Electrostatic Control over the Electrochemical Reactivity of Graphene

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Cite This: Chem. Mater. XXXX, XXX, XXX−XXX

Electrostatic Control over the Electrochemical Reactivity of Graphene Kai-Wen Chang,† Ian Alvarez Santos,‡ Yen Nguyen,‡ Yen-Hsun Su,† Chia Chen Hsu,§ Ya-Ping Hsieh,*,∥ and Mario Hofmann*,‡ †

Department of Material Science and Engineering, National Cheng Kung University, Tainan 70101, Taiwan Department of Physics, National Taiwan University, Taipei 106, Taiwan § Department of Physics, National Chung Cheng University, Chiayi 62102, Taiwan ∥ Institute of Atomic and Molecular Sciences, Academia Sinica, National Taiwan University, Taipei 106, Taiwan

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‡

S Supporting Information *

ABSTRACT: Graphene has shown great potential as electrochemical electrodes in energy storage and sensor applications due to its unique combination of semiconducting and metallic properties. We here demonstrate that graphene’s semimetallic nature imparts it with a continuously tunable electrochemical reactivity. Extrinsic doping was shown to modify the reaction rate of graphene microelectrode arrays and a direct correlation between graphene’s linearly varying density of states and its electron transfer rate was established. Dynamic control of the charge transfer process enabled the variation of graphene’s reaction rate over 1 order of magnitude and was confirmed by a simple Gerischer−Marcus charge transfer kinetics model. The observed fine control over graphene’s electrochemical properties enabled a 2-fold increase in the resolution of an electrochemical impedance sensor. These results not only explain previous observations of graphene’s spatially varying electrochemical reactivity and highlight the importance of doping control in graphene-based electrochemical applications but also open up exciting routes for combining electronics and electrochemistry in novel sensors and actuators.

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applied to energy storage and sensor applications7 and it is thus necessary to clarify if the Fermi-level position is a significant parameter in optimizing and maintaining its performance. Finally, the dynamic control of graphene’s reactivity could enable new applications in sensors similar to breakthroughs in optical sensors8 and electronic devices9 that rely on the same mechanism. We here demonstrate that a variable electrochemical reactivity can be observed in doped graphene. A clear correlation between the doping-induced Fermi-level shift and the reaction rate can be seen under identical conditions. Dynamical control over the doping by an electrostatic gate was shown to modify the reactivity by 1 order of magnitude. This control can be applied to enhance the performance of graphene-based electrochemical sensors. These results answer fundamental questions on the origin of previously observed variations in the reactivity of graphene,10,11 and open up a new research area at the intercept between electronics and electrochemistry.

INTRODUCTION Graphene has shown great promise in electrochemistry due to its high surface area, its inertness to corrosion and its high electron transfer efficiency.1 The property that sets it apart from other metals and other 2D materials, however, is its semimetallic nature.2 Different from other investigated 2D materials it exhibits a continuous density of states and can provide efficient electron transfer kinetics with a wide range of materials.3 Different from metals, however, graphene’s low density of states around the Dirac point allows adjustment of the Fermi level over a large range resulting in a varying enhanced conductivity.4 The question arises, if these semimetallic properties can be observed in the electrochemical response of graphene. It is expected that a Fermi level tuning would modify the electrochemical reactivity of graphene similar to a semiconductor,5,6 albeit on a smaller scale due to a linear change in graphene’s density of states. The observation of such a field-tunable tunable reactivity would have several important implications. From a fundamental perspective, a clear evidence of the interplay between graphene’s electronic structure and its electrochemical properties would enhance the understanding of the charge transfer process at interfaces. Moreover, graphene is already being © XXXX American Chemical Society

Received: July 24, 2018 Revised: September 18, 2018 Published: September 19, 2018 A

DOI: 10.1021/acs.chemmater.8b03152 Chem. Mater. XXXX, XXX, XXX−XXX

Article

Chemistry of Materials

Figure 1. (a) Schematic of graphene microelectrode array. (b) Raman G-band vs 2D-band position for different electrodes obtained by averaging 100 spectra for each electrode. (c) Representative cyclic voltammograms for different electrodes obtained at a scan rate of 0.1 V/s. (d) Peak position vs scan rate for two selected electrodes that correspond to highlights in panel b.

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RESULTS AND DISCUSSION Previous reports could not identify a field effect on the reactivity of graphene12 and suggested that this issue might arise from the limited electrostatic control over the Fermi-level. We therefore hypothesized that chemical doping could reveal the change in reactivity because such strategies can modulate the Fermi level over larger ranges than electrostatic means.13 In fact, unintentional doping of graphene by the environment and the substrate have been reported to result in significant and inhomogeneous charge transfer.14 To test this hypothesis, we produced a microelectrode array from one sheet of CVD-grown graphene (Figure 1a). 52 graphene electrodes were formed that should exhibit identical properties, because they originate from the same graphene sheet. Statistical Raman spectroscopic characterization, however, indicates a large variation in the average G-band and 2Dband peak positions for different electrodes (Figure 1b). From the extend of the shift, we estimate a variability in the Fermi level between electrodes of approximately 0.3 eV.15 This number agrees with Hall effect measurements of the carrier concentration variability in CVD graphene.16 When analyzing cyclic voltammograms of those different electrodes, we observe large variations in the peak shape (Figure 1c), which suggests varying degrees of reversibility of the redox reaction. Scan rate dependent measurements of the anodic peak position (Figure 1c) reveal different slopes for each electrodes that confirm a variation in the reaction rate of electroactive species17 across the graphene sheet (more details in the Supporting Information). Such changes could originate from changes in the heterogeneous charge transfer rate or the diffusivity of the electrolyte. Neopolarograms were employed to extract the diffusivity (more details in the Supporting Information) and no correlation of the diffusivity with the peak separation was observed (Supporting Information, Figure S3), which indicates that the observed behavior is due to the changes in charge transfer rate.

Quantitative charge transfer rates were extracted from the scan-rate dependent peak separation following Laviron17 (more details are provided in the Supporting Information, Figure S3). We observe a clear correlation with the Raman Gband position (Figure 2a). The absence of such a correlation

Figure 2. (a) Relation between average G-band position and electron transfer rate for different electrodes. (b) Schematic of graphene’s band structure and overlap with reactant’s density of states at maximum reactivity.

with graphene’s defectiveness (Supporting Information, Figure S4) confirms that the observed variability in reaction rate is not due to structural differences or changes in the concentration of surface contaminants between electrodes. According to the Gerischer−Marcus model, the trend between doping and reactivity can be explained by a changing density of states in graphene (DOSG) upon doping.5 B

DOI: 10.1021/acs.chemmater.8b03152 Chem. Mater. XXXX, XXX, XXX−XXX

Article

Chemistry of Materials k = vn

∫ εred(E)f (E − EFermi)DOSG(E)W0(E − η)dE (1)

where f(E − EFermi) is the Fermi distribution and W0(E − η) is the density of states of the reactant at overpotential η (Figure 2b). Graphene’s linear dispersion results in a dependence of the density of states on energy according to18 DOSG =

2E π ℏ vFermi 2 2

(2)

where vFermi is the Fermi velocity in graphene. Thus, a decrease in Fermi level under p-doped conditions will increase graphene’s DOS and thus the overlap with the oxidized states of the reactant. At the highest reactivity the formula simplifies to k max(η = Ef ) =

1 + 2π λkT Ef 8kT

(3)

where λ is reorganization energy of ferrocene (more information about the calculation can be found in the Supporting Information). This simple analytical model can thus explain the observed linear relationship in Figure 2b because the G-band position is directly proportional to the Fermi level.15 To our knowledge, this is the first quantitative correlation between a semimetal’s electrochemical reactivity and its electronic structure and provides clear evidence for previous observations that graphene’s reactivity can be adjusted in a similar fashion as a semiconductor.19 In agreement with the comments from previous publications, the variation in reactivity is only 5-fold over the relatively large doping window, which is significantly smaller than for semiconducting MoS2.12 These results indicate that proper control over graphene’s doping concentration is required to obtain reproducible device performance in sensors and electrodes. Moreover, our findings can explain previous observations that the reactivity of graphene’s basal plane is not homogeneous,10,20 because it is controlled by the morphology and character of dopants on graphene.21 This is especially important for electrochemical sensor arrays where each sensor is expected to behave the same. To achieve such a characteristic, care has to be taken to ensure the uniformity of doping throughout the sample. The observed dependence of reactivity on electrostatic conditions, however, also represents an opportunity to realize fine control over the electrochemical process. For this purpose, we introduce an electrostatic gate in the vicinity of the graphene that is insulated from the electrolyte (Figure 3a). Previous reports had experienced difficulties in observing an appreciable change in reactivity due to the mismatch between the energy levels of the reactant and graphene.12 To avoid this, we employed mildly doped graphene whose Fermi-level is approximately 0.3 eV below the Dirac point. Transconductance plots indicate that the Dirac point is outside of the doping range that can be modulated by the gate (Supporting Information, Figure S5). Under these conditions, we observe a significant change of the position and peak current with gate voltage (Figure 3b). These results confirm that the reaction rate of graphene can be dynamically adjusted by varying graphene’s Fermi level. Figure 3c demonstrates the expected linear trend of the reaction rate on the Fermi level and shows that variation of the Fermi level by 200 meV can adjust the reactivity over 1 order of magnitude. We also observe that the

Figure 3. (a) Schematic of sample structure during electrostatic gating experiments. (b) Peak shift and peak current vs gate voltage. (c) Extracted electron transfer rate vs Fermi level.

reactivity close to the Dirac point deviates from the simple ̀ linear equation which could explain why no change in reactivity was observed previously.12 The presented novel ability to modify the reactivity of an electrode by a small amount can be applied in novel electrochemical sensors with improved performance. In many cases, the sensitivity of electrochemical sensors is determined by random variations in the experiment over time, which cannot be easily accounted for. As an example, when collecting electrochemical impedance spectroscopy (EIS) for 10 times, we observe a large variation in the Nyquist plots (Figure 4a). Fits to a Randles circuit (inset Figure 4a) show that these changes are caused by variations in the interfacial resistance of approximately 5%. The application of a gate voltage is expected to affect this interfacial resistance (Rinterface) due to the inverse dependence of this parameter on the reaction rate.22 Indeed, we obtain a linear dependence of the Rinterface value on gate voltage (Figure 4b). This trend suggests that the change in reaction rate is small enough to not significantly affect the distribution of reactants in the solution which is a marked difference to semiconductors where small gate modulations fundamentally alter the charge transfer kinetics. By exploiting the small response, we can thus linearize the complex process and extrapolate toward the interfacial resistance at zero gate voltage. Even in the presence of noise, we extract an error in the intercept of the fitted line of 2%, which shows that this process results in a 2-fold improvement of the error compared to averaging multiple spectra. Moreover, C

DOI: 10.1021/acs.chemmater.8b03152 Chem. Mater. XXXX, XXX, XXX−XXX

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Chemistry of Materials

graphene’s reactivity is expected to be independent of the number of defects.5 Gold electrodes were patterned onto silicon wafers with a 90 nm thermal silicon oxide layer by photolithography using the design shown in Figure 1a to allow individual access to each electrode while maximizing the packing density. Subsequently, the graphene was transferred onto the sample following previous reports26 using polymethyl metacryalate as mechanical support that was removed by immersion in acetone. After transfer, a second lithography step was employed to define the graphene electrode areas and the exposed graphene was removed by oxygen plasma. Finally, 100 nm thick aluminum oxide patterns were deposited to serve as electrical isolation of the interconnects from the environment (Supporting Information, Figure S10). Electrochemical characterization was conducted inside a miniature reactor using a CHI-660 potentiostat that was connected to micropositioners and an Ag/AgCl reference electrode (Supporting Information, Figure S9). The electrolyte for CV experiments corresponds to previous reports27 and consisted of 0.1 M Bu4NPF6 and 1.0 mM ferrocene in acetonitrile. Prior to use, the electrodes were electrochemically cleaned by sweeping the potential between 0.1 and 0.9 V until no change in reactivity was observed.

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Figure 4. (a) Electrochemical impedance spectra of graphene electrode over time showing large variability (inset) Randles circuit that accounts for the impedance of the electrodes (R1,C1), the electrolyte resistance Rs, and the inhomogeneous interfacial charge transfer impedance (Rinterface, CPEinterface, Winterface). (b) Rinterface as a function of applied gate voltage compared to variability in Rct from panel a.

* Supporting Information

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.chemmater.8b03152. Detailed sample fabrication, transparency measurement, Raman characterization, transfer reaction rate calculation, diffusion simulation and cyclic voltammetry result fitting (PDF)

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outliers from the linear trend can be more easily identified and excluded from the data, resulting in further improvements in accuracy. In conclusion, we have demonstrated that graphene’s electrochemical reactivity is determined by the position of its Fermi level. The intrinsic and spatially varying change of this parameter in chemically doped graphene can explain previous observations of graphene’s variable reactivity and has to be considered when applying graphene in electrochemistry. Dynamic control over graphene’s reactivity could be exerted by an electrostatic terminal and a modification of graphene’s reactivity by 1 order of magnitude was observed and explained by an increasing density of states upon gating. The presented ability to finely control graphene’s reactivity by electrostatic gating was applied to electrochemical impedance sensors and resulted in a significant enhancement of their performance which highlights the potential of this approach for future devices at the intersection of electronics and chemistry.

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ASSOCIATED CONTENT

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AUTHOR INFORMATION

Corresponding Authors

*M. Hofmann. Email: [email protected]. *Y.-P. Hsieh. Email: [email protected]. ORCID

Kai-Wen Chang: 0000-0002-1482-9069 Chia Chen Hsu: 0000-0002-3014-8829 Ya-Ping Hsieh: 0000-0002-6065-751X Mario Hofmann: 0000-0003-1946-2478 Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This research was supported by Ministry of Science and Technology, R.O.C. (No. 104-2112-M-002-026-MY3 and 1042112-M-194-002-MY3).

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EXPERIMENTAL SECTION

REFERENCES

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DOI: 10.1021/acs.chemmater.8b03152 Chem. Mater. XXXX, XXX, XXX−XXX