Vertical graphene nanosheets have advantages over their horizontal counterparts, primarily due to the larger surface area available in the vertical systems. Vertical sheets can accommodate more functional particles, and, due to the conduction and optical properties of thin graphene, these structures can find niche applications in the development of sensing and energy storage devices. This work is a combined experimental and theoretical study that reports on the synthesis and optical responses of vertical sheets decorated with gold nanoparticles. The findings help in interpreting optical responses of these hybrid graphene structures and are relevant to the development of future sensing platforms.
Graphenes consist of a small number of atomic carbon layers arranged in a hexagonal lattice. Graphene has unique optical and electrical properties [
VGNs typically consist of a few vertically oriented atomic carbon layers produced via plasma enhanced chemical vapour deposition [
This combination of large surface area and control of interparticle coupling makes VGNs decorated with functional materials promising candidates for the development of new hybrid materials. Such materials can display exotic physical properties that are not seen in the individual elements making up the hybrid material. For example, when metal nanoparticles are combined with carbon nanotubes, the new hybrid structures display electron transport properties not seen in either of the constituents [
Graphenes are relatively low-loss and transparent optical materials which can provide strong electromagnetic (EM) confinement, making the interaction of graphene with metal nanoparticles of interest for the development of novel plasmonic-based devices [
Gold nanoparticle-decorated VGNs are a hybrid plasmonic system which could find applications in optical and SERS sensing. This paper studies the optical properties of these gold nanoparticle-decorated VGN systems synthesised by plasma enhanced chemical vapour deposition (PECVD), using a combination of optical microscopy, Raman spectroscopy, and theoretical finite element analysis models.
The VGNs were fabricated on a Si(100) substrate using a low-temperature, low-pressure PECVD process. The substrate was first pretreated by exposure to N2 plasma for 5 min (N2 inlet 50 sccm, microwave power 500 W, and chamber pressure 7 Torr) and the substrate reached a temperature of approximately 400°C. After the treatment, 10 minutes of deposition was performed using the following process parameters: CH4/N2 gas inlet ratio of 1 : 1, input power of 750 W, and chamber pressure of 10 Torr. The final temperature of the substrate at the end of deposition was approximately ~800°C. Further information on the relevant fabrication processes can be found elsewhere [
Gold nanoparticles were then thermally evaporated onto the VGN at room temperature. The process parameters used were the following: filament temperature ~1620°C, distance between the sample and filament ~25 cm, 0.5 mm diameter of mesh between the sample and filament, mesh thickness ~1 mm, distance between mesh and sample ~1 mm, and chamber pressure 2.0
SEM images of the resultant gold-decorated VGNs are shown in Figure
(a) SEM of uncoated VGN, (b) Au nanoparticle coated VGN edge, and (c) side-view of the Au nanoparticle coated vertical walls of the VGN.
The density of the gold nanoparticles on the VGNs varied from distance of the specific sample areas from the evaporation orifice. Four samples were considered with varying distance to the evaporation orifice. This was done by mounting the VGN samples radially from the center of the mesh hole [
(a–c) SEM images show denser patterns of Au NPs thermally deposited on VGN as moving radially towards the center of the mesh hole. (d) A dense pattern of larger Au NPs on VGN close to the center of the mesh.
The SEM images of the four samples were analysed and the density of particles and particle size are given in Table
Average particle diameter and number of particles per nm2 for four samples.
Sample | Average particle diameter (nm) | Nanoparticles/area (×10−3/nm2) |
---|---|---|
1 | 11 ± 1 | 6 ± 1 |
2 | 10 ± 1 | 9 ± 1 |
3 | 11 ± 2 | 13 ± 1 |
4 | 14 ± 3 | 22 ± 3 |
The optical properties of the gold-coated VGNs changed significantly depending on the density of the gold nanoparticles. Various densities of gold nanoparticles were deposited on the VGN, and CCD camera images of the samples were taken using a Renishaw
Optical images of increasing density (a–d) of Au nanoparticles on VGN sheets. The scale bar in all images is 5
Using the Renishaw
Representative Raman spectra (1 s acquisition time) for gold nanoparticle-decorated VGNs (blue, green, and brown) and for undecorated VGNs (red).
Clearly, decorating the VGNs with gold nanoparticles results in a stronger SERS signal as compared to pristine VGNs. Main peak positions also experienced a slight shift between the areas of different Au nanoparticle density, that is, where interparticle distances were different.
From the optical images and Raman spectra, it is clear that the interparticle spacing between the gold nanoparticles affects the optical properties of the hybrid gold-decorated VGN structure. Furthermore, these hybrid graphene structures have promising applications in optical sensing, as can be seen in Figure
The Raman spectra in Figure
To understand why the Au nanoparticle presence (and density) on both sides of the vertical graphene sheets affects the optical properties of the VGN structures, numerical modeling of the optical responses of these hybrid structures has been performed using COMSOL Multiphysics.
The gold nanoparticles are modelled as 10 nm diameter spheres atop 1.5 nm (approximately five atomic carbon layers) graphene sheet. The optical properties of gold and few-layer graphenes were taken from Palik [
Schematic of the gold trimer system on the vertical graphene sheet of approximately 5 atomic carbon layers. The separation distance between the top particles is 12 nm in this diagram.
Two types of incident beam are considered: (1) beam polarised in
In the trimer system, the resonance peak is obtained at 531 nm with the maximal SERS signal at resonance recorded for the 12 nm separation. The SERS signal peak is ~5.9 × 106 which is stronger than the case of a single isolated gold nanoparticle on a graphene sheet [
Maximum SERS signal for various nanoparticle separation distances.
Separation (nm) | SERS signal (×106) |
---|---|
12 | 5.89 |
14 | 2.28 |
16 | 1.27 |
As expected, the SERS signal strength decreases with increasing the interparticle distance. This is clear from the electric field distribution (|
|
However, this was for the beam incident in the
|
Possible future avenues of theoretical study would be to test infinite arrays of these gold nanoparticles to determine the influence an ordered system has on the resultant SERS signal. Methods of increasing the SERS signal, such as by altering the particle geometry, decreasing the number of sheets in the VGN, or introducing further close packed particles might also be considered to better understand the effect of the contact region on the resultant optical response.
Decoration of VGNs with gold nanoparticles results in a unique 3D hybrid graphene-gold architecture which provides a strong SERS signal as opposed to uncoated VGNs. The density of the gold nanoparticles on the VGNs directly affects the optical properties and the resultant maximum SERS signal that can be obtained from these hybrid structures. Coupling between the gold nanoparticles and the graphene sheet should be optimized for achieving the maximum SERS signal enhancement. A viable option is to control positions, sizes, and densities of gold nanoparticles on both sides of the vertical graphene sheets. These results are relevant to the development of the next-generation optical sensing platforms based on localized plasmonic and SERS responses to various optical excitations and analyzed species.
The authors declare that there is no conflict of interests regarding the publication of this paper.
Angus Mcleod acknowledges support from the QUT HPC team. Angus Mcleod and Kristy C. Vernon acknowledge the Australian Research Council (ARC) Grant DP110101454. Angus Mcleod and Shailesh Kumar acknowledge support from CSIRO’s Sensor and Sensor Networks TCP. Shailesh Kumar and Kostya (Ken) Ostrikov acknowledge support from the CSIRO Office of Chief Executive Science Leadership Program and the ARC.