Understanding Sources of Electrical Disorder in Graphene Grown by

Article Cite This: ACS Appl. Nano Mater. 2019, 2, 3426−3433

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Understanding Sources of Electrical Disorder in Graphene Grown by Chemical Vapor Deposition for Wafer-Scale Device Applications Qun Su and Steven J. Koester* Department of Electrical & Computer Engineering, University of Minnesota, 200 Union Street SE, Minneapolis, Minnesota 55455, United States

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S Supporting Information *

ABSTRACT: We present a comprehensive explanation of the sources of electrical disorder in graphene grown by chemical vapor deposition (CVD) and transferred onto SiO2 substrates. By correlating carrier concentration distribution to the topographical mapping, we show that, due to the embedded ripple array created by the thermal expansion mismatch during growth, graphene forms uneven charge interaction with the SiO2 substrate, causing the areas in proximity of SiO2 to have higher hole concentration while the raised regions have lower hole doping. The net disorder of graphene is, therefore, a function of the density and scale of the thermal expansion ripples. We further show that, while the ripple-induced topographical nonuniformity can be alleviated by thermal annealing, the reduced topography actually has competing effects on overall disorder. On one hand, the reduced topography decreases the concentration nonuniformity between the raised and lowered regions, but on the other hand, annealing more closely couples the entire graphene layer to impurities in the SiO2 substrate. The results show that the ripple structure is not a disorder source by itself, but only contributes to disorder via the substrate interaction. This study suggests that minimizing substrate-induced disorder is of fundamental importance to reducing electrical disorder in transferred CVD graphene, which is significant for enabling wafer-scale integration of graphene devices for electronic, photonic, and sensing applications. KEYWORDS: graphene, chemical vapor deposition, ripples, electrical disorder, Raman spectroscopy, atomic force microscopy

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INTRODUCTION Graphene, a monolayer of sp2-bonded carbon atoms arranged in a honeycomb pattern has attracted tremendous interest since its discovery1 for its unique electrical and mechanical properties. Graphene is especially interesting for electrical applications due to its high mobility,2 and monolayer thickness.1 Early works on graphene mostly used mechanically cleaved graphene from natural graphite, which possesses ultrahigh electrical mobility and minimal defects3,4 but is limited to small sizes. On the other hand, chemical vapor deposition (CVD) of graphene, first demonstrated by X. Li et al.5 allows high-quality graphene synthesis at the wafer scale on thin Cu foils, achieving ∼95% monolayer coverage. Following their work, CVD processes for graphene has been improved tremendously. Z. Yan et al. reported millimeter-sized singledomain CVD graphene with hole mobility of ∼11 000 cm2V−1s−1.6 Aside from Cu, CVD growth of graphene has also been realized on other transition metal substrates, including Ni, Ir, and Co, etc.7−9 For actual electrical applications, graphene deposited on metal foils needs to be transferred onto other substrates such as silicon and such transfer can be achieved using a polymeric handle layer and appropriate etchant to remove the metal foil.10 Despite the relative high-quality of CVD graphene, it still contains imperfections in various forms, one of which is the © 2019 American Chemical Society

embedded ripple structure resulting from thermal expansion mismatch. As illustrated in Figure 1a and b, during CVD growth of graphene at high temperatures, graphene forms a smooth layer that is conformal to the Cu surface. However, since the coefficient of thermal expansion (CTE) for graphene is negative,11 whereas the CTE for transition metals is positive and large, during the cooling stage after CVD growth, compressive strain accumulates in graphene and relaxes by forming ripple arrays (Figure 1c).12,13 A recent study has also shown that the morphology of ripples is related to the distribution of intrinsic defects such as Stone−Wales arrays and grain boundaries.14 Furthermore, these ripples are retained after transfer (Figure 1d) onto silicon substrates. Several studies have reported on attempts to reduce or eliminate ripple formation in CVD graphene. Recent works from B. Deng et al. and J. Choi et al. have demonstrated nearly ripple-free growth using strain-engineered Cu (111) single crystal substrate and textured Pt film.15,16 These approaches are, however, exotic and expensive for large-scale manufacturing. In most applications where graphene is grown at high temperatures (>1000 °C) on multicrystal Cu substrates, the embedded Received: February 24, 2019 Accepted: June 5, 2019 Published: June 5, 2019 3426

DOI: 10.1021/acsanm.9b00350 ACS Appl. Nano Mater. 2019, 2, 3426−3433

Article

ACS Applied Nano Materials

lead to graphene disorder is critical for improving many graphene applications. Disorder induced from the surrounding materials will also be discussed in this paper. Since it is known that Raman peak positions of exfoliated graphene on h-BN have a more uniform distribution than SiO2, it is clear that SiO2 induces more disorder to graphene.41 Polymer residue such as PMMA can also dope graphene to p-type,42 contributing to disorder. In this work, we primarily used Raman spectroscopy and atomic force microscopy (AFM) to deconvolve these various sources of disorder in graphene, by statistically analyzing the disorder arising from the peak and valley regions of the ripples separately. Finally, the effects of thermal annealing on this disorder were also analyzed. Results from this study provide insight into how more electrically uniform graphene can be produced, which is significant for a wide range of device applications that utilize large-area CVDgrown graphene. Raman spectroscopy is a common characterization tool for graphene. Generally, Raman spectra of graphene contain three characteristic modes: G, 2D (G′) and D modes.43,44 Among the three peaks in the Raman spectrum, the G and 2D peaks reflect the doping and strain levels in graphene.45−48 The doping dependence of the G peak can be explained by the nonadiabatic Born−Oppenheimer approximation.45,46 Substitutional doping also changes the lattice structure of graphene, causing a shift in G and 2D peak positions.43 Similarly, strain also changes the positions of the G and 2D peaks as it breaks the symmetry of the hexagonal lattice.48 Assuming that the net shift in Raman peak positions are the superposition of doping and strain effects, J. Lee et al. introduced a graphical decomposition technique that separates the doping and strain effects,33 as illustrated in Figure 2. Through this method, actual

Figure 1. (a) CVD growth process of graphene. (b) When growth completes at growth temperature, graphene has the same area as its substrate. (c) After cooling to room temperature, ripples form due to CTE mismatch (right panel: SEM image of as-grown graphene on Cu; the scale bar is 1 μm). (d) Ripple structure retains after transfer onto SiO2/Si substrate, which can be analyzed using optical and scanning probe techniques (right penal: SEM image of transferred graphene on SiO2/Si substrate; the scale bar is 1 μm).

ripple array remains an unavoidable reality. Therefore, a more in-depth understanding on how ripples affect the fundamental properties of transferred graphene is certainly necessary, and the properties of these ripples can be explored using a combination of optical and scanning probe techniques as illustrated in Figure 1d. In recent years, some reports have been published concerning the properties induced by the graphene ripples. It has been shown using Raman spectroscopy that as-grown graphene on Cu and Co substrates has a periodic variation in strain associated with thermal expansion effects,17,18 and these variations were shown to still be present after being transferred onto other substrates.17 B. Deng et al. also pointed out that strain accumulation in graphene on Cu depends on the crystalline orientation of Cu.15 Regarding electrical effects, it has been reported that ripples could induce an anisotropy in the transport characteristics of graphene-based devices,19,20 and that a well-engineered CVD process which suppresses ripple formation can enhance the electrical performance of graphene.21,22 On the atomic level, several reports have observed local variation in electrical conductivity induced by graphene rippling using scanning tunneling microscopy and scanning probe microscopy, where these variations were likely caused by the distortion in lattice symmetry in ripples.23−26 In addition, some previous studies have shown that dielectric substrates can have a doping effect on graphene,27−31 and such effects are enhanced when graphene is closer to the substrate.32−35 It was also reported that wrinkling induced by nanoparticles can induce doping effects in graphene.36 Those results suggest that CVD graphene could suffer from rippleinduced disorder due to the thermal expansion mismatch with its growth substrate, which is still not yet thoroughly studied. In this paper, we comprehensively analyze the sources of electrical disorder, especially those induced by the embedded ripple structure, in CVD-grown graphene transferred onto SiO2 substrates, a system that forms the basis of large-scale integrated graphene electronic, photonic, and sensing devices. Electrical disorder can greatly affect the performance of many of these devices. For example, the sensitivity of graphene-based biosensors can be limited by electrical disorder in graphene.37−40 Disorder also adds device-to-device variability, potentially limiting the performance of multicomplex sensing arrays. Therefore, a thorough understanding of the factors that

Figure 2. Graphical separation of the strain and doping components in Raman spectrum of graphene. The blue (red) solid line represents the ω2D and ωG correlation of zero strain (doping) graphene. The blue (red) dashed lines are lines of equal strain (doping) as labeled. In a graphical separation process, graphene spectrum is represented by a (ωG, ω2D) pair as shown by the black point. Its projections onto the zero-strain axis (blue solid line) and the zero-doping axis (red solid line) yield the pure doping component and pure strain component of the original spectrum, respectively.33

carrier concentration and residual strain can be extrapolated by projecting the spectrum (ω2D, ωG) to the doping-free line and the strain-free line. Applying this method to Raman spectroscopy mapping of transferred CVD graphene, along with atomic force microscopy (AFM), allows us to identify the microscopic features causing disorder. 3427


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RESULTS AND DISCUSSION CVD graphene samples were transferred to Si substrates with thick SiO2 on top as described in the Methods section. Raman spectroscopy mapping of an as-transferred CVD graphene layer on SiO2 is shown in Figure 3. Figure 3a and b are the G

Raman spectroscopy mapping, due to its limited spatial resolution, is not able to resolve the ripple patterns in all Cu grains.15,23 To understand the mechanism behind ripple-induced disorder further, we correlated the topographical fluctuations and carrier distribution by performing AFM and Raman spectroscopy mapping on the same area of a transferred graphene layer on SiO2. The resulting topographical image and carrier concentration maps obtained through the same process as Figure 3 are shown in Figure 4a. The blue-red color map is

Figure 3. Raman spectroscopy mapping data for as-transferred graphene on SiO2/Si substrate. (a) and (b) Position maps extrapolated from Lorentzian fitting of G and 2D peaks. (c) and (d) Carrier concentration map and strain level map computed from the doping and strain component of the original spectrum, respectively, which are obtained through the graphical separation method. The scale bar in the maps is 5 μm, and the resolution of the mapping is 4 pixels per μm.

Figure 4. (a) Carrier concentration map (resolution = 5 pixels per μm) of transferred graphene on SiO2/Si, with AFM height map of the exact same position overlays on top. The two maps are carefully aligned using the Cr/Au alignment marker and PMMA residuals. The valley stripes in AFM image aligns perfectly with the heavily p-type doped lines in the carrier concentration map. The scale bar in the map is 4 μm. The four dashed squares indicate areas used for bisection analysis, with their indices labeled. (b) 3D sketch illustrating the effect of ripple on carrier concentration distribution. The valley areas, which are closer to the substrate, receive more doping and disorder from it. Whereas the peak areas are closer to pristine graphene. (c) Carrier concentration histograms with Gaussian fitting of the peak and valley sets of all areas combined. (d) Graphene disorder as a function of the fraction of peak area simulated using data from (c). A and B are the extreme cases with zero peak area (no Gr/Cu mismatch) and zero valley area. The red arrow indicates where the studied sample locates in the curve.

and 2D peak position maps, respectively, obtained by Lorentzian fitting. An example spectrum fitting is shown in Supporting Information (SI) Figure S1. In both maps, a periodically varying pattern appears, along with some other background features. Using the graphical separation method as demonstrated in Figure 2, the doping and strain components of the G and 2D peak positions were separated, from which the actual carrier concentration and residual strain values were computed. To ensure an accurate separation, the chargeneutral positions of the G and 2D peaks were calibrated using an ionic liquid gated graphene field effect transistor (FET). Details regarding our Raman setup and this calibration are described in the Methods section. Results from the calibration are close to those described in ref 33. The carrier concentration map of the studied area in Figure 3c also has the same periodically alternating pattern. The doping disorder, defined as the full-width half-maximum (fwhm) of the Gaussian fitting of the carrier concentration histogram, is 1.83 × 1012 cm−2. Similarly, Figure 3d shows the strain level map of the studied area, though in this case, almost no clear pattern emerges. Comparing the separated carrier concentration and strain maps with the initial peak position maps, the separation process effectively filters out strain-induced factors in the initial peak position maps. These strain-related features are likely from the transfer process or large-scale background roughness on the substrate. The periodic patterns we observed in the maps clearly arise from the ripple structure, as their scale and density correspond precisely with the SEM images displayed in Figure 1. We also note that, as that ripple density and size depend on the crystalline orientation of the Cu grain,

the carrier concentration map, and the black-gold scaled map that overlays on top is a portion of the AFM height image of that area. These two maps were carefully aligned to show the position-wise doping-height correlation. The square Cr/Au alignment marker was used for alignment during the experiment. In addition, the spots with extraordinarily high p-type doping are due to PMMA residue.42 These locations were precisely correlated to the transfer residue on AFM, and used to align the two images. Both of the maps have a clear ripple pattern embedded, and together, they directly show that the hole concentration is larger (smaller) where graphene is topographically lower (higher). This agrees with the general trend of SiO2 providing p-type doping that has previously been reported in the literature.27−30,32,36 Therefore, it can be concluded that the ripple contrast in doping distribution is directly related to the graphene-SiO2 spacing, and the fact that graphene becomes more p-type doped the closer it is to the SiO2 substrate (Figure 4b). 3428


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Table 1. Summary of Bisection Analysis in the Four Areas Shown in Figure 4a before RTA (in Units of 1012 cm−2)a area no. 1

area no. 2

area no. 3

area no. 4

all combined

valley set

mean fwhm

2.76 ± 0.10 2.42 ± 0.26

2.24 ± 0.04 1.51 ± 0.10

2.41 ± 0.04 1.30 ± 0.11

2.39 ± 0.06 1.87 ± 0.16

2.40 ± 0.04 1.61 ± 0.10

peak set

mean fwhm

1.46 ± 0.03 1.09 ± 0.07

1.70 ± 0.05 1.44 ± 0.12

1.62 ± 0.05 1.50 ± 0.12

1.74 ± 0.04 1.47 ± 0.11

1.61 ± 0.04 1.35 ± 0.09

The bin size for histogram generation was set to be 0.5 × 1012 cm−2 for all data sets.

a

Figure 5. (a) and (b) Upper panel: AFM image (color bar range is −5 to 15 nm) of the studied sample before and after annealing; lower panel: carrier concentration map (color bar range is 0 to 8 × 1012 cm−2) before and after annealing. The black curves are the carrier concentration distribution along the black dashed lines in the lower panel. The range of the two curves is 0 to 6 × 1012 cm−2. The scale bars in the carrier concentration maps are 4 μm. (c) 3D height profile of the area marked by the black square in (a) and (b). The black arrows indicate the ripples. (d) Height histogram of the area studied in (c) before (blue curve) and after (red curve) RTA. The arrows indicate the height difference between the valley and peak areas.

We ascribe this to the fact that graphene interacts more strongly with charged impurities in the SiO2 when it is closer to the SiO2.41 Therefore, in Figure 4b, the doping profile in the valley areas has higher variation. We also notice that PMMA residue has minimal effect on the overall disorder as it populates only on the tail right of the histogram. A complete set of the bisected statistical results of each individual area is shown in SI Figure S3 and Table 1. The two trends discussed are consistent in all four areas, considering the fitting error. It should be pointed out that, due to the limited spatial resolution of Raman spectroscopy mapping, alignment of the two maps is still imperfect, which systematically induces errors in labeling the peak and valley areas. Additional discussion of the fitting error is described in the Supporting Information related to SI Figure S4. It is worth noting that fine-grained height variations in graphene could produce side peaks in the G and 2D modes if the Raman spectrum simultaneously captures signals from areas with different doping.36 In this study, however, the period of the ripple features is large enough that our Raman system is mostly able to separate out these periodic doping variations, and in the boundary regions, the doping difference between the valley and peak areas is too small to be resolved from a single spectrum. The statistical analysis shows that the ripple structure has little-to-no intrinsic effect on doping disorder. Clearly, it is the differential interaction with the substrate that leads to the periodic concentration variation.

The correlation result suggests that graphene consists of two distinct sets according to its ripple structure: the valley set that is topographically lower but more p-type doped, and the peak set that is physically higher but more neutral in doping. We thus labeled the Raman spectroscopy mapping data according to the AFM image to analyze the valley and peak sets separately. However, owing to the resolution limit of Raman mapping, aligning all pixels on the 20 × 20 μm2 carrier concentration map could be extremely difficult and unrealistic. Instead, four 4 × 4 μm2 portions of the map were selected for this analysis, as marked by the black dashed squares in Figure 4a. Each square is centered at a piece of PMMA residue that is noticeable in both carrier concentration and AFM maps. The bisection process generates a binary label map for each area (see SI Figure S2 for complete data). Combining all the four sections with all duplicated data points being removed, in Figure 4c, the carrier concentration histograms of the valley and peak sets are plotted, together with their Gaussian fittings. Several trends can be observed in the histograms. First, the valley and peak sets have a noticeable separation of 0.79 × 1012 cm−2 in the hole concentration, which corresponds to the difference in doping caused by the topographical ripple terraces. Second, the fwhm of the valley set (1.61 × 1012 cm−2) is higher than that of the peak set (1.35 × 1012 cm−2), which suggest that the graphene in contact with the SiO2 is more disordered than in the raised areas created by the ripples. 3429


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closely as possible using the PMMA cluster on the right end to represent the same positions before and after RTA. The fluctuation in carrier concentration is clearly smaller. The observations in the topography and doping domains are consistent with expectations based upon Figure 4b. Since the RTA heals the topography caused by the ripples, doping variation across ripples is also suppressed. In order to quantify the above observations, the valley and peak areas were analyzed separately using the Raman spectroscopy mapping and AFM data after RTA. This analysis was performed on the exact same four areas indicated in Figure 4a. Although annealing removes a fair amount of PMMA residuals, the ones used for position alignment were still attached, which assures the comparison is made at the same locations. The valley areas on the AFM after RTA are almost exactly the same as before RTA (SI Figure S2). Therefore, the binary maps generated in the previous bisection analysis (Figure 4) were used again after annealing. The carrier concentration histograms of all four sections combined (with all duplicated points being removed) are shown in Figure 6b,

The data so far suggest a duality in the role played by ripples on disorder. On one hand, the ripple structure produces a bimodal distribution of the doping, causing disorder to increase. On the other hand, the elevated peak regions of the ripples have reduced disorder due to the weakened substrate interactions. As a result, the total disorder is a function of the areal fraction of the ripple peaks, which is mostly determined by the degree of CTE mismatch between graphene and Cu. Ripples triggered by intrinsic defects (Stone−Wales arrays and grain boundaries) can also contribute to the amount of peak area, if the rippling is strong enough.14 To compute such a dependency, the peak and valley data sets in Figure 4c were rescaled to simulate graphene with different amounts of peak area fraction. The two rescaled sets were then combined to extract the total disorder in each through a Gaussian fitting, as shown in Figure 4d. The plot shows that disorder increases with as peak area fraction increases (section I). The reason is that the split between peak and valley sets becomes more predominant when their sizes become comparable. However, at some point the disorder reaches a maximum but then starts decreasing as the peak regions begin to dominate. The two extreme cases, A and B correspond to graphene with only valley areas (exact match between graphene and Cu, closer to substrate), and only ripple peak areas (more separated from substrate), respectively. Their difference reflects the amount of disorder received from the substrate when graphene-SiO2 separation decreases by the amount of the ripple step height. The roll over in the trend manifests the competition between the splitting and “screening” effects caused by ripples. The red arrow indicates disorder of the sample used in this study (with fraction of peak set of ∼0.77). Although the trend predicts lower disorder in graphene with stronger rippling, a greater percentage of elevated regions can cause secondary problems such as reduced gating efficiency in transistors and increased intercalation in sensors.38 Thermal annealing is a common post-transfer treatment to graphene. Studies have demonstrated that annealing removes polymer residue attached to the graphene surface,42,49,50 enhances the coupling of graphene to SiO2,51,34 and shifts the doping in graphene to be more p-type.33,35 In this study, we investigated the effect of thermal annealing on electrical disorder, especially as it relates to the ripples. As a rigorous control, the same sample studied in Figure 4a was subjected to rapid thermal annealing (RTA) at 350 °C 15 min under Ar/H2 flow. Next, Raman spectroscopy mapping and AFM imaging were conducted in the same area studied in Figure 4a. The upper panels of Figure 5a and b compare the AFM images before and after RTA, where a lowering in the ripple terraces can be observed. As a more straightforward comparison, we tracked the area marked by the black squares in the AFM images throughout the process, and plotted its 3D height profile in Figure 5c. Ripple height was clearly reduced after annealing. Further, the height histograms of this particular area before and after RTA are plotted in Figure 5d. Each histogram contains two distinct peaks, where the short (tall) ones represent the valley (peak) area. Quantitatively, the RTA process lowers the ripples from ∼1.1 nm to ∼0.4 nm. As discussed earlier, the difference in doping of ripple valley and peak areas is caused by their height contrast. Consequently, such difference should decrease after being annealed, which is confirmed by the insets in the lower panels of Figure 5a and b showing the doping distributions of the indicated dashed lines running across the ripples. The two lines were aligned as

Figure 6. Carrier concentration histograms of the valley set (blue squares) and peak set (black squares) of all four areas combined (a) before and (b) after RTA, along with their Gaussian fitting.

compared with the same regions before RTA (Figure 6a). SI Figure S5 and Table 2 show the complete results for each area, and the trends are seen to be consistent in each section within experimental error. Overall, hole doping increases in both the two sets after annealing, but more strongly in the peak set. The gap between the two histograms therefore shrinks to 0.64 × 1012 cm−2, which agrees with the Raman line scan results in Figure 5a and b. There is also a distinguishable increase in the fwhm of the peak area histogram (to 2.11 × 1012 cm−2) upon annealing, decreasing the difference between the peak and valley set disorder. Since previous AFM analysis (Figure 5c and d) has showed that annealing drives the ripple peaks closer to the substrate, the increased peak set disorder after annealing would appear to arise from stronger interactions with the SiO2. As shown in Tables 1 and 2, these two trends occurred consistently in all studied areas. Therefore, the annealing results can be summarized as follows. Thermal annealing transferred CVD graphene on SiO2 reduces the ripple topography which causes (1) graphene to become more ptype; (2) the hole concentration difference between peaks and 3430


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ACS Applied Nano Materials Table 2. Summary of Bisection Analysis in the Four Areas Shown in Figure 4a After RTA (in Units of 1012 cm−2)a area no. 1

area no. 2

area no. 3

area no. 4

all combined

valley set

mean fwhm

3.46 ± 0.05 2.11 ± 0.13

3.33 ± 0.04 1.28 ± 0.11

3.56 ± 0.07 2.34 ± 0.21

3.16 ± 0.15 2.57 ± 0.41

3.39 ± 0.03 2.02 ± 0.07

peak set

mean fwhm

2.39 ± 0.02 1.68 ± 0.06

2.96 ± 0.06 1.80 ± 0.15

3.00 ± 0.06 2.74 ± 0.18

2.95 ± 0.02 2.01 ± 0.06

2.75 ± 0.04 2.11 ± 0.09

The bin size for histogram generation was 0.5 × 1012 cm−2 for all data sets.

a

water bath several times to remove possible etchant residual. After that, the film was carefully transferred onto a Si substrate with thermal SiO2 (300 nm) which was precleaned with solvents and an oxygen plasma. Finally, the sample was baked at 65 °C on a hot plate for 15 min to evaporate residual water, and then at 180 °C to cure the PMMA layer. The PMMA layer was removed by soaking the sample in an acetone bath overnight. Raman Spectroscopy. Raman spectroscopy was performed using a Witec Alpha 300 R confocal Raman microscopy with UHTS300 spectrometer and DV401 CCD detector. An argon ion laser source was used (wavelength = 514.5 nm). A 100× objective lens was used for optimized mapping resolution. All mappings were performed using an integration time of 0.2 s. The stage for mapping was piezoelectrically driven with 4 nm lateral movement accuracy. Field Effect Transistor (FET) Fabrication for Gated Raman Spectroscopy. Gated Raman spectroscopy was realized with locally ionic liquid gated graphene FETs on SiO2. The transferred graphene was first patterned with e-beam lithography to form channels on SiO2. The unwanted graphene was etched with oxygen plasma. Next, electrical contacts were defined with a second e-beam lithography, together with local ionic liquid gating pads. The spacing between contact fingers on the channel is >10 μm to accommodate the laser beam from Raman spectroscopy. To achieve large capacitance through ionic liquid, the local gating pads are designed to be much larger than the channels. Finally, metallization (Cr/Al/Au) was done using e-beam evaporation and metal lift-off. Ionic liquid gating was formed by carefully dropping a small amount of P14-FAP liquid on the device area. A micrograph of the finished device is shown in SI Figure S6a. After device fabrication, electrical connections to source and the local gating pads were made using wire bonding. Before Raman spectroscopy, the transfer characteristics (Id − Vg) of the graphene channels were measured with a Keysight B1500A Semiconductor Device Parameter Analyzer to identify the charge neutral point. For gated Raman spectroscopy, using a Keithley 2450 source-meter as a voltage source, bias was applied through the wire-bonded connections. The voltage was swept from −2 V to 2 V then swept backward with a step size of 0.1 V. A Raman spectrum (integration time = 5 s) was collected at each step. Through this process, G and 2D peak positions were measured at each voltage step and plotted in SI Figure S6b. The peak positions of charge-neutral graphene were determined by locating the minimum points in the plot.

valleys to decrease; (3) the peak areas to have increased disorder from the SiO2.

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CONCLUSION In conclusion, our work presents an in-depth study of the role played by the embedded ripple structure on the electrical disorder in CVD graphene, from which a full picture of the extrinsic sources of electrical disorder is obtained. In transferred graphene, PMMA residuals and SiO2 are the sources that directly induce doping and doping disorder. The ripple structure by itself does not contribute to disorder. Rather, it produces disorder indirectly by forming uneven separation between graphene and SiO2. Our results also indicate that graphene disorder depends on the fraction of the ripple peak areas, or the degree of CTE mismatch between graphene and the growth substrate. In addition, while thermal treatment heals the topographical variation from ripples, and therefore lowers the doping variation caused by the ripples, the annealing increases interactions between the graphene and SiO2, which enhances the overall substrate-induced disorder. This study provides insights on the strategies that can be taken to lower disorder in graphene. Specifically, since ripples do not contribute to disorder unless there is doping from the substrate, replacing the substrate with materials that have minimal doping effect and impurities should lead to lower disorder. Conversely, while lowering the growth temperature or growing on substrates with minimized CTE mismatch is expected to reduce ripples, these techniques will not improve disorder without a corresponding reduction of substrate disorder. Similarly, thermal treatments to produce flatter graphene can still lead to more disorder in graphene. This study has many implications for wafer-scale integration of graphene-based devices.

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METHODS

Graphene Growth and Wet Transfer. Graphene samples were synthesized in a low-pressure CVD tube furnace. Prior to the growth, the copper foils (Alfa Aesar, 0.025 mm thick, 99.8% purity) were cleaned in acetone, methanol, isopropanol alcohol, and deionized water, and then blow-dried with nitrogen flow. The Cu foils were later oxidized in ambient environment at 300 °C for 30 min. After loading into the furnace, the pressure was first lowered to 33 mTorr, and the temperature was raised to 1050 °C in 16 sccm of H2 flow. The Cu foils were held in this environment for 30 min as a preannealing stage. Then the gas flow was switched to 21 sccm H2 and 0.105 sccm CH4 mixture at a pressure of 250 mTorr for 2 h graphene growth. Finally, the furnace was cooled to room temperature under 16 sccm H2 flow. For wet transfer of the as-grown graphene, 950 poly(methyl methacrylate) (PMMA) C4 was first coated on one side of the Cu foil at 3000 rpm. The polymer coating was then cured on 180 °C hot plate for 15 min. An oxygen plasma was used to etch graphene from the backside of the Cu foil. The sample was then gently placed in 7 g/ L ammonium persulfate solution so that it naturally float on the liquid surface for substrate etching. When the Cu was completely etched, the PMMA/graphene film was transferred with a glass slide into a DI

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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/acsanm.9b00350. Detailed data for bisection analysis for all four areas; Detailed doping concentration histograms from the bisection analysis for as-transferred graphene; Error analysis on bisecting the Raman mapping data; Detailed doping concentration histograms from the bisection analysis for annealed graphene; Gated Raman spectroscopy on CVD graphene FET device as a calibration of intrinsic G and 2D peak positions (PDF) 3431


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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. ORCID

Steven J. Koester: 0000-0001-6104-1218 Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS We acknowledge funding from Boston Scientific Corporation. Portions of this work were also carried out in the University of Minnesota Characterization Facility, which receives capital equipment funding from the University of Minnesota MRSEC under National Science Foundation (NSF) Award DMR1420013. Device fabrication was performed in the Minnesota Nano Center, which is supported by the NSF through the National Nanotechnology Coordinated Infrastructure (NNCI) under Award Number ECCS-1542202.

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