Graphene Nanobubbles Produced by Water Splitting - Nano Letters

Apr 10, 2017 - Although this process can also lead to the formation of gaseous surface nanobubbles on top of the substrate, the two types of bubbles c...
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Graphene Nanobubbles Produced by Water Splitting Hongjie An,*,† Beng Hau Tan,† James Guo Sheng Moo,‡ Sheng Liu,† Martin Pumera,‡ and Claus-Dieter Ohl*,† †

Division of Physics and Applied Physics, School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore 637371, Singapore ‡ Division of Chemistry and Biological Chemistry, School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore 637371, Singapore S Supporting Information *

ABSTRACT: Graphene nanobubbles are of significant interest due to their ability to trap mesoscopic volumes of gas for various applications in nanoscale engineering. However, conventional protocols to produce such bubbles are relatively elaborate and require specialized equipment to subject graphite samples to high temperatures or pressures. Here, we demonstrate the formation of graphene nanobubbles between layers of highly oriented pyrolytic graphite (HOPG) with electrolysis. Although this process can also lead to the formation of gaseous surface nanobubbles on top of the substrate, the two types of bubbles can easily be distinguished using atomic force microscopy. We estimated the Young’s modulus, internal pressure, and the thickness of the top membrane of the graphene nanobubbles. The hydrogen storage capacity can reach ∼5 wt % for a graphene nanobubble with a membrane that is four layers thick. The simplicity of our protocol paves the way for such graphitic nanobubbles to be utilized for energy storage and industrial applications on a wide scale. KEYWORDS: Graphene nanobubbles, electrochemistry, water splitting, atomic force microscopy, hydrogen, energy storage

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To create graphene nanobubbles we perform electrolysis on a slab of highly ordered pyrolytic graphite (HOPG). The substrate was prepared by freshly cleaving it with Scotch tape to expose a clean, atomically flat surface. A 100 μL drop of electrolyte containing 10 mM Na2CO3 or NaCl was dispensed over the substrate. A three-electrode electrochemical circuit was used in which the primary electrodes were the HOPG substrate and a platinum wire, with Ag/AgCl/1.0 M KCl used as a reference electrode. Electrochemical potentials stated were taken in reference to Ag/AgCl/1.0 M KCl reference electrode. An electrochemical analyzer (μAutolab III, Eco Chemie, The Netherlands) was used to maintain the electrolytic potential at a constant voltage. At a sufficiently large potential difference, water molecules embedded between a pair of electrodes begin to split into hydrogen and oxygen. Hydrogen is produced at HOPG when it is designated as the cathode, and oxygen when it is designated the anode. It is known in the literature that a modest potential of about −1.5 V is sufficient for bubbles to start appearing on the surface. This phenomenon has long been exploited to study the nucleation of surface-attached nanobubbles using either dilute salt or acid solutions.13−15 We first produce these well-known gaseous nanobubbles by applying a potential of −1.5 V for 90 s in 10 mM sodium carbonate before characterizing the objects with atomic force microscopy (AFM; we use the Bioscope Catalyst, Bruker Corporation, United States). AFM scans were captured in

he curious fact that the interlayer attraction between layers of graphite is significantly weaker than the attraction internal to the layer allows individual layers of graphene to be extracted for a wide variety of novel purposes. In the event of a partial exfoliation, membranes known as graphene nanobubbles are formed. Remarkably, these membranes can be selectively permeable, filtering small gas molecules and even the isotopes effectively.1−5 This discovery has exciting implications for energy generation and storage, nanofluidics, and nanoscale bioreactors; the remarkable optical and electronic properties of graphene nanobubbles may also be useful in nonlinear optics6 or tunable catalytic reactions.7 However, typical protocols used to create graphene nanobubbles require complicated preparation steps, extreme conditions and specialized equipment, all of which hinder the production of graphene nanobubbles at a larger scale. Conventionally, graphene nanobubbles are fabricated by methods such as subjecting graphite to gas ion irradiation at temperatures under thermal annealing at high temperatures,8−12 or with intense laser irradiation.6 The extreme conditions required means that such protocols are not economically viable and cannot be used in situations in which it is desired to create graphene nanobubbles on a substrate that already contains a delicate material such as a biological specimen. Moreover, the type of gas that can be trapped in the nanobubble is specific to the protocol and the specialized equipment available. In this Letter, we show that a simple electrolysis setup in which a slab of graphite is used as one of the electrodes can be used to generate graphene nanobubbles. © 2017 American Chemical Society

Received: December 14, 2016 Revised: February 22, 2017 Published: April 10, 2017 2833

DOI: 10.1021/acs.nanolett.6b05183 Nano Lett. 2017, 17, 2833−2838

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Nano Letters

bubbles, which are intercalated between graphene layers, also known as graphene nanobubbles.8−12 In the rest of this Letter, we define the reaction in which the HOPG is set as the cathode as HOPG-H2, and HOPG-O2 for the electrochemical reaction conducted in the opposite direction. Figure 2 compares the topography of the electrolyzed substrate in liquids (Figure 2a) and when the substrate is

either ScanAsyst mode with manual control (using a peak force of about 0.3 nN) or tapping mode (A/A0 = 0.75 to 0.8, with the free amplitude A0 = 10 nm). Silicon nitride cantilevers (SNL10A, Bruker) with a nominal spring constant of 0.35 N/m, tip half angle of 18°, and a resonance frequency of 65 kHz in air were treated with oxygen plasma (30 W, 30 s, Harrick Plasma, United States) to turn them hydrophilic before imaging. The size (∼50 nm height, ∼800 nm footprint radius) and contact angles (∼168°, measured from the denser water phase) of the nanobubbles are similar to those reported by other research groups who nucleated nanobubbles with electrochemical methods16,17 as well as with the solvent exchange method.18−20 To show the general applicability of this method, we show scans of nanobubbles formed by the same water splitting process using NaCl as well in Figure S1. Unexpectedly, we observe substantially different objects when the applied potential was increased to −3 V for 5 s. The objects observed in the AFM height image are significantly larger, with lateral sizes of bubbles of up to 2 μm and heights of up to 100 nm, see Figure 1c. The nanoscopic contact angles of the objects ranged from 165−177°. Most of the objects are fairly round, though a few were irregularly shaped.

Figure 2. AFM height images after electrolysis with a negative potential of −2.5 V for 30 s, captured in 10 mM Na2CO3 solutions (a) and in air (b). (a) Images were captured in ScanAsyst mode (300pN) after electrolysis. (b) AFM images captured in air after the substrate was rinsed with Milli-Q water for three times and dried. Higher objects in panel (a) disappeared in (b) but left footprints at their original positions (as indicated by black arrows), while the delaminated graphene caused by gas intercalation and evolution remain visible in the images. Scan size, 4 μm × 4 μm; height scale, 50 nm. (c) Crosssectional profiles of surface nanobubble and graphene nanobubble at the position shown in (a). Figure 1. Tapping mode AFM height images (a,c) and phase images (b,d) for surface bubbles and graphene bubbles in 10 mM Na2CO3 solutions, respectively. (a,b) Electrolysis was conducted at a negative potential (−1.5 V) for 90 s. Phase image (b) shows the smooth surface and the objects of big phase contrast to the substrate. (c,d) Electrolysis was done at a negative potential (−3 V) for 5 s. Phase image (d) shows a very rough surface and small contrast. (a−d) Scan size, 10 μm × 10 μm; height scale, 50 nm; phase scale, 5°.

subsequently dried and imaged in air (Figure 2b). Electrolysis was performed at a negative bias of −2.5 V for 30 s. The images show the formation of both round and irregularly shaped objects along with cracks on the substrate (Figure 2a). Many of the smaller, round objects visible in liquid had disappeared by the time the sample was dried and imaged in air, suggesting that these objects were surface-attached nanobubbles sitting on top of the substrate. Some of the objects that had disappeared left behind observable footprints in the dry sample, as indicated by black arrows in Figure 2. The fact that the larger round objects remain in the height images, even when the substrate is dry, supports our hypothesis that these objects are likely to be graphene layers, which have delaminated from the substrate. We also found some cracks in the substrate that are not as straight as the background cleave lines, suggesting the influence of violent forces such as those inducing delamination. Figure 2c shows the plot of the cross-sectional profiles of a surfaceattached nanobubble formed in ionic solutions and of an intercalated nanobubble embedded between graphene layers. It is clear here that the size and angles are significantly different for the two objects. In particular, it is likely that the larger

Phase imaging in tapping mode AFM allows us to distinguish between the two types of objects. Phase imaging is sensitive to soft objects and creates a strong contrast between the objects and the stiff HOPG substrate, as we see with the gaseous surface nanobubbles in Figure 1b. However, the phase image for the objects created with the larger potential exhibited a much smaller contrast, as shown in Figure 1d. In fact, HOPG cleave lines can be seen to run through the object in the lower right corner of Figure 1d, which is not observed for the surface nanobubbles in Figure 1b. All of this suggests that the object observed is delaminated graphite. Since the delaminated bulges are circular and formed by electrolysis, we surmise that the structures are actually electrochemically generated nano2834

DOI: 10.1021/acs.nanolett.6b05183 Nano Lett. 2017, 17, 2833−2838

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Nano Letters contact angle of the intercalated nanobubble is due to mechanical pressure by graphene sheets stacked over it. After removing the liquids, the samples were kept in an oven (60 °C) for 2 days to evaporate any residual water. Then the sample was kept in a desiccator at room temperature to remove as much of the remnant traces of water as possible, before performing AFM imaging in air. While nanobubbles in liquids can only be imaged with small forces since the objects are fairly soft, intercalated nanobubbles covered with graphene can be scanned with relatively invasive contact mode imaging. Figure S2 shows height images captured with contact mode AFM in air, at the same scan area, before and after electrolysis. Using the method detailed by An et al.,20 we estimate that graphene bubbles survive invasive contact mode scanning with a force of ∼20 nN. SEM images (Figure S3) on a dry HOPG substrate also show that the electrolysis has patterned the substrate with objects with dimension ≈ 1 μm, in agreement with the AFM characterization. We can exploit the ability of the electrolysis to create two different types of gas to prove that the graphene nanobubbles observed here are indeed created by electrolysis of water. The water splitting reaction 2H2O → 2H2(g) + O2(g) implies that twice as many hydrogen molecules are produced as oxygen ones during electrolysis. Our results are consistent with this expectation. In Figure S4 we show contact mode AFM scans of a dried HOPG substrate showing graphene nanobubbles formed during electrolysis. The hydrogen graphene nanobubbles (HOPG-H2, −5 V for 5 s, Figure S4a; HOPG-H2, −10 V for 5 s, Figure S5) are clearly in greater abundance than the oxygen graphene nanobubbles (HOPG-O2, 5 V for 5 s, Figure S4b), leading to the creation of a significantly rougher surface. To further differentiate the nanomechanical properties of gaseous surface nanobubble and intercalated graphene nanobubbles, we performed force curves in ScanAsyst mode using a module known as “point and shoot”, the details of which have been described in An et al.20 Figure 3 shows force−separation curves on HOPG, surface nanobubbles, and graphene nanobubbles nucleated between layers of graphite. All the curves are captured when the substrate was immersed in liquid. The force−separation curves were calculated from the deflection versus z-piezo displacement curves using in-built software. Figure 3a,b illustrates the behavior of nanobubbles intercalated between graphene layers. If a sufficiently large force is used then the AFM tip successfully snaps through all the layers of the membrane and snaps into contact with the HOPG substrate beneath. Note that the vertical separation and force required for snap-in varies from bubble to bubble; a higher bubble would require a larger separation for penetration, while a graphene nanobubble with a thicker top graphite membrane would require a larger peak force for penetration and snap-in. The force curves are noticeably different for a surface nanobubble (Figure 3d). After the AFM tip touches the surface bubbles, a linear compliance regime follows with a small slope, suggesting that the object is deformable.18,20−22 The aforementioned force curves allow us to estimate the Young’s modulus of the intercalated graphene nanobubble using the Sneddon model.23,24 The ramping force F is related to 2 E the Young’s modulus by F = π (1 − ν 2) tan(α)δ 2 , where E is the

Figure 3. Force versus separation curves for bubbles between layers (a,b),and surface bubble (d) using the same cantilever, measured in ionic solutions. The AFM tip penetrates the intercalated bubble during approaching at the breakthrough force of ∼20 nN (a) and 120 nN (b), respectively. (c,d) Force vs separation curve on HOPG and surface nanobubbles. (e,f) Estimated Young’s modulus of bubble membrane by Sneddon model from curves (a) and (b), respectively.

versus the load from the AFM tip. From the curve in Figure 3a, we obtained E ≈ 700 GPa at a load of 19 nN on a small nanobubble (height = 12 nm, footprint radius = 175 nm, ∼20 layers), and from the force curve in Figure 3b, we obtained E ≈ 780 GPa at the load of 120 nN for the bubble with height of 22 nm and base radius of 375 nm, around ∼50 layers (Figure 3f). In order for the graphene nanobubbles created in this system to be useful for applications it is important to understand some basic properties about them: how large is the pressure exerted by the graphene membrane, and how thick is the membrane of the graphene nanobubble? The latter question is of significance in optical applications of graphene nanobubbles since the optical properties of the nanobubbles depend strongly on the membrane thickness. To estimate the internal pressure in the graphene nanobubble we follow the formulation of Yue et al.26 closely. Although it is common to use Hencky’s equation27−29 to recover the internal pressure in a graphene nanobubble, it is worth noting that a uniform lateral loading on the membrane assumed in the Hencky model differs from the physical situation in which entrapped gas in the graphene nanobubble is exerting a uniform pressure. The Yue model improves on the original Hencky estimate by assuming a uniform pressure rather than a uniform lateral load. It considers an energetic balance between the elastic strain energy of the membrane (which is in turn supplied by the gas pressure within the graphene nanobubble) and adhesion energy responsible for delaminating the graphene nanobubble. At equilibrium, the adhesion energy can be expressed as

sample modulus; ν is Poisson’s ratio; α is tip half angle; and δ is the indentation of the sample. For the values ν = 0.1625 and α = 18°, we estimate E before the AFM tip breaking through the membrane. Figure 3e,f shows the estimated Young’s modulus

Γ= 2835

5E2Dh4 8ϕa 4

=

5Enth4 8ϕa 4

(1) DOI: 10.1021/acs.nanolett.6b05183 Nano Lett. 2017, 17, 2833−2838

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Nano Letters where h and a are the height and footprint radius of the graphene membrane and ϕ(ν) =

75(1 − ν 2) 8(23 + 18ν − 3ν 2)

The Raman spectra indicate changes to the crystalline structure of HOPG, such as those brought on by oxidation during water splitting. The D and D′ bands in the Raman spectra (Figure 5) give an indication on whether the electrolysis

is a geometric

prefactor that is a function of the Poisson ratio ν, when h ≪ a. For ν = 0.16, we have ϕ(0.16) ≈ 0.345. The E2D term is the Young modulus of the membrane, which scales with that of monolayer graphene as E2D = Ent, where E = 1 TPa is the accepted Young modulus of monolayer graphene, n is the number of graphene layers, and t = 0.335 nm is the thickness of monolayer graphene.25 Finally, the adhesion energy between layers of graphite has been found from both experimental30−32 and numerical calculations33 to be in the region of 0.33 J/m2. Some older studies have cited slightly different values for the adhesion energy,2,34−36 which originate from an underestimate of the Young modulus E. Upon substituting the aforementioned constants and the adhesion energy Γ ≈ 0.33 J/m2 and rearranging, we obtain an equation for the number of layers of graphene n=

4 8Γϕ ⎛ a ⎞4 −4 ⎛ a ⎞ ⎜ ⎟ ≈ 5.75 × 10 ⎜ ⎟ ⎝h⎠ 5Et ⎝ h ⎠

(2)

The top layer number n is determined by the ratio h/a (Figure 4a), and is independent of h and a (Figure S6). This calculation

Figure 5. Raman spectra of HOPG with oxygen bubbles (a), HOPG with hydrogen bubbles (b), and pristine HOPG (c). Raman spectra showed D, G, and 2D peaks. The G band for HOPG samples with oxygen and hydrogen bubbles between layers was numerically fitted by two peaks (G and D′). The 2D band was divided into two peaks by Lorentz fitting (2D1 and 2D2). The fitted parameters are listed in Table S1.

is creating crystalline defects in the HOPG. We note the emergence of a pronounced D peak at 1349 cm−1, which is particularly strong for HOPG-O2, which produces both O2 and H+. The accumulation of H+ rapidly decreases the pH, which further accelerates the oxidation of graphite. The presence of strong oxidation of the HOPG-O2 is also supported from ATRFTIR spectra (Supporting Information Figure S8), where the strong peak at 1733 cm −1 is an indicator of CO stretching.37,38 The ability of graphene oxide to be an impermeable gas trap has long been noted in the literature.39,40 The line shape of the 2D band has long been utilized to deduce the layer number, orientation, and stacking of graphene.41 This band is typically deconvolved into two Lorentzian curves, revealing a 2D1 peak at 2684 cm−1 and 2D2 peak at 2724 cm−1 for pristine HOPG.42,43 Typically, the integrated intensity ratio I2D1/I2D2 (Supporting Information Table S1) is at its lowest for bulk graphite and starts to increase as the layer number reduces. We indeed see a steady increase of I2D1/I2D2, and this ratio is largest for HOPG-H2, which produces more graphene nanobubbles than the oxygen counterpart. The increase of I2D1/I2D2 indicates the formation of few-layer graphene domains when gaseous bubble intercalated between the graphite layers. A red shift of about 10 cm−1 was observed on HOPG-H2 bubbles, similar to that observed in Raman spectra of electrochemical expanded and chemical exfoliated graphene.44 Overall, the Raman spectra suggest the delamination of fewlayer graphene by our water splitting protocol. In order to evaluate the potential for the graphene nanobubbles created with our water-splitting technique for energy storage applications, we next estimate the gravimetric storage density achieved by the nanobubbles for the HOPG-H2 reaction. Here we assume that only hydrogen is produced inside the nanobubble. If we take a single graphene bubble as a spherical cap, the total number of carbon atoms can be

Figure 4. (a) Number of top graphene layers n as a function of h/a. The ratio of h/a determines the thickness of the delaminated membrane. For details of the error propagation, refer to Table S2 of the Supporting Information. (b) The estimated gravimetric hydrogen storage capacity versus top layer number. The solid line is a fit to a power law. Fewer top layer numbers imply a higher gas storage efficiency.

predicts that h/a = 0.155 for a monolayer membrane. By applying this equation to the 24 graphene nanobubbles presented in Table S2, we find a range of membrane thicknesses ranging from several layers (4−5) to a relatively thick graphite membrane of up to 100 graphene layers (Figure S7). The Yue model also allows us to estimate the internal pressure in the graphene nanobubble by the equation Δp =

E2Dh3 ϕa 4

≈

2.82Enth3 a4

(3)

in which the coefficient 2.82 is close to K(ν) = 3.09 in Hencky’s solution Δp =

K (ν)Enth3 . a4

The number of gas molecule inside the pV

bubble is thus obtained by the ideal gas law NG = kT , where k is the Boltzmann constant, T is temperature, and πh V = 6 (3a 2 + h2) for a spherical cap. The internal pressure Δp of the 24 graphene nanobubbles based on eq 3 is tabulated in Table S2 of the Supporting Information. 2836

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estimated: Nc = 2S/Auc, where Auc is the area of unit cell Auc = 0.051 nm2,45 S is the total surface area S = πa2 + π(a2 + h2), and there are two carbon atoms per unit cell. Assuming that the spherically capped membrane is composed of n layers of graphene, and there is only one graphene layer at bottom, S = πa2 + nπ(a2 + h2). The gravimetric storage capacity at the 2N bubble area is obtained by Ω = 12NG . Figure 4b shows the

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.nanolett.6b05183. Raman shift band positions; top layer numbers, thickness and pressure of graphene nanobubbles; AFM height images; SEM images of graphene nanobubbles; and ATR-FTIR spectra (PDF)

C

gravimetric hydrogen storage capacity for randomly selected graphene bubbles. Let us note that the gravimetric storage capacity in Table S2 is not for the whole graphite surface, and the average gravimetric storage capacity depends on the distribution and density of graphene bubbles, which can be controlled by reaction parameters. Our calculations indicate that graphene nanobubbles have significant potential for hydrogen storage applications. Our calculations show that graphene nanobubbles with membranes less than five layers thick have a gravimetric capacity of about 5.3%. In fact, the capacity diverges rapidly with membrane thinness; the thinner the bubble membrane is, the higher hydrogen gravimetric storage capacity. If the top membrane is a monolayer, the hydrogen capacity of ∼21 wt % is obtained from the fitting curve (Figure 4b), i.e., H2/C = 1.26. Hydrogen captured by the graphene nanobubbles in our experiments is much higher than the theoretical binding capacity of hydrogen in graphene of about 7.7 wt %.46 This is because the number of hydrogen molecules in graphene nanobubble is far more than the quantity by physical adsorption and chemical binding of hydrogen onto the graphene surfaces. These numbers in our experiment easily match national targets set by the United States Department of Energy to achieve a hydrogen storage capacity of 5% by 2020 and 7.5% ultimately.47 Although we have not found nanobubble membranes thinner than four layers in limited testing, refinement of the present protocol should be able to maximize the storage capacity through the reproducible creation of monolayer graphene nanobubbles. In conclusion, we show in this Letter a method to generate graphene nanobubbles from a slab of graphite using electrolysis of water at standard laboratory conditions, while avoiding the need for specialized equipment. Although this method can create both graphene nanobubbles intercalated between graphite layers and gas bubbles atop the substrate, we are able to distinguish between the two with careful AFM characterization. Raman characterization and theoretical calculations are consistent with the interpretation that the graphene nanobubbles comprise membranes that are several layers thick. Our method of nucleating graphene nanobubbles is particularly advantageous over existing protocols in several respects. The wide availability of the materials, simplicity of the protocol, and use of a modest electrochemical potential mean that graphene nanobubbles can be fabricated on an arbitrarily large scale as compared to, for instance, laser irradiation where nucleation is essentially limited by the size of the laser spot. Moreover, the method is general enough that one can, in principle, create graphene nanobubbles containing any kind of gas, provided that the right electrolyte is used and a suitable electrochemical pathway exists. Finally, our calculations suggest that graphene nanobubbles are able to achieve a hydrogen gravimetric storage capacity close to the theoretical limit when the membrane is several layers thick. We anticipate that our results will be especially useful in the widespread adoption of graphene nanobubbles in the development of clean energy technologies that utilize hydrogen as a fuel source.

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AUTHOR INFORMATION

Corresponding Authors

*E-mail: [email protected]. *E-mail: [email protected]. ORCID

Hongjie An: 0000-0003-4095-1751 Martin Pumera: 0000-0001-5846-2951 Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS We gratefully acknowledge funding from a competitive research programme under the auspices of the Singapore government’s National Research Foundation (programme no. NRF-CRP92011-04). B.H.T. acknowledges financial support from the Agency of Science, Technology and Research in Singapore. J.G.S.M. is supported by the National Research Foundation Singapore under its National Research Foundation (NRF) Environmental and Water Technologies (EWT) Ph.D. Scholarship Programme and administered by the Environment and Water Industry Programme Office (EWI). M.P. acknowledges a Tier 2 grant (MOE2013-T2-1-056; ARC 35/13) from the Ministry of Education, Singapore.

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REFERENCES

(1) Lozada-Hidalgo, M.; Hu, S.; Marshall, O.; Mishchenko, A.; Grigorenko, A. N.; Dryfe, R. A. W.; Radha, B.; Grigorieva, I. V.; Geim, A. K. Science 2016, 351, 68−70. (2) Joshi, R. K.; Carbone, P.; Wang, F. C.; Kravets, V. G.; Su, Y.; Grigorieva, I. V.; Wu, H. A.; Geim, A. K.; Nair, R. R. Science 2014, 343, 752−754. (3) Bunch, J. S.; Verbridge, S. S.; Alden, J. S.; van der Zande, A. M.; Parpia, J. M.; Craighead, H. G.; McEuen, P. L. Nano Lett. 2008, 8, 2458−2462. (4) Kim, H. W.; Yoon, H. W.; Yoon, S.-M.; Yoo, B. M.; Ahn, B. K.; Cho, Y. H.; Shin, H. J.; Yang, H.; Paik, U.; Kwon, S.; Choi, J.-Y.; Park, H. B. Science 2013, 342, 91−95. (5) Li, H.; Song, Z.; Zhang, X.; Huang, Y.; Li, S.; Mao, Y.; Ploehn, H. J.; Bao, Y.; Yu, M. Science 2013, 342, 95−98. (6) Bao, Q.; Chen, J.; Xiang, Y.; Zhang, K.; Li, S.; Jiang, X.; Xu, Q.H.; Loh, K. P.; Venkatesan, T. Adv. Opt. Mater. 2015, 3, 744−749. (7) Su, Y.; Kravets, V. G.; Wong, S. L.; Waters, J.; Geim, A. K.; Nair, R. R. Nat. Commun. 2014, 5, 4843. (8) Zamborlini, G.; Imam, M.; Patera, L. L.; Mentes, T. O.; Stojić, N.; Africh, C.; Sala, A.; Binggeli, N.; Comelli, G.; Locatelli, A. Nano Lett. 2015, 15, 6162−6169. (9) Levy, N.; Burke, S. A.; Meaker, K. L.; Panlasigui, M.; Zettl, A.; Guinea, F.; Neto, A. H. C.; Crommie, M. F. Science 2010, 329, 544− 547. (10) Herbig, C.; Ahlgren, E. H.; Jolie, W.; Busse, C.; Kotakoski, J.; Krasheninnikov, A. V.; Michely, T. ACS Nano 2014, 8, 12208−12218. (11) Lu, J.; Neto, A. H. C.; Loh, K. P. Nat. Commun. 2012, 3, 823. (12) Stolyarova, E.; Stolyarov, D.; Bolotin, K.; Ryu, S.; Liu, L.; Rim, K. T.; Klima, M.; Hybertsen, M.; Pogorelsky, I.; Pavlishin, I.; Kusche, 2837

DOI: 10.1021/acs.nanolett.6b05183 Nano Lett. 2017, 17, 2833−2838

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Nano Letters K.; Hone, J.; Kim, P.; Stormer, H. L.; Yakimenko, V.; Flynn, G. Nano Lett. 2009, 9, 332−337. (13) Zhang, L.; Zhang, Y.; Zhang, X.; Li, Z.; Shen, G.; Ye, M.; Fan, C.; Fang, H.; Hu, J. Langmuir 2006, 22, 8109−8113. (14) Wu, Z.; Chen, H.; Dong, Y.; Mao, H.; Sun, J.; Chen, S.; Craig, V. S. J.; Hu, J. J. Colloid Interface Sci. 2008, 328, 10−14. (15) Yang, S.; Tsai, P.; Kooij, E. S.; Prosperetti, A.; Zandvliet, H. J. W.; Lohse, D. Langmuir 2009, 25, 1466−1474. (16) Zhang, L.; Zhang, X.; Zhang, Y.; Hu, J.; Fang, H. Soft Matter 2010, 6, 4515−4519. (17) An, H.; Tan, B. H.; Ohl, C.-D. Langmuir 2016, 32, 12710− 12715. (18) An, H.; Liu, G.; Atkin, R.; Craig, V. S. ACS Nano 2015, 9, 7596−7607. (19) Zhang, X. H.; Maeda, N.; Craig, V. S. J. Langmuir 2006, 22, 5025−5035. (20) An, H.; Tan, B. H.; Zeng, Q.; Ohl, C.-D. Langmuir 2016, 32, 11212−11220. (21) Butt, H.-J.; Cappella, B.; Kappl, M. Surf. Sci. Rep. 2005, 59, 1− 152. (22) Heinz, W. F.; Hoh, J. H. Trends Biotechnol. 1999, 17, 143−150. (23) Sneddon, I. N. Fourier Transforms; McGraw-Hill: New York, 1951. (24) Sneddon, I. N. Int. J. Eng. Sci. 1965, 3, 47−57. (25) Lee, C.; Wei, X.; Kysar, J. W.; Hone, J. Science 2008, 321, 385− 388. (26) Yue, K.; Gao, W.; Huang, R.; Liechti, K. M. J. Appl. Phys. 2012, 112, 083512. (27) Zabel, J.; Nair, R. R.; Ott, A.; Georgiou, T.; Geim, A. K.; Novoselov, K. S.; Casiraghi, C. Nano Lett. 2012, 12, 617−621. (28) Dollekamp, E.; Bampoulis, P.; Poelsema, B.; Zandvliet, H. J. W.; Kooij, E. S. Langmuir 2016, 32, 6582−6590. (29) Bunch, J. S.; Dunn, M. L. Solid State Commun. 2012, 152, 1359− 1364. (30) Koenig, S. P.; Boddeti, N. G.; Dunn, M. L.; Bunch, J. S. Nat. Nanotechnol. 2011, 6, 543−546. (31) Shih, C.-J.; Strano, M. S.; Blankschtein, D. Nat. Mater. 2013, 12, 866−869. (32) Zacharia, R.; Ulbricht, H.; Hertel, T. Phys. Rev. B: Condens. Matter Mater. Phys. 2004, 69 (15), 155406. (33) Sasaki, N.; Okamoto, H.; Masuda, S.; Miura, K.; Itamura, N. J. Nanomater. 2010, 2010, 12. (34) Georgiou, T.; Britnell, L.; Blake, P.; Gorbachev, R. V.; Gholinia, A.; Geim, A. K.; Casiraghi, C.; Novoselov, K. S. Appl. Phys. Lett. 2011, 99, 093103. (35) Wang, S.; Zhang, Y.; Abidi, N.; Cabrales, L. Langmuir 2009, 25, 11078−11081. (36) Zong, Z.; Chen, C.-L.; Dokmeci, M. R.; Wan, K.-t. J. Appl. Phys. 2010, 107, 026104. (37) Wang, Y.; Cao, J.; Zhou, Y.; Ouyang, J.-H.; Jia, D.; Guo, L. J. Electrochem. Soc. 2012, 159, A579−A583. (38) Pan, Q.; Guo, K.; Wang, L.; Fang, S. J. Electrochem. Soc. 2002, 149, A1218−A1223. (39) Goss, C. A.; Brumfield, J. C.; Irene, E. A.; Murray, R. W. Anal. Chem. 1993, 65, 1378−1389. (40) Hathcock, K. W.; Brumfield, J. C.; Goss, C. A.; Irene, E. A.; Murray, R. W. Anal. Chem. 1995, 67, 2201−2206. (41) Xu, W.; Mao, N.; Zhang, J. Small 2013, 9, 1206−1224. (42) Ferrari, A. C. Solid State Commun. 2007, 143, 47−57. (43) Pimenta, M. A.; Dresselhaus, G.; Dresselhaus, M. S.; Cancado, L. G.; Jorio, A.; Saito, R. Phys. Chem. Chem. Phys. 2007, 9, 1276−1290. (44) Kim, H. J.; Lee, S.-M.; Oh, Y.-S.; Yang, Y.-H.; Lim, Y. S.; Yoon, D. H.; Lee, C.; Kim, J.-Y.; Ruoff, R. S. Sci. Rep. 2014, 4, 5176. (45) Fuchs, J.-N.; Goerbig, M. O. Introduction to the Physical Properties of Graphene. Lecture Notes: http://web.physics.ucsb.edu/ ~phys123B/w2015/pdf_CoursGraphene2008.pdf, 2008; p 11. Access date: 23-Aug-2016. (46) Pumera, M. Energy Environ. Sci. 2011, 4, 668−674. (47) Jena, P. J. Phys. Chem. Lett. 2011, 2, 206−211. 2838

DOI: 10.1021/acs.nanolett.6b05183 Nano Lett. 2017, 17, 2833−2838