Doping-Induced Tunable Wettability and Adhesion of Graphene

Jun 28, 2016 - We thank P. Kang, J. Leem, and D. Lisk for assistance. Figure 4. WCA modulation of doped graphene investigated by combined first-princi...
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Doping-Induced Tunable Wettability and Adhesion of Graphene Ali Ashraf,† Yanbin Wu,† Michael Cai Wang,† Keong Yong,† Tao Sun,† Yuhang Jing,† Richard T. Haasch,‡ Narayana R. Aluru,† and SungWoo Nam*,† †

Department of Mechanical Science and Engineering and ‡Frederick Seitz Materials Research Laboratory, University of Illinois at Urbana−Champaign, Urbana, Illinois 61801, United States S Supporting Information *

ABSTRACT: We report that substrate doping-induced charge carrier density modulation leads to the tunable wettability and adhesion of graphene. Graphene’s water contact angle changes by as much as 13° as a result of a 300 meV change in doping level. Upon either n- or p-type doping with subsurface polyelectrolytes, graphene exhibits increased hydrophilicity. Adhesion force measurements using a hydrophobic selfassembled monolayer-coated atomic force microscopy probe reveal enhanced attraction toward undoped graphene, consistent with wettability modulation. This doping-induced wettability modulation is also achieved via a lateral metal−graphene heterojunction or subsurface metal doping. Combined firstprinciples and atomistic calculations show that doping modulates the binding energy between water and graphene and thus increases its hydrophilicity. Our study suggests for the first time that the doping-induced modulation of the charge carrier density in graphene influences its wettability and adhesion. This opens up unique and new opportunities for the tunable wettability and adhesion of graphene for advanced coating materials and transducers. KEYWORDS: Graphene, tunable wettability and adhesion, doping, first-principles, nonbonded interaction

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screening of underlying substrate forces).13−15 This study focuses on the effect of graphene’s electronic states (i.e., doping) on wettability of graphene and therefore reconciles these unresolved questions regarding wetting transparency and opacity. To elucidate the contribution of doping to water−graphene nonbonded interactions or secondary bonding (i.e., vdW and electrostatic interactions), we chemically modulated graphene’s electronic state, changing its electron density using different subsurface polyelectrolytes without new chemical bond formation or continuous external electron flow.16−18 Our investigations reveal that the WCA changes by up to 13° when the work function (WF) is modulated by 300 meV. In addition, the adhesion force between the doped graphene sample and the hydrophobic atomic force microscopy (AFM) probe was half the level of an undoped sample. Graphene synthesized by chemical vapor deposition19 was transferred onto a polyelectrolyte-coated SiO2/Si surface by a modified graphene transfer technique (Figure S1) that simultaneously incorporated the subsurface polyelectrolytes. The WCA was measured on the micrometer scale by environmental scanning electron microscopy (E-SEM) image analysis (Figures S2 and S3). The corresponding doping level of graphene by the subsurface polyelectrolyte was analyzed by

raphene, unlike conventional bulk materials, interacts with external molecules in its close vicinity1,2 via delocalized π-electrons. External molecules can affect the doping levels of graphene by interacting with delocalized Dirac electrons (e.g., water is an electron acceptor, whereas ethanol is a donor).2,3 The modulation of the doping levels, in turn, can affect the way that graphene interacts with external molecules; for example, doping-induced electron−hole puddles and change in the spatial extent of π-orbitals in graphene were found to change its chemical reactivity4 and van der Waals (vdW) interaction with nonpolar molecules,5 respectively. More recently, simulation studies have suggested that doping and charge injection into graphene can lead to higher water adsorption6 and changes in wettability.7 Elucidating the direct connections between the delocalized electrons and the surface adhesion/wettability of graphene will open up new opportunities in tunable wetting and adhesion. Graphene is intrinsically hydrophilic with a water contact angle (WCA) of ∼45°.8,9 Hydrocarbonaceous adsorbates of ambient origin impart hydrophobicity to graphene8,10,11 by creating local hydrophobic spots sufficient to mask its intrinsic hydrophilicity. Furthermore, because pristine graphene is a gapless and semimetallic material, its interactions with water are dominated by vdW interactions. However, when graphene is sitting on a substrate, WCA of graphene can be influenced by both graphene and graphene−substrate interactions (i.e., doping). Contradictory findings have been reported for the so-called “wetting transparency” (dominant influence of vdW forces of underlying substrates)12 and “opacity” (graphene © XXXX American Chemical Society

Received: June 2, 2016 Revised: June 23, 2016

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DOI: 10.1021/acs.nanolett.6b02228 Nano Lett. XXXX, XXX, XXX−XXX

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Figure 1. Concept and relationship between doping and wettability. (a) Schematic illustrations showing graphene wettability modulation by dopinginduced Fermi level shifts. (b) WCA (left axis) measured by E-SEM and WF (right axis) measured by SKPM of polyelectrolyte-doped and undoped graphene samples. For both n- and p-doping, the WCA of graphene decreases. Error bars represent one standard deviation. Insets show false-colored E-SEM images of water droplets (scale bars represent 10 μm).

Figure 2. Doping and surface functionality characterizations. (a) Raman peak shifts for doped and undoped graphene samples. For n-doping, the 2D and G peaks are red-shifted, whereas the opposite occurs for p-doping. The 2D peaks exhibited higher intensities for all the doped samples. For the PSS sample, a higher peak intensity of the G peak was observed. (b) XPS comparison of hydrophilic groups of doped and undoped graphene samples. The doped sample (PAH) had a similar or lower number of hydrophilic groups than the undoped sample (SiO2), which supports our finding that the reduction in the WCA is not caused by the surface functional groups.

[PSS] and poly(acrylic acid) [PAA]) exhibited a lower WCA by up to 13° (Figure 1b). Furthermore, at higher doping levels (as measured by SKPM) we observed lower WCAs. In contrast, the WCA of graphene on poly(methyl methacrylate) (PMMA), which is a polymer that contains no charged groups, was similar to that of undoped graphene on SiO2 (Figure S11). The chemical doping of graphene by charged polyelectrolytes was further verified by ultraviolet photoelectron spectroscopy (UPS) (Figure S12), polyelectrolyte solution gating of a graphene field-effect transistor (FET) device (Figure S13), and Raman spectroscopy (Figure 2a). The change in graphene’s WF (Figure S12b), the shift of the Dirac point of the graphene FET source-drain current (I) versus solution gate voltage (V) curve (Figure S13), and the Raman G and 2D peak shifts (red shift for n-doping, and vice versa) (Figure 2a)20 confirmed that the graphene was effectively doped by the various polyelectrolytes. Our simulation studies also show that the WF of graphene changes when graphene is in contact with the four different polyelectrolytes (Figure S14). The sign of the WF change agrees with the experimental results, and the magnitude of the WF change varies depending on the polyelectrolyte configuration (as indicated by the error bars in Figure S14). The simulation results for doping with water molecules demonstrate that graphene is not significantly doped by water (Figure S15). Therefore, compared to polyelectrolyte-induced doping, the

scanning Kelvin probe microscopy (SKPM) to probe the WF. Post examination of the graphene sample area using microscopy techniques (E-SEM and Raman microscopy) (Figures S4 and S5) produced reliable data by eliminating the possibility of errors resulting from breakage in the graphene film (Figure S6) or polyelectrolyte swelling (Figures S7 and S8) and thus provided a degree of measurement reliability not achievable by macroscopic techniques (Figure S9). In addition, the modified graphene transfer technique eliminated the possibility of unintentional doping and enhanced hydrophobicity (Figure S10) due to polymeric residue left behind by conventional transfer technique utilizing polymeric scaffold. The E-SEM and SKPM results demonstrate that chemically doped graphene shows a smaller WCA than nominally undoped graphene on the same SiO2 substrate (Figure 1). Compared to that resulting from polyelectrolyte-induced doping, doping by bare SiO2 substrate was found to be negligible (Figure 1) (more details in Supporting Information) and hence it is considered an undoped sample. Depending on the polyelectrolyte type (electron donor or acceptor), graphene’s Fermi level shifts result in either p- or n-type doping, which influences the WCA (Figure 1a). Compared to undoped graphene on a SiO2 substrate, both the n-doped graphene (by high molecular weight [HMW] poly(allylamine hydrochloride) [PAH] and poly-L-lysine [PLL]) and the pdoped graphene (by HMW poly(sodium 4-styrenesulfonate) B

DOI: 10.1021/acs.nanolett.6b02228 Nano Lett. XXXX, XXX, XXX−XXX

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Figure 3. Relationship between band bending and wettability and adhesion force measurements. (a) Relationship between band bending and WCA of graphene. The surface potential (right axis) was measured using SKPM, and the WCA (left axis) was measured by E-SEM at different distances from the gold-graphene junction. Inset shows a schematic illustration of the WCA measurement of graphene transferred onto a gold pad. (b) Adhesion force measurement of doped and undoped graphene samples using an OTS-coated silicon AFM probe. For both n- and p-doping, a decrease in the adhesion force was observed. Hydrophilic SiO2/Si was used as a control substrate and showed the lowest adhesion force. Inset shows a typical force curve observed using an OTS-coated silicon AFM probe. Error bars represent 1 standard deviation.

that of undoped graphene on SiO2 (78−81°). We also investigated WCA modulation resulting from the subsurface metal-induced doping of graphene. For graphene grown on copper with a low n-doping level (see Supporting Information), the WCA was similar to that of undoped graphene (∼81°), whereas greater p-doping of graphene by subsurface gold resulted in a 2° WCA decrease (Figure S19). The adhesion force is closely related to the WCA. The interaction between an AFM probe (coated with hydrophobic self-assembled monolayer [SAM]) and a substrate can indicate a substrate’s adhesion force toward the hydrophobic probe,26 which can provide evidence regarding the wettability state.27 We carried out AFM adhesion force measurements using an octadecyltrichlorosilane (OTS)-coated silicon tip (Figure 3b; 128 data points were recorded in an 18 μm2 sample area). The difference in force upon the approach and retraction of the AFM probe toward and from the graphene surface represents the adhesion force. A graphene surface with a larger adhesion force has a stronger interaction with the hydrophobic AFM probe and is therefore more hydrophobic. Undoped graphene showed a stronger adhesion force (∼25 nN) than doped graphene (∼17 and 11 nN), indicating that undoped graphene is more hydrophobic than the doped samples studied here with the bare SiO2 control sample being the most hydrophilic (∼6.1 nN) (Figure 3b). Control experiments with an uncoated probe revealed no difference in the adhesion force between undoped graphene and bare SiO2 (Figure S20). This nanoscopic investigation confirms the E-SEM findings of wettability modulation and thus supports the different WCAs result from the polyelectrolyte doping of graphene. To understand the tunable wettability of doped graphene, we performed an analytical estimation based on the modified Young−Lippmann equation. The Young−Lippmann equation analytically predicts WCA modulation on a semiconductor or metal caused by electrowetting (see Supporting Information). The same concept can be extended to doped graphene, with modifications of the electric field and capacitance terms (Figure S21). From the modified Young−Lippmann equation, the WCA changes by ∼1.5−4° for a 400−700 meV change in the graphene WF (see Supporting Information). To obtain a more accurate theoretical estimation of the WCA modulation achieved by doping graphene, we performed combined first-principles and atomistic simulations (Figure

doping of graphene by water molecules during the WCA measurement is negligible. We also studied other factors that can influence graphene wettability, including the number of graphene layers,21,22 roughness,23 and surface functionality.8 Raman spectroscopy indicates that the graphene samples are single or bilayer graphene20 (Figure 2a). AFM thickness measurements of the graphene sample on SiO2/Si corroborate the single-layer observation (thickness ∼0.3 nm) (Figure S16a). Additionally, AFM roughness measurements show that all the graphene samples (doped and undoped) have similar roughness, with a root-mean-square (RMS) value of less than 10 nm (Figure S16b). We conducted X-ray photoelectron spectroscopy (XPS) to compare the prevalence of oxygen-containing hydrophilic functional groups on the graphene surface for the doped and undoped samples. Hydrophilic surface functional groups can decrease the WCA. The doped graphene was analyzed by angle-resolved XPS (ARXPS), and the atomic compositions of the functional groups were adjusted to avoid the influence of the subsurface polyelectrolyte for comparison with the undoped sample (see Supporting Information). ARXPS results show that the doped sample has a similar (0.056 vs 0.05 for carbonyl groups) or lower (0.02 vs 0.04 for hydroxyl and 0.001 vs 0.007 for carboxylic species) amount of hydrophilic oxygencontaining functional groups than the undoped graphene (Figures 2b and S17a−f). Therefore, we conclude that the observed decrease in the WCA is not caused by changes in the number of layers, roughness, or surface functional groups. Rather, it results from the change in graphene’s doping level. Another approach to modulating the charge carrier density or surface potential of graphene is to place graphene in proximity to a metal by creating a lateral metal−graphene heterojunction or doping with a subsurface metal. In a metal−graphene heterojunction, graphene’s surface potential will change as a function of the distance (in the micrometer range because of band bending and doping) from the contact.24,25 Graphene’s WCA decreased when the water droplet was close to the graphene−gold junction (Figure 3a) and was observable up to 20 μm away from the junction (another sample showed changes at distances up to 35 μm, Figure S18). Within this region, we observed a change in WCA of ∼3° for a 20-meV change in the WF. Beyond 30 μm, the WCA value converges to C

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change of 300 meV caused by the electrostatic interaction of graphene with subsurface atoms and molecules translates to a change of as much as 13° in the WCA, and we believe that this is an important factor that can explain earlier observations of phenomena such as wetting translucency, tunable water adsorption, and tunable adhesion force. Achieving microscopic wettability modulation by changing the electronic structure of graphene could potentially be extended to advanced tunable coating layers, multifunctional biological and chemical sensors with tunable adhesion,30 doping-induced electrowetting displays,31 surface energy-driven microelectromechanical system (MEMS) devices, and antifouling heat transfer surfaces. This investigation further contributes to the overall understanding of graphene’s wettability by elucidating the influence of dopinginduced nonbonded interactions on wettability modulation. This study provides a new perspective on wetting transparency and/or opacity by shifting the focus from the underlying substrate to graphene’s doping level. Finally, it also suggests a unique linkage between a subatomic particle (i.e., electron) and the macro/microscopic properties (i.e., surface energy) of graphene.

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ASSOCIATED CONTENT

S Supporting Information *

Figure 4. WCA modulation of doped graphene investigated by combined first-principles and atomistic simulations. (a) WF change and number of electrons transferred to graphene per dopant computed by DFT. (b) Changes in the graphene−water binding energy when graphene was doped. Four different water orientations were considered. The binding energies were computed by the RPA method. (c) WCA changes when graphene was doped. The WCA was simulated using MD simulations based on the binding energy in (b). (d) Water orientation distributions for undoped and doped graphene. The angles formed by O−H and the surface normal direction of the graphene surface (ω) were sampled.

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.nanolett.6b02228. Methods and supporting figures. (PDF)

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Notes

The authors declare no competing financial interest.

4). First, using density functional theory (DFT) calculations,28 we elucidated whether graphene is p-doped by an increase in the WF or n-doped by a decrease in the WF. We showed that the change in the WF is caused by charge transfer between the dopant and graphene (Figure 4a). Second, using random phase approximation (RPA),29 we computed the binding energy between the water molecules and graphene, which changes when the graphene is doped. The sign and magnitude of the change depend on the water orientation with respect to graphene (Figure 4b). The binding energies computed by RPA were used to develop force field parameters for water interacting with doped graphene. Finally, using molecular dynamics (MD) simulations, we computed the WCA on graphene with developed force field parameters. The WCA decreases by 9.1 ± 3.6° for n-doped graphene and by 7.2 ± 3.6° for p-doped graphene for a 450 meV change in the WF (Figure 4c). Therefore, for a 100 meV change in the WF caused by doping, the corresponding changes in the WCA were 2.02° for n-doping and 1.6° for p-doping. These values exhibit a trend similar to the experimental observations for n-doped graphene on PAH (3.5° ΔWCA for 100 meV ΔWF) and p-doped graphene on PAA (2.4° ΔWCA for 100 meV ΔWF). The increased hydrophilicity was mainly caused by the modulation of the binding energy between the water molecules and graphene with a minor modulation of the water orientation distribution with respect to graphene (as shown in Figure 4d). In conclusion, we used experimental, analytical, and simulation studies to demonstrate for the first time that the WCA of graphene can be modulated by doping. The WF

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ACKNOWLEDGMENTS This work was financially supported by the Air Force Office of Scientific Research/Asian Office of Aerospace Research Development (AFOSR/AOARD) Nano Bio Info Technology (NBIT) Phase III Program (AOARD-13-4125), the AFOSR under award number FA9550-16-1-0251, and by the National Science Foundation (NSF) CAREER Award 1554019. Y.W. and N.R.A. were supported by the AFOSR under Grant FA9550-12-1-0464 and by the NSF under grants 1264282, 1420882, 1506619, and 1545907. Experiments were carried out in part in the Frederick Seitz Materials Research Laboratory Central Research Facilities, Micro and Nano Technology Laboratory and the Beckman Institute Imaging Technology Group at the University of Illinois at Urbana−Champaign. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation Grant Number OCI-1053575. This research is part of the BlueWaters sustained-petascale computing project, which is supported by the National Science Foundation (awards OCI-0725070 and ACI-1238993) and the state of Illinois. Blue Waters is a joint effort of the University of Illinois at UrbanaChampaign and its National Center for Supercomputing Applications. We thank S. Robinson and S. MacLaren for support with E-SEM and AFM measurements, respectively. The advice of G. Mensing and M. Hansen concerning graphene sample preparation is gratefully acknowledged. We thank P. Kang, J. Leem, and D. Lisk for assistance D

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(31) Cheng, C.-C.; Yeh, J. A. Opt. Express 2007, 15 (12), 7140−7145. (32) Hong, G.; Han, Y.; Schutzius, T. M.; Wang, Y.; Pan, Y.; Hu, M.; Jie, J.; Sharma, C. S.; Muller, U.; Poulikakos, D. Nano Lett. 2016, DOI: 10.1021/acs.nanolett.6b01594.

with artwork preparation. We acknowledge the support of I. W. Jung, R. E. Koritala, and N. J. Zaluzec at Argonne National Laboratory with E-SEM, AFM, and Raman spectroscopy.

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NOTE ADDED IN PROOF We have recently become aware of a related work (ref 32).

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DOI: 10.1021/acs.nanolett.6b02228 Nano Lett. XXXX, XXX, XXX−XXX