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Defect-Driven Heterogeneous Electron Transfer between Individual Graphene Sheet and Electrode Yi Xiao, Yi Su, Xiaodong Liu, and Weilin Xu J. Phys. Chem. Lett., Just Accepted Manuscript • DOI: 10.1021/acs.jpclett.9b02134 • Publication Date (Web): 28 Aug 2019 Downloaded from pubs.acs.org on August 30, 2019

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The Journal of Physical Chemistry Letters

Defect-Driven Heterogeneous Electron Transfer between Individual Graphene Sheet and Electrode Yi Xiao,1,2 Yi Su,1 Xiaodong Liu,1,2 and Weilin Xu*,1 1State

Key Laboratory of Electroanalytical Chemistry and Jilin Province Key Laboratory of Low

Carbon Chemical Power, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin 130022, P. R. China. 2University

of Science and Technology of China, Hefei, Anhui 230026, P. R. China.

AUTHOR INFORMATION Corresponding Author *E-mail: [email protected].

ABSTRACT. Understanding the heterogeneous electron-transfer (ET) kinetics on graphene is essential for its extensive applications. Here, based on the redox-induced fluorescence variation of monolayer graphene itself, the heterogeneous ET kinetics at the interface between electrode and the monolayer graphene was studied label-freely at single-sheet level. By tuning the defect density on graphene, an optimal heterogeneous ET rate was observed at a moderate defect density, indicating a defect-driven ET kinetics. The heterogeneities of both the intrasheet and intersheet ET kinetics were revealed at single-sheet level. With the optimal defective graphene sheets as sensing material for oxygen gas, a cost-effective electrochemical oxygen sensor was

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obtained with high sensitivity, fast response/recovery and remarkable durability. The results obtained here deepen our understanding to the electrochemical properties of graphene and imply that a rational defect control can enhance the ET process between electrode and graphene, and then improve the performance of graphene-based functional materials or devices.

TOC GRAPHIC

KEYWORDS. Defective graphene, Electron transfer kinetic, Electrode, Single molecule fluorescence microscopy Graphene has fascinated the scientific community due to its useful properties1-6 and applications such as nanoelectronic devices,7 biosensing8 and energy conversion/storage.9 In the field of electrocatalysis, defects on graphene have attracted great interest due to their positive effects on catalysts.10-16 Therefore, understanding impacts of defects on electron transfer/transport (ET) kinetics of graphene is significant for guiding the design of ideal catalysts. As an electroactive material, typically there are three different ET processes on graphene as shown in Scheme 1. One (Scheme 1a) is the electron transport (ET) process along the graphene basal plane, which has been studied extensively via field effect transistor.1,4,17 The second (Scheme 1b) is the heterogeneous electron transfer (ET) process at the interface between supported graphene and


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electroactive probe molecules (such as FcMeOH, Fe(CN)63-, and Ru(NH3)2+) in solution, which has also been studied widely.18-24 The third one is the heterogeneous electron transfer (ET) process at the interface between electrode and graphene sheet (Scheme 1c). Obviously, the completed understanding to the whole ET process (Scheme 1) on graphene can help its extensive application, from surface modification25 to (electro) catalysis.26 By now, the defect effects on the first two ET processes (Scheme 1a, b) on graphene have been studied before,27, 28 while little work has been done to probe the defect effect on third ET process (Scheme 1c).

Scheme 1. Electron transfer/transport process on graphene. (a) Electron transport (ET) process along the graphene basal plane studied via field effect transistor. (b) Heterogeneous electron transfer (ET) process at the interface between graphene and probe molecules in solution. (c) Heterogeneous electron transfer (ET) process at the interface between graphene and substrate electrode. In this work, with the redox-induced fluorescence variation of individual graphene sheet as a probe,29 by combining single-molecule fluorescence microscopy (SMFM) with electrochemical method, we in situ study the ET kinetics at the interface between electrode and the individual


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monolayer graphene nanosheets (Scheme 1c). By tuning the defect density on graphene sheet, we observe the defect-driven heterogeneous ET kinetics. Both the intrasheet and intersheet ET kinetic heterogeneities on graphene are also revealed. Moreover, with the defective graphene sheets as sensing materials for oxygen gas, a cost-effective electrochemical oxygen sensor was obtained with high performance. These results indicate that a rational defect control can maximize the ET process between electrode and graphene, and then improve performance of graphene-based functional materials or devices. Monolayer graphene oxide (GO) (Figure 1a, c) was synthesized by a modified Hummers method.30, 31 Defects were introduced onto such GO sheets by creating surface holes via a plasma etching method.32 The holes could be seen clearly in the basal plane of GO from AFM images (Figure 1b).33 TEM images showed that the average size of the visible holes on GO (HGO) sheets increased with the etching time (Figure 1c-f). Three types of HGO (named as HGO-50, HGO-100, and HGO-200) were obtained with average pore sizes of about 50 nm, 100 nm, and 200 nm, respectively. Raman analysis confirmed the formation of more defects on GO with larger pores as indicated by the calculated defect density (nD, cm-2) (SI, Figure S1 and Table S1). Typically, cyclic voltammetry (CV) of HGO on ITO electrode showed a pair of oxidationreduction peaks in the range of -1 to 1 V vs. SCE (Figure S2). As expected, the ensemble in-situ fluorescence spectra of GO samples (Figure S3) showed that the redox recycling of GO could induce the on/off-recycling of GO fluorescence.29


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Figure 1. (a) Typical AFM image of monolayer GO sheet and (b) HGO sheet with thickness of around 0.7 nm; scale bars are 1 μm. TEM images of (c) GO, (d) HGO-50, (e) HGO-100, and (f) HGO-200 sheets; scale bars in (c-f) are 200 nm. For a single particle experiment under SMFM, a home-built microfluidic electrochemical cell (Figure 2a) was fabricated to directly observe the redox-induced fluorescence variation of individual GO sheet. The as-prepared GO sheet was dispersed on the working electrode (WE) of an indium tin oxide (ITO)-coated quartz slide. A Pt foil and a saturated calomel electrode were used as counter electrode (CE) and reference electrode (RE), respectively. The fluorescence of individual GO sheet excited by a 532 nm green laser was detected by an EMCCD camera. As shown in Figure 2b, when a positive voltage (+0.8 V) was applied, the fluorescence intensity increased gradually until saturation (P1), corresponding to the oxidation process of GO sheet under high positive voltage. After the voltage switched to -0.8 V, the fluorescence intensity declined rapidly to the lowest value (P2), resulting from the reduction of GO, namely, yielding rGO. Then, when +0.8 V was applied again, the fluorescence intensity increased to a maximum (P3) due to the reoxidation of rGO. The reversible fluorescence variation could be attributed to an intrinsically reversible redox ET process.29 It should be noted here, due to the photobleaching


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of fluorophores by continuous laser irradiation, the maximum intensity P3 was slightly lower than that of P1.

Figure 2. (a) Scheme of experimental setup for single-molecule electrocatalysis. WE: working electrode, RE: SCE, CE: Pt foil. (b) Fluorescence trace of an as-prepared GO sheet under applied periodic voltage. Inset: typical images of one GO sheet at different time. (c) Positive voltagedependent fluorescence time traces of HGO-100 sheet; solid lines are corresponding singleexponential fits. (d) Negative voltage-dependent fluorescence time traces of HGO-100 sheet; solid lines are corresponding single-exponential fits. To understand the ET kinetics of redox process occurring at the interface between electrode and graphene sheets, we monitored the fluorescence variation of individual GO/HGO sheets under applied voltages. Figure 2c displayed the time traces of fluorescence intensity from four individual sheets of HGO-100 at different positive voltages (+0.2, +0.4, +0.6, +0.8 V). Due to the electro-oxidation of GO (or the electron transfer from GO to electrode), the fluorescence intensity increased gradually, and the higher voltage corresponded to a faster increase. Similarly, at negative potentials, due to the reduction of GO (or the electron injection from electrode to


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GO), the traces showed a faster descent under more negative voltages (Figure 2d). Analogous voltage-dependent fluorescence behaviors were also observed in the fluorescence response of other GO samples (Figure S4). From the fluorescence variation kinetics of individual GO sheets, the ET rates (ko for oxidation process and kr for reduction process) during the redox process were quantified 29 by fitting the data of the first 30 s in traces (Figure 2c, d) with single exponential rise or decay functions to avoid the possible effect of photobleaching.34, 35 For the case here, corresponding oxidation rates (ko) and reduction rates (kr) of different graphene samples were expectedly dependent on applied voltage (Figure 3a, b), where both rates increased with the augment of voltage. Interestingly, all the HGO samples exhibited faster ET rates than those of GO samples, in both oxidation process and reduction process, indicating that defects on graphene sheets could make a positive effect on ET kinetics. Furthermore, based on Butler-Volmer model for ET kinetics,36 the standard rate constants of the oxidation (k0o) and reduction (k0r) process for all of graphene samples were calculated using: ko ∝ k0o exp ( (1-α) f E) kr ∝ k0r exp (-α f E)

(1)

(2)

where α and E were the transfer coefficient and driving potential, respectively. In this case, the α was assumed to be 0.5 in the redox kinetic studies on graphene.28 The obtained results from individual sheets exhibited significant heterogeneous ET activity during redox process for all graphene samples (Figure S5). Statistically, as shown in Figure 3c and Table S1, initially, the standard rate constants for both oxidation and reduction process increased with the increase of defect density, after a maximum on HGO-100 sheets, the standard rate constants decreased


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inversely with the further increase of defect density, unambiguously indicating that an optimal ET kinetics could be achieved at a moderate defect density on GO.21, 37, 38 Such defect densitydependent ET kinetics was further confirmed by electrochemical impedance spectroscopy (EIS) measurements (Figure S6), which showed that the ET resistances of GO samples with different defect densities follow the same trend as the measured standard rate constants shown in Figure 3c.39 Such positive effect of defects on the ET kinetics of graphene might be due to the charge carrier hopping and tunneling from highly conducting graphene regions to disordered regions at high local electric fields.40, 41 Significantly, above results could explain the observed positive effect of carbon defects on graphene- or carbon-based devices or functional materials.18, 21, 42

Figure 3. Kinetic analysis of electro-redox process for GO, HGO-50, HGO-100 and HGO-200 sheets. (a) Voltage-dependent oxidization rates (ko). (b) Voltage-dependent reduction rates (kr). (c) Histogram of standard ET rate constants for oxidation and reduction process (k0o and k0r). (d) ko distributions of edge and center region on individual graphene sheets (+0.8 V); solid lines are Gaussian fits. (e) kr distributions of edge and center region on individual graphene sheets (-0.8 V); solid lines are Gaussian fits. The error bars are standard deviations of the ET rate constants.


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At the single-sheet level, we further studied the heterogeneity of ET kinetics among different regions across the same graphene sheet by extracting the redox ET rates from the centers (ko,c and kr,c, Figure S7) and edges (ko,e and kr,e, Figure S8) of individual sheets (Figure 3d,e). As expected, among these different GO samples, the HGO-100 exhibited the highest ET rates for both the oxidation and reduction process on both the centers and edges of individual GO sheets, and the reduction process on all these GO samples was faster than the oxidation process, all consistent with the observation shown in Figure 3c. Significantly, it also could be seen that the ET process on center was much faster than that on edge, indicating the heterogeneity of ET kinetics among different regions across the surface of graphene sheet. Besides that, Figure 3d,e also showed that the magnitude of the intrasheet inhomogeneities of ET process on GO could be tuned precisely by the surface defect density as indicated by the observed largest inhomogeneities on HGO-100.23 Such fact suggested that an appropriate amount of defects on GO could maximize the intrasheet spatial heterogeneity of ET kinetics. The fastest ET kinetics and the largest ET inhomogeneities observed simultaneously on HGO-100 probably indicate that the fast ET process on defective GO could disturb the microstructure of GO, while such disturbance of the microstructure then could reversibly promote the ET process on GO.43,44 The intrasheet ET kinetic variation of individual GO sheets was further highlighted in detail through the 2D mapping of redox rates as shown in Figure S9. These maps were obtained by extracting values from individual pixels (a bin size of 2 × 2 pixels) on the whole graphene sheet in both oxidation and reduction process. From these maps, the active areas (red regions) and inactive areas (blue regions) on individual graphene surface could be seen clearly. Initially, the active area on individual GO sheet increased with the introduction of defects (from GO to HGO-


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50), and then reached a maximum (from HGO-50 to HGO-100), after that, it decreased inversely when the defect density on GO was too high (from HGO-100 to HGO-200). Such observed enhancement of active area could be related with the surface roughness of graphene sheets.45, 46 The introduction of defects could unavoidably create surface cracks and corrugations (as demonstrated by AFM and TEM images shown in Figure 1), which could activate the ET process through generating significant curvature and strain at atomic scale.47, 48 While the inverse decrease observed on HGO-200 could be due to its low charge carrier mobility,22, 49 which was most likely owing to the destruction in the electronic structures of GO by the excessive formation of holes or defects. The effect of defects on intersheet heterogeneity among multiple individual as-prepared graphene sheets was further studied. Figure S10 displayed the redox fluorescence trajectories from 78 individual sheets for each graphene sample. From these traces, the redox ET rates of each sample were shown statistically in Figure S11. As expected, Figure S11 showed that the ET rates for both oxidation and reduction process could be enhanced by the introduction of an appropriate amount of defects on GO, consistent with above observation at sub-particle level (Figure 3). For each type of GO, it showed that the ET rates vary across individual sheet and distribute widely as indicated by the Gaussian curve. The wide distributions shown in Figure S11 indicated the heterogeneities of samples in morphology and size of as-prepared graphene sheets, while the differences in local electronic structure and surface properties caused by defects could also play an important role in the wideness of ET kinetics.50 Moreover, based on above observed defect-driven ET, these defective graphene sheets were adopted as sensing materials for practical electrochemical oxygen sensors as shown in Figure 4a (Supporting Information, Figure S12).51 Figure 4b shows the responses of as-prepared GO and


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HGO to 100 ppm of oxygen gas at controlled potential of 0.7 V. From the response currents (Figure 4b), the response/recovery times (Figure 4c) and the long-term durability (Figure 4d) of different sensors, one can deduce the following order of sensing performance: HGO-100 > HGO50 > HGO-200 > GO. Such order is consistent with the ET rate or resistance order (Figure 3c and Figure S6). Such results indicate that the high oxygen sensing performance of HGO-100 could be due to the defect-induced optimal porosity and ET process between graphene layer and electrode52 as that revealed above from single-sheet level. All these results imply that the graphene with an optimal amount of defects could be used as a cost-effective functional material for practical oxygen sensing applications.

Figure 4. (a) The photograph of electrochemical oxygen gas sensors with different graphene samples as sensing materials for oxygen (1: GO; 2: HGO-50; 3: HGO-100; 4: HGO-200); (b) I-t curve of the sensor based on GO and HGO towards 100 ppm oxygen gas (controlled potential: 0.7 V); (c) Response/recovery time of different samples; (d) long-term stability of the sensors towards 100 ppm oxygen gas.


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To summarize, at single-sheet level, we make a direct study of ET kinetics at the interface between electrode and monolayer graphene sheet without additional redox mediators. By tuning the defect density on graphene, the defect-driven ET kinetics on individual sheet is observed. The heterogeneities of both the intrasheet and intersheet ET kinetics on individual defective graphene is also revealed. Further, inspired by the results obtained at single-sheet level, a costeffective electrochemical oxygen sensor with defective graphene sheet as sensing material was obtained with high performance. These reuslts not only deepen our understanding to the electrochemical properties of graphene, but also indicate that a rational defect control can enhance the ET process between electrode and graphene, and then lead to improved performance of graphene-based functional materials or devices.

ASSOCIATED CONTENT Supporting Information Supporting Information is available free of charge on the ACS Publications website. Raman spectroscopy of as-prepared graphene sheets, in situ fluorescence spectra of different samples, cyclic voltammetry of HGO, redox kinetics of individual graphene sheets, electrochemical impedance spectra and measurements of electrochemical gas sensor. AUTHOR INFORMATION Notes The authors declare no competing financial interests. ACKNOWLEDGMENT


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This work was supported by National Natural Science Foundation of China (U1601211, 21633008, 21733004, 21721003, 2018YFB1502302, and 21433003), K. C. Wong Education Foundation and Science and Technology Innovation Foundation of Jilin Province for Talents Cultivation (20160519005JH, 20170414019JH). REFERENCES (1) Yao, B.; Huang, S.; Liu, Y.; Vinod, A.; Choi, C.; Hoff, M.; Li, Y.; Yu, M.; Feng, Z.; Kwong, D.; Huang, Y.; Rao, Y.; Duan, X.; Wong, C. Gate-tunable frequency combs in graphene-nitride microresonators. Nature 2018, 558, 410-414. (2) Yousefi, N.; Lu, X.; Elimelech, M.; Tufenkji, N. Environmental performance of graphene-based 3D macrostructures. Nat. Nanotechnol. 2019, 14, 107-119. (3) Yankowit, M.; Chen, S.; Polshyn, H.; Zhang, Y.; Watanabe, K.; Taniguchi, T.; Graf, D.; Young, A. F.; Dean, C. R. Tuning superconductivity in twisted bilayer graphene. Science 2019, 363, 1059-1064. (4) Novoselov, K.; Geim, A.; Morozov, S.; Jiang, D.; Zhang, Y.; Dubonos, S.; Grigorieva, I.; Firsov, A. Electric Field Effect in Atomically Thin Carbon Films. Science 2004, 306, 666-669. (5) Abraham, J.; Vasu, K. S.; Williams, C. D.; Gopinadhan, K.; Su, Y.; Cherian, C. T.; Dix, J.; Prestat, E.; Haigh, S. J.; Grigorieva, I. V.; Carbone, P.; Geim, A. K.; Nair, R. R. Tunable sieving of ions using graphene oxide membranes. Nat. Nanotechnol. 2017, 12, 546-550. (6) Kozawa, D.; Zhu, X.; Miyauchi, Y.; Mouri, S.; Ichida, M.; Su, H.; Matsuda, K. Excitonic Photoluminescence from Nanodisc States in Graphene Oxides. J. Phys. Chem. Lett. 2014, 5, 1754-1759. (7) Kim, S.; Jung, H. J.; Kim, J. C.; Lee, K. S.; Park, S. S.; Dravid, V. P.; He, K.; Jeong, H. Y. In Situ Observation of Resistive Switching in an Asymmetric Graphene Oxide Bilayer Structure. ACS Nano 2018, 12, 7335-7342.


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Defect-Driven Heterogeneous Electron Transfer ... - ACS Publications

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