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This paper presents a rapid approach for assembling gold nano-particles (AuNPs)-based microstructures using optically-induced electrokinetics. Results showed that number of AuNPs in the assembled microstructures could be controlled by adjusting the input optically-induced electrokinetics parameters. The formation conditions were experimentally investigated by varying several key electrokinetics parameters, and the results were compared to a numerical simulation of the electrokinetic forces. The experimental results were also analyzed by counting the number of deposited AuNPs in a microstructure using an image processing algorithm. We will show that the optimal parameters for this optoelectronic AuNPs assembly method are electric field frequency range from 9 to 11 kHz with a voltage range of 18-20 Vpp, and an optical exposure time of ~120 s.
© 2014 Optical Society of America
1. Introduction
The assembly of gold nanoparticles (AuNPs) has been studied and explored extensively due to the general application of nanoparticles in various fields, such as energy harvesting [1, 2], biomedical engineering [3, 4], nanomedicine delivery [5], electrochemical biosensors [6, 7], nanodevices [8, 9], and photothermal therapy [10]. For example, the electrodes of solar cells coated with electrophoretically deposed AuNPs-based film have been used to demonstrate an incident photon to photocurrent efficiency of up to 54% and wide photocurrent function spectra. Accordingly, the power conversion efficiency of the modified solar cells may be effectively increased [2]. In the field of biomedical engineering, due to their biocompatibility (the property that their presence in cells is not detrimental to cellular functions), AuNPs have been used as biomarkers in living cells. AuNPs can specifically and homogeneously adhere to the surface of cancer-type cells with greater affinity than to noncancerous cells. Due to the uniquely metallic and optical properties of AuNPs, cancer cells attached to them show distinctive patterns of motion compared with noncancerous cells. Consequently, the manipulation and assembly of AuNPs could be used to explore novel techniques for the diagnosis and detection of living cancerous cells in vivo and in vitro [4]. Moreover, when enzymes and AuNPs are assembled together in silicate networks, the enzymes can connect electrode surfaces and mediate and enhance recognition signals for biological processes. The AuNPs in silicate networks efficiently catalyze the oxidation of the reagent with a decreased overall potential. Thus, AuNP-based biosensors have the desired characteristics of good stability, high sensitivity, and fast response time [7]. Furthermore, the self-assembly of AuNPs’ heterostructure by using functionalized graphene nanosheets as building blocks could improve electrochemical catalytic functionality [9]. For example, the use of high-loading AuNPs on graphene nanosheets as electrochemically enhanced material for sensing hydrogen peroxide has the advantage of creating wide linear ranges and low detection limits.
Hence, substantial efforts have been devoted to manipulating and assembling AuNPs in one, two, and three dimensions. For instance, the manipulation mechanism based on optical tweezers, which is a flexible and well-known technique, has been employed to trap and assemble AuNPs [11]. However, this technology has a shortcoming in that several complex components are required, such as a high numerical aperture lens and extremely precise motion translational stages. This reduces the available working area and makes the operation significantly more difficult. The template-assisted approach [12] has been demonstrated to be a simple and elegant technique for assembling structural AuNP thin films with well-defined dimensions and shapes, although the dimensions and shapes of assembled AuNP structures are subject to pre-defined poly (methyl methacrylate) structures. That is, changing the patterns of nanostructures requires the redesign and re-fabrication of the mask. The atomic force microscope (AFM) based nanorobotics manipulation technique has also been experimentally investigated. It may be used to manipulate AuNPs in three spatial dimensions with the assistance of electromagnetic [13] or electro-enhanced kinetics [14]. Because an electric field or current can be applied independently of the feedback control of tip-to-sample distance, the AFM technique for the assembly of AuNPs is flexible and easy to control with a high resolution and accuracy. Nevertheless, it is disadvantaged by the requirement of lengthy operational time, and is difficult to use for large-scale and large-area manipulation. In our group’s previous work, the pearl chains of AuNP-based sensors assembled and fabricated by the dielectrophoresis (DEP) technique were subjected to detailed theoretical and experimental investigations [15]. AuNP-based sensors were demonstrated to work as low-power flow sensors with a higher frequency response and lower junction resistance than conventional hotwire airflow sensors. However, a major drawback of the DEP assembly technique is the requirement for fixed metal electrodes used for generating a spatially non-uniform electric field. These electrodes are fabricated by conventional micro-lithographic techniques. Hence, this technique generally lacks the flexibility required for dynamic and reconfigurable manipulation of nanoparticles and.
Optical electronic tweezers (OET) or optically induced dielectrophoresis (ODEP) [16] have similar operational principles as the DEP technique based on fixed metal electrodes, except that they offer the capability of dynamically moving and reconfigurable electric fields in a microfluidic system. In the past decade, they have gained recognition as promising techniques capable of manipulating, concentrating, discriminating, and assembling micro-/nano-particles in a dynamic and real-time manner. These techniques can be used for the separation of semiconducting and metallic nanowires [17], the patterning of AuNPs [18], the manipulation and patterning of carbon nanotubes [19], the manipulation of polystyrene beads [20], and the non-UV based fabrication of micrometer- and nanometer-scale polymer hydrogel structures [21]. Using the OET or ODEP techniques, the traditionally complicated fabrication of microelectrodes to generate a spatially nonuniform electric field can be substituted by using real-time and reconfigurable “virtual” electrodes defined by the programmable and digitized optical patterns projected through a projector. We note that, in addition to the DEP force, two other kinds of AC related electrokinetics forces, namely AC electroosmosis (ACEO) and electrothermal (ET) flows, which are derived from the interaction of the electric double layers with the tangential component of the electric field and the presence of the nonuniform field resulting in Joule heating, respectively, could also be present in a microfluidic chip when an electric field is applied across fluidic medium in the chip. Consequently, we herein define and “OEK chip” as a microfluidic chip where optically-induced electrokinetics forces can be generated dynamically and reconfigurably. The electrokinetics forces will include DEP, ACEO, and ET flow forces.
The focus of this papers is to present a systematic study of rapid and automatic AuNP assembly using optically-induced electrokinetics (mainly optically-induced DEP and ACEO forces) technique, and elucidate the key governing electrokinetics parameters that affect the quality of the assemble AuNP-based microstructures. The experimental results were also validated using the finite element method (FEM) simulation of the aforementioned electrokinetic forces exerted on AuNPs. Furthermore, the experimental results were characterized using an image processing method to quantify the optimal experimental parameters for assembling AuNP-based microelectrodes.
2. Experimental setup
2.1. Chip structure and fabrication process
A generalized schematic of the OEK chip is shown in Fig. 1.Briefly, the OEK chip consisted of a top glass substrate coated with a transparent and conductive indium tin oxide (ITO) film that is used as an electrode, a liquid chamber that comprised the working area of the chip, and a bottom layer with a thin photoconductive film of hydrogenated amorphous silicon (a-Si:H) deposited onto another ITO glass substrate. The fabrication process of the OEK chip used in this paper has been described in detail in our previous work [21]. The chip was further processed by etching part of the a-Si:H for electrical connection, as shown in Fig. 1. A 5 mm × 8 mm area of a-Si:H was patterned through standard photolithography and dry-etching using the Oxford Plasma Lab 80 Plasma Etching System with 2% oxygen, 12.5% CF4 gas, a 30mTorr etching chamber, and a 6-minute plasma exposure. The chip was then rinsed and cleaned with acetone and DI water before being dried by nitrogen gas. The liquid chamber with a thickness of ~60 μm, constructed by using a polydimethylsiloxane spacer or a double-sided tape as a spacer, was used to create a microfluidic channel into which the liquid solutions were injected.
Fig. 1 Three-dimensional schematic illustration of the OEK chip. The schematic of the assembled AuNPs structure on the a-Si:H layer indicates that the optically projected square pattern can concentrate AuNPs into a special microstructure with four lines pointing toward the vertex of the square.
2.2. Experimental configuration
A photograph of our experimental setup is shown in Fig. 2.The fabricated OEK chip was fixed on a 3D digital translation platform (Leetro Automation Co. Ltd, China) that could accurately and quickly control the spatial movement of the OEK chip with a minimum motion step of 10 micron meters. A commercial graphics software package (Flash 11, Adobe, US) was used to generate the virtual electrodes that were projected onto the lower surface of the OEK chip via a commercial LCD projector (VPL-F400X, Sony, Japan) coupled with a computer. The manipulation and concentration process of the particles was observed by a charged coupled device (DH-SV1411FC, DaHeng Image, China) mounted on a microscope (Zoom 160, OPTEM, US). In addition, a condenser lens (Nikon, MS plan, 50 × ) fixed between the LCD projector and the OEK chip was used to focus and collimate the optical pattern onto the OEK chip. In addition, an AC bias potential, supplied by a function generator (Tektronix, AFG 3022B, US), was applied to the two transparent and conductive ITO glasses located at the top and bottom of the OEK chip, respectively.
Fig. 2 Schematic illustration of the experimental setup for optically induced electrokinetic assembly of the AuNPs. The setup was composed of an image acquisition system to observe the manipulation and concentration process of the particles, an image generation system to generate the virtual electrode using the commercial software Flash and then project it to the lower surface of the OEK chip by a commercial LCD projector, and a three-dimensional digital control system to automatically and accurately control the motion of the OEK chip.
AuNPs with a diameter of 100 nm (EM, GC series from British Biocell International, Cardiff, UK) were suspended in a liquid solution consisting of deionized (DI) water and KCl salt, which were mixed in different concentrations to obtain a liquid conductivity ranging from 5 × 10−5 S/m to 1 × 10−2 S/m (measured with the Cond 3110 conductivity meter). The dark conductivity and photoconductivity of the a-Si:H were 1 × 10−11 S/m and 4 × 10−5 S/m, respectively (experimental values measured with a Keithley 2410 source meter).
3. Rapid assembly of AuNPs-based microstructures
The experimental process and results for the automatic and rapid assembly of the AuNPs by using the OEK chip are shown in Fig. 3.Briefly, when no bias potential was applied and during the projection of the four geometrical patterns of optical images projected onto the a-Si:H layer of the OEK chip, the AuNPs were randomly suspended in the chip chamber with a liquid conductivity of 1 × 10−3 S/m due to Brownian motion, as shown in Fig. 3(a). In this figure, the geometrical sizes for the four optically projected patterns are the spot pattern with a diameter of 60 μm, the ring pattern with an outer diameter of 60 μm and inner diameter of 40 μm, the regular triangle pattern with each side length of 60 μm, and the square pattern with each side length of 60 μm, respectively. The AuNPs were concentrated and assembled in the illuminated areas [Fig. 3(b)] after an external AC voltage potential, with a 20 Vpp at a frequency of 20 kHz, was switched on. After 30 s, both of the projected optical patterns and the bias potential were shut and the assembled AuNP-based microstructures were recorded, as shown in Fig. 3(c). The randomly distributed AuNPs in the field of view of the microscope were attracted to and thus assembled in the illumination areas. In particular, most of the assembled AuNPs were located in the center of the optical patterns. SEM images of the experimental results were obtained and are shown in Figs. 3(d)-3(f). However, compared with Fig. 3(c), which was captured by the microscope, the number of concentrated AuNPs shown in the SEM images in Figs. 3(d)-3(f) decreased, because some of the concentrated AuNPs were swept away by the water flow when the OEK chip was gradually dried in air. It is worth noting that the incident optical patterns with a triangle image resulted in a circle structure with three lines pointing toward the vertex of the triangle and a square image resulted in a similar structure, but with four lines.
Fig. 3 Assembly of AuNP-based microstructures. (a) The incident optical patterns were projected onto the OEK chip and no bias potential was applied. (b) The suspended AuNPs were concentrated in the illuminated areas when an external AC voltage potential with 10 Vpp at a frequency of 20 kHz was switched on. (c) The microscope image of assembly of AuNPs. (d) The SEM image of (c). (e) SEM image of the patterned AuNPs structure in the regular triangle pattern. (f) SEM image of the patterned AuNPs structure in the square pattern.
To explore the conditions for fabricating such special microstructures, as described, the experimental parameters, including the liquid conductivity, the applied frequency, and the voltage were investigated. The results are shown in Fig. 4and summarized in Table 1. The results demonstrate that the liquid conductivity range for forming the special AuNP-based microstructures varied from 5 × 10−5 S/m to 5 × 10−3 S/m, and the frequency range was from 8 kHz to 20 kHz with a voltage of 10-16 Vpp. To be more precise, when the liquid conductivity was 5 × 10−5 S/m, that is, the conductivity of the pure DI water without containing any KCl, the special microstructures, as in Fig. 3(c), could be formed only at the frequency range of 10-20 kHz, as shown in Fig. 4(a) ii. That is, when the frequency range was located in the range of 5.5 kHz-10 kHz or higher than 20 kHz, the special microstructures could not be obtained, as shown in Figs. 4(a) i-ii, respectively. The bubbles were generated with a frequency lower than 5.5 kHz. In addition, when the liquid conductivity was 5 × 10−4 S/m and 5 × 10−3 S/m, the frequency range for the formed microstructure was 15-20 kHz and 8-9 kHz, respectively, as shown in Figs. 4(b) ii and 4(c) ii.
Fig. 4 Concentration and assembly of AuNPs with different liquid conductivities, frequencies, and voltages. (a) The AuNPs’ microstructures were formed only in the frequency range of 10-20 kHz with a liquid conductivity of 5 × 10−5 S/m. (b) The AuNPs’ microstructures were formed only in the frequency range of 15-20 kHz with a liquid conductivity of 5 × 10−4 S/m. (c) The AuNPs’ microstructures were formed only in the frequency range of 8-9 kHz with a liquid conductivity of 5 × 10−3 S/m. All scale bars are 30 μm.
Table 1. Experimental Parameters of the Formed AuNP Microstructures
4. Discussion
4.1. ODEP
As a whole, nearly all of the applied voltage dropped across the a-Si:H layer when the OEK chip was not illuminated by visible light, due to its inherent lower conductivity. Instead, when an optical pattern from a commercial digital projector was projected onto the surface of the a-Si:H, the electron-hole pairs were excited and enhanced by the migration of electrons from the valence band to the conduction band of the a-Si:H layer, thus locally increasing the conductivity of the a-Si:H via the photoconductive effect. Then, the electric field across the liquid chamber dramatically increased above the locally illuminated a-Si:H area because most of the applied voltage was substantially shifted to the liquid chamber. Accordingly, a nonuniform electric field could be created in the liquid chamber and then any suspended particles at locations in the vicinity of this optically-induced nonuniform electric field would experience a force though an interaction between the electrically polarized dipole moments of both of the particles and the liquid solution, known as the DEP function, which is defined as the “ODEP force” in this OEK chip. Unlike conventional DEP chips, no metal electrodes were required to create the non-uniform electric field. The ODEP force could be either positive or negative under specific conditions, meaning that the particles could be either attracted to or repelled from the illuminated areas due to the positive or negative DEP force, respectively. Our previous work, as presented in [20], provides a more detailed treatment of the spatial distribution of the positive and negative ODEP force and how optical wavelengths, applied AC wave forms, and frequency can affect the ODEP force.
The time-averaged DEP force acting on a spherical nanoparticle is defined as [22]:
where R is the particle radius, εm denotes the permittivity of the liquid medium; Erms is the root-mean-square (rms) value of the electric field; and Re[K(ω)] is the real part of the Clausius-Mossotti (CM) factor, representing the direction of the DEP force.To theoretically obtain whether the DEP force can assemble AuNPs and form the AuNP-based microstructures shown in Fig. 3(c), the simulation results of the DEP force vectors distribution had first to be obtained. Assuming a liquid conductivity of 5 × 10−5 S/m as an example, the numerical distribution of the DEP force vectors are shown in Fig. 5, obtained through the use of the FEM software package (Multiphysics, COMSOL AB, Sweden). In this example, the frequency range was 10-20 kHz with a voltage of 16 Vpp. The selected modules and boundary settings were the same as those discussed in our previous work in [20]. The dark conductivity of the a-Si:H was 1 × 10−11 S/m, and the photoconductivity was 4 × 10−5 S/m (experimental values for the a-Si:H film used in our work, as measured by a Keithley 2410 source meter). Moreover, the relative dielectric constant of the liquid and the a-Si:H were 78 and 11, respectively. Figure 5(a) shows the distribution of the DEP vectors induced by the optically projected spot, and indicates that the DEP force will manipulate and only assemble the AuNPs at the edge of the optically projected spot. Furthermore, few AuNPs were in the center area of the optically projected spot due to the DEP forces. As regards the DEP vectors induced by the optically projected ring in Fig. 5 (b), the AuNPs was also assembled at the edge of the illuminated areas. Furthermore, in terms of the DEP vectors induced by an optically projected triangle [Fig. 5(c)] and square [Fig. 5(d)], the assembled AuNPs were located at the edges of the optically projected patterns, respectively. In conclusion, the simulation results for the DEP forces indicated that the forces cannot fabricate and construct the special microstructures as shown in the experimental results on the special microstructures (i.e., the results in Fig. 3(c), Figs. 4(a) ii, 4(b) ii, and 4(c) ii, respectively). Accordingly, other AC electrokinetic forces must play a critical role in the process of assembling AuNPs.
Fig. 5 Simulation results for the distribution of the DEP vectors induced by the optical spot (a), ring (b), triangle (c), and square (d) patterns, respectively. The liquid conductivity is 5 × 10−5 S/m at the frequency range of 10-20 kHz with a voltage of 16 Vpp.
4.2. ACEO
From (1), it can be seen that the DEP force exerted on a nanoparticle sharply decreases, as it is directly proportional to R3. Accordingly, for the manipulation of AuNPs using the DEP technique, the magnitude of the DEP force may not effectively overcome Brownian motion in a specific frequency range. Furthermore, it is critical to consider the amount of temperature increase when the AuNPs are manipulated and assembled in the liquid solution due the temperature gradient would result in the liquid flow. In general, the temperature increase of the OEK manipulation is classified as two categories: 1) the absorption of the incident optical energy by the metallic particles; 2) the electro-thermal (ET) effect. As described in our previous work [23], the ET flow can be neglected because the ET flow velocity is ~one order of magnitude lower than the ODEP velocity. To evaluate the first type of the temperature increase for the AuNPs, an analysis [24] was conducted by A. Jamshidi. For the optical power with an intensity of 40 μW employed in this study, the temperature increase in OEK assembly of 100 nm AuNPs can be estimated to be 0.2 °C. Accordingly, the temperature increase of the AuNPs due to the absorption of optical energy can also be neglected because this increase is lower than the ET effect.
The ACEO production is consistent and the stable flow direction toward the illuminated areas is modeled by calculating the slip velocity [25]:
where ζ is the zeta potential across the electrical double layer formed at the interface between the a-Si:H layer and the liquid layer, and Et is the tangential component of the electric field. As discussed and investigated in [26], there is an optimal frequency at which the slip velocity reaches the maximum value. Furthermore, using the optimal frequency equation of the ACEO [26], the optimal frequency is 24 Hz, 76 Hz, and 240 Hz for a selected experimental liquid conductivity of 5 × 10−5 S/m, 5 × 10−4 S/m, and 5 × 10−3 S/m, respectively. The ACEO flow will produce a stable and consistent hydrodynamic force (i.e., by balancing the slip velocity in (2) with the opposing Stokes’ drag force, Fdrag = 6πηυ [25]), namely,The FEM simulation of the spatial distribution of the ACEO force induced by the optically projected spot pattern under a liquid conductivity of 5 × 10−5 S/m was conducted and is shown in Fig. 6.Both the time-harmonic analysis model and the incompressible Navier-Stokes fluidic model in the FEM software package were used to simulate the ACEO force distribution in the liquid chamber. The time-harmonic analysis model was used to calculate the zeta potential across the electric double layers and the tangential component of the electric field, and then to obtain the slip velocity. The obtained slip velocity was used as the boundary input to solve the incompressible Navier-Stokes equations for the ACEO distribution in the liquid chamber. The applied frequency was 10 kHz.
Fig. 6 FEM simulation result of the ACEO force distribution in the liquid chamber. The arrows indicate the direction of the ACEO force vectors; the surface color represents the magnitude of the ACEO force; and the isolines indicate the magnitude of the ACEO force distribution. The difference between any of the two adjacent isolines was 0.1 pN. The applied frequency was 10 kHz at a voltage of 16 Vpp.
As the arrows in Fig. 6 on the results for the FEM simulation show, the ACEO flow force attracts and thus assembles the AuNPs in the center of the incident optical pattern. Furthermore, compared with the DEP force distribution in the vertical direction shown in our previous work in [27], the magnitude of the ACEO force decreased more slowly along the vertical direction from the a-Si:H surface and still had a larger value even at a height of 10 µm above the a-Si:H surface, meaning that there were many AuNPs assembled and located at the center of the optical pattern as the above experimental results show.
4.3. FEM simulation of AC electrokinetics
Therefore, as regards the DEP and ACEO forces, either one or both may govern the assembly process for the AuNPs under the given experimental parameters shown in Table 1. To theoretically explore which forces will dominate the process of assembly of the AuNP-based microstructures, we obtained the numerical solution for the DEP and ACEO forces exerted on the AuNPs with respect to the applied frequency. Figure 6 shows the simulation and calculation results for the DEP and ACEO forces exerted on the AuNPs as a function of the applied frequency. For the results shown in Fig. 7, we used the following parameters. Three liquid conductivities employed in the experimental process, 5 × 10−5 S/m, 5 × 10−4 S/m, and 5 × 10−3 S/m, were selected as the critical parameters to calculate the DEP and ACEO forces. The dark and photo conductivities of the a-Si:H were the same as those used in Fig. 5. The time-harmonic analysis module of the quasi-static current field of the software was used to solve Maxwell’s equations in the sub-domain of the liquid chamber of the OEK chip to acquire the electric field distribution and then to calculate the DEP force. The corresponding boundary settings were the same as those discussed in our previous work in [23].
Fig. 7 DEP and ACEO forces exerted on the AuNPs with different liquid conductivity as a function of the applied frequency. The applied voltage was 16 Vpp.
The results in Fig. 7 show that when the liquid conductivity was 5 × 10−5 S/m, the DEP force exerted on the AuNPs was the highest, and the ACEO force exerted on the AuNPs increased with as the liquid conductivity increased. The ACEO force for AuNPs was higher than the DEP force for AuNPs regardless of the liquid conductivity and the AC voltage and frequency. The ACEO force was lowest when the liquid conductivity was 5 × 10−5 S/m, meaning that the number of assembled AuNPs was smallest under this liquid conductivity in theory. This same conclusion could be intuitively observed and is shown in Fig. 4(a) ii. The number of assembled AuNPs in Fig. 4(c) is slightly higher than in Fig. 4(b). According to the simulation and calculation results in Fig. 7, the ACEO force for AuNPs with a liquid conductivity of 5 × 10−3 S/m was higher than that for AuNPs with a liquid conductivity of 5 × 10−4 S/m. However, compared with the DEP force exerted on the AuNPs with a liquid conductivity of 5 × 10−3 S/m, the DEP force was higher under a liquid conductivity of 5 × 10−4 S/m. Accordingly, both of the DEP and ACEO forces manipulated and assembled the AuNPs into special microstructures. The ACEO force then dominated the assembled process that formed the special microstructures.
5. Rapid assembly of AuNPs into microelectrodes
In this section, the rapid assembly of AuNPs into microelectrodes without the use of any module or mask was experimentally investigated. A droplet of AuNP solution with a liquid conductivity of 5 × 10−5 S/m was injected into the OEK chip and statically kept in a micro chamber. Figure 8 shows the incident optical configuration with typical electrode patterns that was projected on the a-Si:H surface so that the AuNPs were deposited onto it. The gap between the image electrodes was 2 µm. The main purpose of the experiment was to determine the optimum parameters, such as the frequency, voltage, and exposure time, for the deposition of the AuNPs. Hence, a broad range of frequencies and voltages were tested, from 5.5 kHz to 30 kHz and from 0 Vpp to 20 Vpp. A different exposure time (from 10 s to 300 s) of the pattern was also studied. All of the experiments were carried out in the same configuration and setting, and the temperature was assumed to be constant at 25°C. After each set experiment was performed, the OEK chip was removed from the experimental platform, rinsed with DI water, and then blown dry with compressed air.
According to the experimental results, there were three different deposition patterns of AuNPs on the OEK chip that could be classified into three frequency regions. The applied voltage was 20 Vpp for all cases in this section. When the frequency range was below 5.5 kHz and over 30 kHz, the AuNPs tended not to be attracted into the optical patterns. Bubbles were formed if the frequency was below 5.5 kHz. This indicates that the AuNPs did not experience positive DEP forces in this region. Furthermore, when the frequency range was between 18 k and 30 kHz, the AuNPs were attracted on to the pattern. However, they floated and levitated in the medium, and some of the AuNPs looped in and out of the image. After rinsing, the AuNPs could not be found on the a-Si:H surface. Within this range, the AuNPs experienced a positive DEP force, but were not stable in the given frequency and at the given voltage. Instead, when the frequency range was between 5.5 kHz and 18 kHz, the AuNPs first covered the image and then aggregated at the center of the image. After the rinsing and cleaning process, most of the AuNPs remained on the a-Si:H surface according to SEM images taken after the experiment. The best results were obtained at 9 k–11 kHz, due to ACEO. Applied voltages for AuNPs deposition from 0 Vpp to 20 Vpp at 9.5 kHz were tested. The results showed that the effective deposition range was from 18 Vpp to 20 Vpp, where it provided enough force for ACEO flow.
The effect of the exposure time on the AuNPs’ deposition was also studied. Figure 9 shows the results for AuNP deposition at different exposure times of 10 s, 20 s, 30 s, 60 s, 120 s, and 300 s that were recorded and observed with SEM images with an applied frequency of 9.5 kHz at 20 Vpp. Figures 9 (b)-9(c) are sequences of SEM images of the AuNPs on the electrode and pad areas versus the exposure times of 10 s, 20 s, 30 s, 60 s, 120 s, and 300 s, respectively. Herein, the applied frequency is also 9.5 kHz with an AC bias potential of 20 Vpp. To quantify the number of deposited AuNPs from the SEM images, an algorithm was developed using MATLAB to count how many AuNPs were concentrated at a frequency range of 9-11 kHz with different exposure times. Each of the SEM images was first processed by a function based on a global threshold level using the Ostu’s method to calculate a threshold where the intraclass variance of black and white pixels is minimized [28, 29]. The grey level image was thus converted into a binary image. Subsequently, the number of AuNPs was estimated using two methods. The first method identified separated white pixel groups in the image as an AuNP. A pixel group in which every pixel had at least one direct neighbor was a 4-connected group [30]. By counting the number of 4-connected groups, the number of AuNPs in the SEM image could be estimated. However, this method was inaccurate for a very dense SEM image because AuNPs pack together and may be identified as a single group. Therefore, a second method was used to estimate the number of AuNPs. When the size of the particles and the scale of the image were known, in particular for this experiment, the diameter of the AuNPs could be approximated. The scale of the image was 0.226 micrometers per pixel, and thus the approximate number of pixels that a single particle occupied could be pre-calculated. Subsequently, noise was removed by reversing the value of the 4-connected white pixel groups with pixels much smaller than a particle’s pixel size. The particle count was thus calculated by dividing the white area by the particle pixel size.
Fig. 9 SEM images of AuNP deposition on a-Si:H at an applied frequency of 9.5 kHz at 20Vpp. (a) SEM image of the AuNPs on the electrode pattern. (b) SEM image of the AuNPs on the electrode. (c) SEM image of the AuNPs on the pad. All scale bars are 5 μm.
Figure 10 shows the results obtained by the two methods, and Figs. 10(a)-10(b) are the evaluation of the assembled AuNPs on the electrode and pad areas, respectively. We averaged the number of deposited AuNPs obtained by the two methods to show the relationship between the number of deposited AuNPs at different frequencies and exposure times. The number of deposited AuNPs obtained by method 1 and method 2 was used as the minor and maximum value, respectively. We may conclude that the AuNP concentration increased with exposure time from 10 s to 120 s exposures and reached the maximum at 120 s, decreasing gradually thereafter with the increase of exposure time.
Fig. 10 Evaluation of the assembled AuNPs on the electrode (a) and pad (b) areas by image processing as a function of applied frequency and exposure time.
6. Conclusion
In this paper, the parametric experimental results obtained from the use of optically-induced electrokinetics to rapidly assemble 100nm diameter AuNPs into 2D patterns is presented. The experimental results show that projecting an incident optical pattern with a triangle image onto the OEK chip resulted in a circular microstructure with three lines pointing toward the vertex of the triangle and a square image resulted in a similar microstructure but with four lines. The formation conditions for constructing those special microstructures, including the applied voltage, frequency, and liquid conductivity, were experimentally investigated, and then validated through a numerical simulation of the electrokinetic forces exerted on 100nm AuNPs. The simulated results reveal that the DEP and ACEO forces manipulated and assembled the AuNPs into microstructures; however, ACEO force is dominant in the assembly process that formed the microstructures. To experimentally investigate the performance of assembling AuNPs into microelectrodes by ACEO, the applied voltage, frequency, and exposure time were studied systematically. The results analyzed by counting the number of deposited AuNPs using an image processing algorithm showed that the optimal frequency was between 9 and 11 kHz with a voltage range of between 18 and 20 Vpp, and the optimal exposure time was 120 s. Accordingly, this study presents a novel approach for the rapid assembly of AuNP-based microstructures, and could be promising for assembling other nanomaterials, such as graphene and nanowires.
Acknowledgments
This work is supported by the National Natural Science Foundation of China (project no.: 61107043). Wen Jung Li would like to thank the CAS-Croucher Funding Scheme for Joint Laboratories (project no.: 9500011) and the Hong Kong Research Grants Council (project no.: CityU 116912) for providing financial support to this project.
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