KFM Analysis of Graphene Electrical Properties

By AZoNano.com Staff Writers

Topics Covered

Introduction
Single-Pass KFM
Determining SLG on SiO2 via High-Resolution AFM Imaging
Distinguishing and Quantifying Difference in Surface Potential Between SLG and a Silica Substrate
Single-Pass KFM and Capacitance Gradient (dC/dZ) Measurements of FLG
Conclusions
About Agilent Technologies - Nanotechnology Measurements

Introduction

Graphene and its derivatives have gained significant interest as a potential material for nanoelectronic applications. From an assembly perspective, both single-layer graphene (SLG) and few-layer graphene (FLG) have high compatibility with planar device architectures. In addition, graphene-related nanomaterials exhibit highly tunable electrical properties, such as rich electronic band structures and carrier type or density.

For example, SLG has a zero bandgap, while FLGs have different bandgaps as a function of layer count. Hence, delicate control of graphene sheets with well-defined bandgaps can be achieved to fine tune their electronic properties.

Quantitative measurements of charge exchange at the interface and spatial distribution of the charge carriers are crucial for designing graphene-based devices. This article discusses analyzing the local electrical properties of both SLG and FLG films on silicon dioxide using Kelvin force microscopy (KFM), which is an atomic force microscopy (AFM)-based technique. Quantitative measurements are taken by determining the effect of the film thickness on the surface potential.

Single-Pass KFM

Conventional KFM is put into action in a two-pass approach called ‘lift mode,’ wherein a first scan is performed to acquire the surface morphology and then the tip is positioned at a certain distance over the sample. Quantitative mapping of the surface potential of a sample is generated in the second pass by directing the tip across the surface contour and applying a second feedback control to negate the electrostatic interactions between the tip and the sample.

The subsequent acquisition of surface potential and topography can lead to a disagreement between the two images caused by the thermal drift effect. Additionally, detecting the electrostatic forces at a remote tip-sample separation may negatively affect the detection sensitivity. This, in turn, affects the spatial resolution and the precision of surface potential measurements. Nowadays, most scanning probe microscopes are equipped with multiple lock-in amplifiers (LIAs). For instance, most Agilent AFM platforms have optional MAC Mode III (or AAC III) unit featuring three dual-phase LIAs that facilitate the conversion of AC inputs into amplitude and phase signals.

With a broad bandwidth of up to 6MHz, these digitally controlled analog LIAs can cover the operational bandwidth of the photodetector used in the microscope. Consequently, single-pass KFM imaging is facilitated by the concurrent use of a much lower frequency (ωelec in the second LIA for monitoring the electrostatic interactions) for sample surface potential measurements and the probe flexural resonance frequency (ωmech in the first LIA targeting the mechanical tip-sample interactions).

Furthermore, single-pass KFM as implemented by Agilent Technologies instrumentation functions in the intermittent regime, thereby drastically improving the localized surface potential measurements.

Determining SLG on SiO2 via High-Resolution AFM Imaging

An optical photograph of exfoliated graphene flakes on a silica substrate is depicted in Figure 1, clearly showing different film thickness (or number of layers) in different colors. A darker contrast represents a thicker film.

Figure 1. An optical photograph of exfoliated graphene flakes with various thickness on a silicon dioxide substrate.

Figure 2 illustrates determining SLG on silica through AFM imaging. Figure 2A is a high-resolution topographic image showing the morphological difference between the graphene sheets and the substrate. Individual granular features within the substrate area are resolved due to the smoothness of the graphene layer.

The cross-session cursor profile (Figure 2C) supports this conclusion as it clearly reveals the surface corrugation of graphene film vs. substrate and enables deriving the quantified measurements of the surface roughness in each region.

Figure 2. An example of indentifying single-layer graphene on silica.

The ‘step height’ function in the AFM post-processing software Agilent Pico Image is used to perform the statistical measurement of the apparent height of the SLG (Figure 2B), yielding a value in agreement with the one derived from the local cross-section measurement in Figure 2C.

Practical AFM measurements of a SLG on Si/SiO2 always yield higher values than theoretical value because of the weak sample/substrate interactions and existence of ambient species between graphene and SiO2 and the graphene film and/or on the graphene film.

Assuming the thickness of graphene films follows a linear relationship equation: h = nxt + t0, where n is an integer as the number of layers, t is the approximate theoretical thickness of each graphene layer, and t0 is a systematic offset (i.e., independent of n), the appropriate values for t and t0 based on combined Raman scattering and AFM analyses were 0.35±0.01 nm and 0.33±0.05 nm, respectively.

Hence, the experimentally measured apparent height of single-layer graphene on silica is in line with this model in the case of n=1.

Distinguishing and Quantifying Difference in Surface Potential Between SLG and a Silica Substrate

After locating a sample site consisting of SLG, the surface potential of this site is measured by performing in situ KFM imaging (Figure 3A). Figure 3A is a topographic image that is nearly indistinguishable from Figure 2A, but the scan size is slightly increased from 5µm x 5µm, to 6µm x 6µm.

Figure 3. KFM imaging of single-layer graphene on silica.

Figures 3B and 3C are concurrently acquired phase and surface potential images, respectively. Figure 3B is uniform such that contrast differences between the graphene layer and bare substrate are insignificant. Hence, different contrasts that can be seen in the surface potential image (Figure 3C) are significant, showing boundaries that exactly match the boundaries between the two regions in the corresponding topographic image (Figure 3A).

This demonstrates the ability of the KFM technique to complement phase imaging and act as an effective means to determine graphene-related nanomaterials on a silica substrate. Moreover, Figure 3C reveals that SLG has a slightly higher surface potential compared to silica. Figure 3D depicts the quantified measurement, revealing that the surface potential between the two different materials is roughly 60mV.

Single-Pass KFM and Capacitance Gradient (dC/dZ) Measurements of FLG

Single-pass KFM and capacitance gradient (dC/dZ) measurements of FLG samples provide more valuable data, as shown in Figure 4. Figure 4A is a topography image clearly resolving multiple steps and differentiating the three main regions labeled as I, II, and III. Figure 4D shows a cross-section profile relative to the purple line drawn in Figure 4A, revealing that region I is around 0.75nm higher than region II by considering region III as a background baseline.

This value is in line with the two folds the HOPG interlayer spacing (0.34 nm). Indeed, this estimated bilayer change in the film thickness is further concluded by a well-defined single atomic step resolved between region I and region II in Figure 4A.

Figure 4. Single-pass KFM and capacitance gradient (dC/dZ) measurements of few-layer graphene on silica.

The corresponding phase image (not given) is identical to Figure 3B. Hence, it cannot be used as evidence for distinguishing FLG sheets from a bare silica substrate. Moreover, the dependence of surface potentials on the film thickness, as shown in Figure 4C, further complicates the case of FLG films. Further analysis based on other electrical properties of the samples helps determining region III as a substrate area. Now, the tip response at a frequency of 2ωelec is monitored by directly connecting the third LIA to the photodetector.

The oscillation of the tip actuated by the electrostatic force at this 2ωelec frequency is in proportion to the capacitance gradient (dC/dZ), which is associated with the local dielectric permittivity of the sample. Regions I and II, despite consisting of different graphene layers, show a uniform contrast that is brighter than that of region III in the dC/dZ image (Figure 4B).

Such results can be corroborated by the fact that graphite material has much higher dielectric constant (ε=10–15) compared to that of silica (ε=3.9). From the results it is evident that the interface layer and multilayer graphene can be clearly differentiated by the combination of KFM and capacitance gradient (dC/dZ) measurements. Surface potential measurements of FLG films reveal the layer-dependent surface potential behavior in terms of contrast difference between the thicker film in region I and that in region II (Figure 4C).

Conclusions

The results clearly demonstrate the advantage of using KFM to analyze the local electrical properties of either single-layer or few-layer graphene films on a silicon substrate. The conclusion of this KFM study that FLG surface potential varies monotonically with the number of graphene layers is in good agreement with the results obtained by many other research groups.

About Agilent Technologies - Nanotechnology Measurements

Agilent Technologies nanotechnology instruments let you image, manipulate, and characterize a wide variety of nanoscale behaviors—electrical, chemical, biological, molecular, and atomic. Our growing collection of nanotechnology instruments, accessories, software, services and consumables can reveal clues you need to understand the nanoscale world.

Agilent Technologies offers a wide range of high-precision atomic force microscopes (AFM) to meet your unique research needs. Agilent's highly configurable instruments allow you to expand the system's capabilities as your needs occur. Agilent's industry-leading environmental/ temperature systems and fluid handling enables superior liquid and soft materials imaging. Applications include material science, electrochemistry, polymer and life-science applications.

This information has been sourced, reviewed and adapted from materials provided by Agilent Technologies - Nanotechnology Measurements.

For more information on this source, please visit Agilent Technologies - Nanotechnology Measurements.

Date Added: Feb 13, 2014 | Updated: Feb 19, 2014
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