vb i.e. at 0.2 V, 0.4 V respectively, when Ny = 64. This is because the resonant transmission appears at various energies, which vary inversely proportionally with the length of the interference cavity Ny. Experiments where the overlap between two graphene nanoribbons are altered should be able to reveal the differences in oscillations of I-V characteristics as a function of Ny. We note that experiments with changing overlap dimensions have been performed in carbon nanotubes before44The length of the central multilayer region determines the number of incident carriers, and also characterizes the size of the Fabry-Pérot like interference cavity. For mechanism 1, when the heterostructure length Nz = 1), electrons have high tunneling probabilities and thus the current is mainly limited by the number of modes incident within the energy window. Graphene layer has low DOS near Dirac point, yielding the saturation of peak current at large. It is also observed that for larger Nz , the peak current increases with Ny rapidly without saturation. This is consistent with our previous discussion since a thicker hBN tunneling barrier greatly suppresses the overall tunneling transport probability and therefore the peak current magnitude is a strong function of the number of carriers in graphene.With an ultrathin tunneling barrier  of the top and bottom graphene electrodes align, which leads to a second mechanism for resonant tunneling. Both mechanisms respond to gate voltage distinctly. Gate voltage only controls the locations of NDR peaks from mechanism 1 while can tune both PVR and locations of NDR peaks due to mechanism 2. In the presence of electron-phonon scattering decoherence, mechanism 1 is more intensively suppressed compared to mechanism 2, which may be relevant to the disappearance of mechanism 1 in the experiments.Nx), the multiple current peaks preserve but with decreasing PVR values for both mechanisms. (3) For mechanism 1, the bias voltages at which multiple current peaks, occur depend on the length, and the number of peaks increase with length. In contrast to this, the location of the single peak from mechanism 2 is independent of the length. We believe that the negative differential resistance’s sensitivity to the system dimensions will provide additional insights for future theoretical and experimental investigations.Size scaling analysis provides insight into the device physics that determines the number of NDR peaks, the variation of peak current and PVR value with change in device dimensions: (1) The hBN thickness exponentially controls the magnitude of current without significantly affecting the NDR features. (2) For devices with larger widths .


The growth scheme offers metal-free synthesis at low temperature, grain-size customization, large-area uniformity of electrical properties, single-step preparation of graphene/dielectric structures, and readily detachable graphene. We quantify based on thermodynamic principles the activation energies associated with graphene nucleation/growth on γ-Al2O3, verifying the low physical and chemical barriers. Importantly, we derive a universal equation governing the adsorption-based synthesis of graphene over a wide range of temperatures in both catalytic and spontaneous growth regimes. Experimental results support the equation, highlighting the catalytic function of γ-Al2O3 at low temperatures. The synthesized graphene is manually incorporated as a ‘graphene sticker’ into an ultrafast mode-locked laser.The possibilities offered by catalytic γ-Al Owing to its excellent electrical and optical characteristics, graphene has attracted much research attention over the past decade122141517182 substrate.) Recently, the use of catalytic MgO202Transfer-free processes have drawn particular interest because the transfer of large graphene sample synthesized on a metal catalyst generally leads to contamination or the formation of defects8910122O3 catalyst as a novel substrate for the metal-free direct growth of graphene layers at low temperatures. We elucidate the formation mechanism of graphene on γ-Al2O3 with both numerical simulations and experiments, with concordant results obtained. We derive an equation applicable universally for the adsorption-based synthesis of graphene over a wide range of temperatures, which covers both low-temperature catalytic growth and high-temperature spontaneous growth on diverse substrates, including metal catalysts. We show herein that this equation accurately reproduces experimental results. To verify the successful formation of graphene crystals2In this report, we explore γ-Al2O3 substrates is advantageous in a number of regards over conventionally prepared graphene; these include (i) the low-temperature synthesis afforded by γ-Al2O3 catalysis, (ii) the excellent and very uniform electrical properties provided by the ultrahigh-quality crystals that form because of the negligible activation energies associated with carbon diffusion on the substrate and with the surface-regulated crystal nucleation and growth, (iii) the control offered over the thickness of the graphene layer and of the grain size therein—from nano- to micrograins, which is closely related to band gap opening, (iv) the fact that the formation mechanism is demonstrated here both numerically and experimentally, and (v) the ready detachability of the graphene produced and its very low adsorption energy with respect to the substrate, which guarantee the complete transfer of intact layers. Furthermore, the graphene grown can be used with the γ-Al2O3 substrate—an ideal gate dielectric with a high dielectric constant (κ) of 7.920220−4A·cm−2)25Graphene synthesized on γ-Al2O3 from the additional sacrificial layer deposited on the arbitrary substrate to form a graphene/high-κ dielectric. The graphene can be submitted to additional treatments with the assistance of supporting substructures to obtain ultrathin, transparent sheets and a highly bendable Al2O3 substrate. In particular, graphene stickers, as shown in 2O3 as a substrate for growing graphene, we analyzed the growth mechanism theoretically and validated the resulting equation experimentally. An initially amorphous Al2O3 layer was prepared by atomic layer deposition (ALD). This spontaneously transforms into γ-phase during the first stage of graphene growth, and this phase is retained as the substrate is recycled after growing and detaching the graphene. (The specific conditions used for these steps are described in the methods section)To evaluate the versatility of γ-Al2O3 substrate formed was used for the growth of graphene using CVD at different CH4 partial pressures (pCH4), growth temperatures (T), and durations (t), as shown in The γ-Al2O3 substrate and the growth characteristics of graphene, graphene layers were grown at temperatures ranging from 600 °C to 1050 °C. Regardless of the activity of the substrate, graphene always grows under CVD conditions at temperatures above 950 °C via the spontaneous dehydrogenation of CH42O3 can therefore be proved experimentally by demonstrating graphene growth at temperatures below 950 °C. According to previous reports284 is only adsorbed at tricoordinated AlIII sites on the surface of γ-Al2O3. Furthermore, these sites show catalytic activity for dehydrogenation at temperatures as low as 100 °C282O3 substrates. This scheme contains a number of activation barriers with many factors, which are described below.To confirm the catalytic activity of the γ-AlIII sites by dissociative adsorption of a CH4 molecule. The overall activation energy barrier from the CH4 molecule to the generation of a C adatom involves the dissociative adsorption energy, Ead. The generated adatom then diffuses and becomes anchored onto sites that are more or less favorable according to their associated surface diffusion barrier, Ed. Additional C adatoms may come into contact with the anchored C adatom to form linear and ring shaped carbon clusters, as described by the attachment barrier, Eatt. Alternatively, the C adatom may desorb from the γ-Al2O3 substrate immediately after its generation or as it diffuses across the surface according to the desorption energy, Edes. The activation energy for the detachment of a C atom from the perimeter of the graphene nucleus is the detachment barrier, Edet.A carbon adatom can be generated at Ala) via Arrhenius plots, as shown in a includes all contributions from Ead, Ed, Eatt, and Edes, and the complex relationship between these factors. Measuring Ea provides an experimental parameter against which to validate our theoretical model, and provides insights into the formation and growth of the graphene nuclei.After growing graphene at various temperatures, we measured the overall activation barrier for growth  reveals two distinct growth regimes. The gentle slope in c = 0.21 eV, represents Ea in the catalytic growth regime, while the steeper slope reflects the non-catalytic regime with Es = 2.10 eV, in which growth occurs through site independent spontaneous dehydrogenation of CH4. The specific procedure used to obtain these values is described in To sketch out the overall growth of graphene nuclei on the γ-Alc and Es should be given by Equations Based on these theoretical considerations, Ead = 0.88 eV, Eatt = 0.21 eV, Ed = ~0 eV, and ln(q0/N0) = 1.87 eV, for which N0 = 26 / 0.76 nm−2 and q0 = 4 / 0.76 nm−2 represent the total density of adsorption sites respectively on the surface of the substrate and for CH4 on γ-Al2O3; i.e., there are 26 atoms in total and 4 AlIII atoms on each γ-Al2O3 unit cell (with an area of 0.76 nm2)In the above equation, Ec ~ 0.22 eV and Es ~ 2.09 eV, as shown in c = 0.21 eV and Es = 2.10 eV) shown in Inserting these values into the above equations leads to E2O3, Al4C3 forms very slowly and only above 1600 °C, while Al2OC, which is the first metastable product in the formation of Al4C3, forms only at temperatures above 1427 °C2O3 is therefore negligible under the CVD conditions employed here, such that the formation and growth of graphene nuclei on γ-Al2O3 should follow a surface adsorption route similar to that which occurs on Cu. Two-dimensional crystal growth is similar to the nucleation and enlargement of crystals synthesized by physical deposition. We therefore adapted the model for the latter, derived by Robinson and RobinsRuoff and coworkers have shown that graphene synthesis on transition metals involves surface adsorption on Cu but surface segregation or precipitation on Ni due to the differing solubility of C in the two 31des and Ed, at a given growth temperature. The saturation densities in the high-temperature and catalytic growth regimes are derived from the Equation In the above equation, η is used as a determinant for the growth regime, β is an undetermined dimensionless coefficient, C is the number of effective pair-formation sites neighboring each adatom, and the other factors are described in the SI. The determinant is highly dependent on the validity of the values used for the two activation barriers, Ea in the high temperature growth regime does not match the one measured experimentally. We therefore obtained a rough estimate of the transition temperature (Tc) from the intersection of the lines corresponding to Equations c ≈ 4800 K  is given by the following equation,s) are defined as follows:and the activation barriers in the steeper regime governed by spontaneous dehydrogenation  model37d ≈ 0 eV). This contrasts with the values obtained for Ag and Ni,  but is comparable to the barrier on Cu (0.07 eV)a site (C-C-Oa) is the most stable reaction, with a relative energy of 6.06 eV per C atom. No surface diffusion barriers were evidenced in this process, and since the formation of a bridging-metal linear Cn-Oa structure (n is the number of C atoms) is similar to the formation of graphene nuclei on α-Al2O3d for the latter is negligible.To obtain Eatt. A value of 0.21 eV was obtained using a simple model in which the growth of graphene islands is governed by the edge controlled kinetics of the attachment and detachment of C adatoms, as described on page S26 in the The enlargement of graphene nuclei proceeds according to Ed and C solubility, Ni appears at first glance to be the most favorable substrate. However, these two terms can lead to the growth of graphene on Ni substrates both by segregation and precipitation.ad, while as mentioned above, Eatt governs the enlargement of the graphene nuclei. Therefore, these two activation barriers determine the lowest possible growth temperature. For the theoretical calculation of Ec, Kim et al.att of 2 eV for Cu, based on growth experiments performed on Ruatt att of 0.2 eV yields Ec = 1.1 eV, demonstrating that this equation, originally derived for metal oxides, is also valid for metal catalysts. One also notes that the DFT-calculated value for Eatt  is similar to the one measured here (0.21 eV). In this context, Ead has a significant impact on the catalytic performance of the substrates. Since Eads is similar for γ-Al2O3 and Ni, the growth temperature of graphene on γ-Al2O3 should be comparable to that on Nid determines the homogeneity of the graphene layer grown on the substrate, and since Ed is the lowest in γ-Al2O3, this should be the most favorable of these three substrates for the formation of homogeneous graphene. A further discussion of C solubilities and a quantitative comparison of the different substrates may be found on page S28 of the The supply of C adatoms is governed by EIG/ISi), and of the 2D peak to the G peak (I2D/IG), as a function of the growth temperature. The latter ratio reports on the number of graphene layers formed, with a values of ~0.5 at an excitation wavelength of 532 nm indicating the presence of bilayers. IG/ISi reports on the average area of the graphene grains. The variation of this intensity ratio with the growth temperature follows two distinct slopes in Atomic force microscopy (AFM) images of graphene synthesized for 1 h at 600 °C, 800 °C, and 1050 °C, are respectively shown in 2O3 substrate and evaluate the quality of the graphene. High-resolution XPS profiles were acquired in the C 1s We also analyzed our graphene samples by using X-ray photoelectron spectroscopy (XPS) and X-ray diffraction (XRD) to identify the crystalline phase of the AlC 1s see  regions s) of the graphene samples as a function of the H2 flow rate used during CVD (under a constant 850 sccm flow of CH4). The linear increase of Rs with the H2 flow observed here can be expressed by the following equation.2 is the flow from the mass flow controller (sccm).H2 flow rate was also investigated by Raman spectroscopy, by looking at its influence on the ID/IG ratio , a strong argument in favor of the use of γ-Al2O3 as a growth substrate. It is noteworthy moreover that the Rs standard deviation is less than 1% in all the samples prepared with H2 flows up to 200 sccm  and n is the refractive index of the Al2O3 substrate (1.77 at 550 nm). According to this equation, a single layer of graphene grown on Al2O3 absorbs ~1.66% of the incident light. As shown in opt at 550 nm is 93.8%, which matches the value (93.76%) predicted using Equation 2O3/Quartz wafer/Al2O3 substratein which ZAs a practical application of our readily detachable graphene layers, we incorporated one of these into an ultrafast mode-locked laser22O3 as a substrate for the highly efficient formation of graphene has been explored and the entire formation mechanism has been elucidated using both numerical simulations and experiments. This synthesis route is effective at low temperatures and without metal, and allows grain size customization and the preparation in a single step of graphene/dielectric layer structures. Moreover, the graphene produced in this way is uniform over large areas in terms of its electrical properties and is readily detachable.In summary, the use of catalytic γ-Al2O3 substrate ensure the synthesis of high quality graphene. Finally, we derived a universal equation, which describes the adsorption-based synthesis of graphene over a wide temperature range  and on a number of different substrates, including metal catalysts. The experimental results obtained in this study support the proposed equation.We evaluated theoretically the activation energies associated with all the stages of graphene nucleation and growth, confirming that the low energy barriers for the surface diffusion of C adatoms and for graphene nucleation/growth on the γ-AlTo demonstrate the potential practical applications of this synthesis route, we manually transferred one of the ‘graphene stickers’ prepared in this way to fabricate an ultrafast mode-locked laser.2O3 substrates (50 nm thick) were synthesized via CVD for the growth of graphene on amorphous ALD Al2O3 substrate with 850 sccm of CH4 and 50 sccm of H2 at 1050 °C. In order to get the γ-Al2O3 substrate, the graphene grown was detached by using a polyimide filmThe γ-Al4 and 50 sccm of H2, with different growth temperatures and durations.Except for the optimization of the gas flow rates, all the graphene samples were synthesized using 850 sccm of CH2O3 (50 nm thick) was synthesized via ALD onto a quartz wafer coated on its backside with a polymer film. The backside was also coated with Al2O3 using the same method. Graphene was then synthesized on both sides of the Al2O3/wafer quartz/Al2O3 substrate for 15 min at 1050 °C.Al2O3 substrates. A D-shaped optical fiber was fabricated by polishing one side of a conventional single-mode fiber (SMF) fixed with epoxy on a slide glassGraphene stickers were prepared by detaching spin-coated polyimide together with the graphene from γ-Al−1. The XPS profiles were acquired using a PHI 5000 VersaProbe (Ulvac-PHI) system at a base pressure of 6.7 × 10−8 Pa using a monochromated Al Ka (1486.6 eV) anode  with a spot size of 100 μm × 100 μm. The transmittance data were recorded on a Cary 5000 (Varian) spectrometer from 175 nm to 3300 nm at a scan rate of 600 nm·min−1 at a resolution of 1.0 nm. The optical spectrum, its characteristics, and those of the pulse waveform, were respectively measured using an autocorrelator , an optical spectrum analyzer , and an oscilloscope .Atomic force micrographs were acquired in non-contact mode with a ppp-NCHR 5M probe (Nanosensors) attached to a XE-100 microscope (Park Systems). The Raman spectra were acquired using a Renishaw In-Via system with a 532 nm excitation laser. The XRD profiles were obtained using a Dmax2500/PC (Rigaku) spectrometer operated at 40 kV, 200 mA, and 8 kW using a Cu target (1.5406 Å) at a scan rate of 2° min2O3 was carried out following the method proposed by Digne, et al.et al.2O3 slab with eight layers was reconstructed after having been cut to a size of Calculations were performed using the Vienna ab initio Simulation Package2O3 surface was defined as follows.The adsorption energy of a C atom on the AlThe energy of one C atom was calculated in a 20 Å × 20 Å × 20 Å vacuum space. A CI-NEB calculation was performed to calculate the migration barrier energy of the attached carbon37III, Oa, Ob, and Oc sites. The AlIII site, which has three O neighbors, is reported to act as a catalytic site for the dissociation of CH428a, Ob, and Oc sites are defined as O atoms having bonds with AlIII and AlV, with AlIII and left-AlIV (AlIV (l)), and with AlIII and right-AlIV (AlIV (r)), respectively.C atom adsorption was tested on top of the AlHow to cite this article: Park, J. et al. Growth, Quantitative Growth Analysis, and Applications of Graphene on γ-Al2O3 catalyst. Sci. Rep. 5, 11839; doi: 10.1038/srep11839 (2015).


Ralstonia solanacearum in microcosms and in tomato plant rhizosphere. We find that bipartite resource competition networks are better predictors of invasion resistance compared with resident community diversity. Specifically, communities with a combination of stabilizing configurations (low nestedness and high connectance), and a clear niche overlap with the pathogen, reduce pathogen invasion success, constrain pathogen growth within invaded communities and have lower levels of diseased plants in greenhouse experiments. Bacterial resource competition network characteristics can thus be important in explaining positive diversity–invasion resistance relationships in bacterial rhizosphere communities.Host-associated bacterial communities can function as an important line of defence against pathogens in animals and plants. Empirical evidence and theoretical predictions suggest that species-rich communities are more resistant to pathogen invasions. Yet, the underlying mechanisms are unclear. Here, we experimentally test how the underlying resource competition networks of resident bacterial communities affect invasion resistance to the plant pathogen  Species-rich communities are thought to be more resistant to pathogen invasion. Here, Wei et al. show that the resource competition network architecture of root-associated bacterial communities are better predictors of plant pathogen invasion resistance than measures of community diversity. Bacterial communities cover virtually all host surfaces from skin, gut and mucosa of animals1567989913141518High diversity might increase community invasion resistance due to interactive effects on community stability2223222627Ralstonia solanacearum, the causative agent of bacterial wilt capable of infecting over 200 different plant species across 50 different familiesR. solanacearum pathogen must first invade the resident bacterial communities and reach a threshold density to become virulentHere we directly examined the distribution of trophic links as underlying mechanisms to predict invasion resistance of plant root-associated bacterial communities against an invading pathogen and the subsequent reduction of disease incidence. We focused on the important soil-borne bacterial pathogen Ralstonia spp. speciesResident bacterial communities were constructed by using five, phylogenetically related but non-virulent, Three different network variables were used to describe (1) similarity in resource consumption between the resident community and the invader (niche overlap) and (2) the intensity of resource competition within resident communities (connectance and nestedness). In our study, niche overlap describes the ecological similarity between the invader and the resident community respective to their resource use. High niche overlap between the resident community and the invader is thus likely to be a decisive factor affecting invasion success3422To test these hypotheses, we conducted replicated invasion experiments in laboratory microcosms (in 96-well microtiter plates) and in the tomato plant soil (rhizosphere) to link resident community composition, invasion resistance and spread of bacterial wilt plant disease. Our results show that bacterial resource competition networks are better at predicting invasion resistance than community diversity. Specifically, resident communities with stabilizing configurations (low nestedness and high connectance), and a clear niche overlap with the pathogen, reduce pathogen invasion success very efficiently leading to lowest levels of bacterial wilt plant disease. Bacterial resource competition network characteristics can thus be important in explaining positive diversity–invasion resistance relationships in bacterial rhizosphere communities.R2=0.11, the effect of niche overlap non-significant, R2=0.46, Increasing resident community diversity reduced pathogen invasion success, defined as the portability of successful invasion . At the Together these results suggest that the characteristics of bacterial resource competition networks could partially explain why more diverse communities were often resistant to pathogen invasions: while nestedness and connectance were important for predicting pathogen invasion probability, high niche overlap was the best predictor for subsequent pathogen growth within successfully invaded resident communities.Ralstonia infection, which correlates with pathogen density in the rhizosphere and thus with invasion successR2=0.43, R2=0.75, R2=0.73, R2=0.75, The proportion of wilted plants  to describe the directed dependencies among diversity and different network variables. We first concentrated on pathogen invasion success in microtitre plate invasions assays. Only high community connectance had direct negative effect on pathogen invasion success . The effIn conclusion, network variables were better predictors of resident community invasion resistance in microcosm experiments compared with diversity. However, this pattern was altered in the rhizosphere invasion experiments, where the mix of both indirect and direct effects of diversity and network variables best explained the pathogen invasion success and subsequent spread of tomato bacterial wilt disease.R. solanacearum. Biodiversity of microbial communities is increasingly recognized to constrain invasion by pathogens9Here we show that simple bipartite resource competition networksWe hypothesized that pathogen invasion success should decrease with increasing niche overlap between the resident communities and invading pathogen due to intensified resource competition. While niche overlap had no effect on pathogen invasion probability in microcosm experiments, it constrained subsequent pathogen multiplication in successfully invaded resident communities. This result is in line with previous studies reporting that high catabolic similarity between the rhizosphere community and the invading pathogen reduces the community invasibilityHigh connectance within rhizosphere communities could decrease pathogen invasion success if it leads to generally more efficient consumption of resources, and hence increased competition91137R. solanacearum densities in rhizosphereLastly, we predicted that low nestedness could increase resident community invasion resistance due to less intense resource competition among generalist and specialist members of resident communities. We found that highly nested resident communities were more susceptible to pathogen invasion and subsequent spread of bacterial wilt plant disease in the tomato plant rhizosphere. Nested resource competition patterns could destabilize rhizosphere communities because specialist species need to compete for a subset of the resources used by generalists2542Interestingly, diversity had direct positive effects on rhizosphere community invasion resistance in the tomato plant soil, which was not explained by resource competition network characteristics. There are multiple non-exclusive explanations for this. First, it is likely that some other factors in addition to resource competition patterns were important for resident community and pathogen fitness in the soil. For example, differences in species ability to colonize plant roots could have played significant role for the establishment of protective rhizosphere communitiesRalstonia species that were closely related with the pathogen. As a result, resident community bacterial diversity could have different effect on invasion resistance depending on the genetic distance between the resident bacterial community and the invading pathogen. Further, our model focused only on resource-mediated competition. In a natural system, increasing bacterial diversity could also increase the strength of antagonistic interactions, which could potentially make communities more susceptible to pathogen invasionR. solanacearum pathogen can rapidly evolve respective to its resource consumption patterns53Albeit being effective in demonstrating causal relationships between resident community interaction network structure, invasion resistance and subsequent disease spread in the soil, our simplified approach has some caveats that might lead to different invasion resistance patterns in more complex natural systems. Firstly, our diversity manipulation included only Soil-borne plant pathogens remain difficult to control because their populations are variable in time and space, and because they can often overcome plant resistance via evolution5R. solanacearum QL-Rs1115 (GenBank accession GU390462) tagged with the pYC12-mCherry plasmid as an invading bacterial pathogenR. solanacearum is a soil-borne, Gram-negative bacterium that invades plant roots and multiplies in the cortical tissue before invading the xylemWe used Ralstonia spp. strains to construct model resident bacterial communities that were exposed to pathogen invasion. All resident community bacterial strains were isolated from the tomato rhizosphere and first grown on South Africa semi selective medium (SMSA-E)Ralstonia colonies were identified on the basis of 16S rRNA gene sequence  of 0.1 and grown in microtitre plates in 150 μl OS minimal medium600>0.05 were scored as positive growth on given substrate. We then used these single-species and one-resource interactions to determine resource consumption patterns (1) between the different members of resident communities and (2) between different resident communities and the invading pathogen. We first defined niche overlap between resident communities and the invading pathogen as the proportion of resources used by the pathogen and by at least one member of the given resident community2627C=L/S2, where L denotes for links between species  and S denotes for species richness of the community. Nestedness describes the trophic interactions between generalist and specialist resource consumers. In highly nested networks, generalist species have many links, which are shared by specialist species that have only few links. Mathematically, nestedness was estimated by the system's ‘temperature' via binary matrixes in three steps by computing first an isocline of perfect order, reorganizing the matrix by permuting rows and columns in the way that maximizes its nestedness and comparing its normalized distance to the isoclineWe used bacterial resource consumption patterns to determine indirect resource competition networks (1) between different members of resident communities and (2) between different resident communities and the invading pathogen. To this end, we first characterized the resource consumption pattern of each bacterial strain individually in single-species monocultures on 48 different single carbon resources representative of tomato root exudates. Briefly, overnight cultures were adjusted to an optical density OD0 of 0.1 −1, peptone 5.0 g l−1, yeast extract 0.5 g l−1, beef extract 3.0 g l−1, pH 7.0) on a shaker at 170 r.p.m., 30 °C for 12 h, after which 31 resident communities were constructed with a starting density of 107 cells per ml. All resident communities were inoculated to 20 different resources environments , each of which were composed of OS minimal medium supplemented with a random mixture of 20 carbons selected from the total pool of 48 resources (R. solanacearum QL-Rs1115 strain (105 cells per ml) or grown alone in the absence of pathogen in 96 wells microtitre plates (200 μl per well) at 30 °C with agitation. Resident community growth was recorded after 48 h on the basis of optical density (OD600) and pathogen growth on the basis of the mCherry fluorescence signal . The invasion process was broken into two steps. First, the probability of successful invasion was measured as a binary variable for each resident community resource environment combination: invasion was scored as successful if the fluorescence signal was higher, and unsuccessful if it was lower, than the background signal of the corresponding control treatment. Second, we quantified the pathogen invasion success within successfully invaded resident communities as pathogen density based on the level of fluorescence signal  were germinated on water-agar plates for three days before sowing into seedling plates containing Cobalt -60-sterilized seedling substrate . Tomato plants at the three-leaf stage (11 days after sowing) were transplanted to seedling trays (8 CFU per g soil)6 CFU per g soil). Tomato plants were grown for 42 days after transplantation in a greenhouse with natural temperature variation ranging from 25 to 35 °C and watered with sterile water regularly. Note that the plants from individual single seedling plates were not considered as independent replicates, but instead the number of wilted plants per seedling plate was used as a disease index. Seedling plates were arranged in randomized order and rearranged randomly every 2 days. The number of wilted plants per seedling plate was recorded at daily basis after 17th day post transplantation (no symptoms were observed before day 17). As we were unable to quantify available carbon resources in the rhizosphere directly, we made the assumption that all 48 resources used to characterize bacterial resource consumption patterns were available in the rhizosphere.The spread of periment . As diseng trays  containi−1) and the asymptotic disease prevalence (% of wilted plants); later referred to as early, intermediate and late stages of infection, respectively. Curves were fitted individually for each tray—an approach very similar to survival analysis—and the resulting variables used as dependent variables in independent GLMs, weighted by –log10(SE) of the parameter estimates to account for the quality of the curve fitting. Due to potential correlation between connectance and nestedness, sequential analysis was used to uncover the most parsimonious GLM's. To this end, we used stepwise model selection using the Akaike information criteria (AIC) to select the model with best explanatory power (step function in R). We used both a backward elimination  and forward-selection model (from simple to more complex) to avoid selecting a local AIC minimumPathogen invasion pattern in microcosm experiment was analysed with GLM assuming binomial data distribution for invasion success analysis and lognormal data distribution for invader density increase analysis. For greenhouse invasions experiments, disease spread over time was assessed as a logistic growth curve spanning the percentage of wilted plants as a function of time during whole duration of the experiment. The curves were fitted individually for each tray, in an approach very similar to mortality curves. This fit produced three variables: the lag phase (days after pathogen addition) before disease onset, the intrinsic increase of wilted plants .Supplementary Figure 1, Supplementary Table 1-4 and Supplementary References