1. Introduction
Microfluidics is a scientific field concerned with miniature fluid manipulation and the practices of microfluidics benefit a wide range of scientific applications, from biosensing to genome analysis to electrochemistry to environment monitoring, and more [
1,
2,
3,
4,
5]. Microfluidic platforms offer precise control over fluid flow, cell manipulation, and biochemical reactions, allowing us to mimic aspects of the complex microenvironment of breast tumors and study cellular behaviors in a controlled setting [
6,
7,
8,
9,
10,
11]. Passive and active techniques are both utilized in microfluidics. Passive techniques include flow manipulation achieved solely from components that do not require energy—such as physical mesh filters, obstacles impeding flow, or grooves and trenches spatially interacting with the fluid. Active filtration requires mechanisms that actively work; this form of filtration is more functional but is more expensive to produce and maintain. Much research today regarding microfluidics considers such active techniques and has been spoken of at length by other authors [
12,
13,
14,
15,
16,
17,
18,
19,
20,
21]. One technique utilized in microfluidics is electroosmotic flow (EOF) or electroosmosis, in which flow is driven using an electric field and solutions doped with particles that will be affected by said EF. These particles are usually ions or dielectrics that move according to Coulomb’s law. The motion of these particles then drives a bulk fluid flow. Alternating current electroosmosis (ACEO) is a type of induced-charge electroosmosis in which a non-uniform electric field provides a tangential force that affects the motion of ions to control flow. This study will examine the range of frequencies most effective for ACEO to separate chosen particles. The frequency refers to how quickly the current changes polarity over time. Higher frequencies will result in more rapid changes in the electric double layer (EDL) on which the EOF depends. Furthermore, a time-dependent EOF can also affect fluid flow because, in different instances, the AC will be at different points in its cycle.
The set-up of a microfluidic experiment can include mechanical pumping in parallel with EOF within a tiny chip shaped with channels and fitted with electrodes. The bulk movement can be provided by pressure. However, precise adjustments come easier when using EOF. Our solution is doped with ions that provide Newtonian force to the surrounding fluid from their coulombic-driven motion required from the present EF. The charged surface of the electrodes creates an electrical double layer, a phenomenon driven by the chemical interactions of ions and the charged surface material in an aqueous solution. When this first layer is formed, known as the stern layer, other ions are further attracted according to Coulomb’s law. Ions are attracted via the coulomb force screen in the first layer but are loosely attached and, therefore, more capable of influencing flow. However, because we use electrodes with an alternating current, the stern layer is also dynamic and thus influences the effects of electroosmosis and electrophoresis. Electrophoresis is the movement of ions or dielectrics in a uniform EF, such as direct current electroosmosis (DCEO). Dielectrophoresis, however, is concerned with the effect of non-uniform electric fields on ions and dielectrics, as in ACEO. Because of the non-uniform EF, ions are more dynamic than particles in DCEO. This increase in mutability makes ACEO ideal for mixing fluids. However, this mixing occurs on a micro-scale more suitable for research and analysis. Areas that utilize this technique include the following: lab-on-a-chip systems that enable fast and inexpensive mixing for analysis such as chemical and biological assays; drug delivery systems that take advantage of micromixing to ensure a homogenous solution for increased effectiveness; and chemical synthesis that requires precision when dealing with reactants; ACEO can provide better control over reaction conditions and results. Objects for mixing and transport within this experiment included chosen particles and cancer cell lines. Relevant to the concern of application towards cancer breast diagnostics, an insight was taken within the literature and the breast cancer cell lines, MD-MBA-231 and MCF-7, were selected for modeling, representing different cancers [
6,
22,
23,
24]. These were parameterized and added to the microfluidic device simulation.
In this study, our microchip includes three bands on either end that lead to a central chamber. The electrodes are placed throughout the channel, alternating from the top to the bottom of the chamber walls. The periodic placement of the electrodes is ideal for driving flow because they are placed so as not to counteract each other’s EF, thus interfering with the desired motion. Without pressure-driven flow, the electrodes only contribute enough to exhibit vortical particle movement corresponding to each pair of electrodes. The pair of electrodes plays a crucial role in creating a non-uniform EF as they have opposite polarities: one is a cathode, while the other is an anode. In sum, we are utilizing microfluidics to simulate and optimize the process of generating improved diagnostic and therapeutic discovery devices for breast cancer. Towards this end, within this paper, we emphasize that this work entails a set of simulations that ultimately will require physical validation through physical paired tests. Already, prior work has emphasized the importance of predicting cell trajectories and orientation in microdevices [
25,
26,
27]. Further, this work is not intended as a manufacturing aid and thus analyses of cost-effectiveness are beyond the scope of this work. Until then, this work functions as a theoretical aid towards improved cell separation to aid work in the microfluidic management of cell characterization and separation. Ultimately, our objective is to leverage microfluidic-based simulation approaches that can assist the development of improved diagnostic devices that can revolutionize breast cancer cell diagnostics.
4. Discussion
In order to fully grasp the intricacies of microfluidic devices used to transport biological molecules, it is crucial to examine the principles of dielectrophoresis (DEP) and the Clausius–Mossotti factor. DEP, as explained in detail by Doh and Cho (2005), involves the interaction between the dipole moment of neutral particles and non-uniform electric fields, allowing for the precise manipulation of particles in fluid environments [
28]. This process is precious in microfluidic devices, enabling tasks such as trapping, translation, and the focusing of biological analytes. Additionally, as Farasat et al. (2022) highlighted, the Clausius–Mossotti factor plays a pivotal role in determining the direction and magnitude of DEP forces applied to particles [
29]. Understanding these fundamental concepts is essential for optimizing the design and functionality of microfluidic devices, particularly in biomedical applications where the precise control over particle movement is crucial for effective separation and characterization processes.
Incorporating optimal parameters into the design of microfluidic devices for handling biological material is critical in maximizing device performance and efficacy. Doh and Cho (2005) discuss the application of hydrodynamic dielectrophoresis in continuous cell separation, emphasizing the significance of accurate control over cell movement within microchannels [
28]. Advanced valve-controlled systems for the simultaneous separation of positive and negative DEP cells can significantly improve throughput and efficiency [
28,
29]. Research in this area highlights the importance of electrode design, fluid flow control, and automation in optimizing microfluidic device performance for handling biological samples. Our simulation adds to the research towards this goal.
Upon analyzing the simulated device design, it has been determined that the microchannel consists of 16 electrodes, with 8 pairs in total. The anodes are situated at the channel’s top, while the cathodes are located at the bottom. All electrodes on the device are axisymmetric, with applied voltages of 1 V in the anodes and −2 V in the cathodes. The cathode’s largest electrode size is 200 microns, while the anodes measure 50 microns.
Figure 3 depicts the microchannel’s surface potential, while
Figure 4 illustrates the fluid flow with 0 nm/s inlet velocity. The maximum velocity recorded in this condition is 137.63 nm/s, with vortexes created between the anode and cathode due to the ACEO phenomenon, as seen at the end of the channel. When the pressure-driven flow is applied, a sinusoidal fluid flow pattern emerges and the maximum fluid velocity observed is 187.31 nm/s with 50 nm/s inlet velocity, as seen in
Figure 5. As expected, with increased inlet velocity, the maximum fluid velocity also rises, as shown in
Figure 6, where a clear sign wave and maximum 218.67 nm/s fluid velocity inside the channel are measured with 100 nm/s inlet velocity. Furthermore, a significant sign wave is observed in the last trial when the inlet velocity is 200 nm/s, as seen in
Figure 7, where the maximum velocity reaches 300.05 nm/s. This increase in pressure-driven flow leads to a rise in the maximum fluid velocity due to the ACEO phenomenon.
In the graphs displayed in
Figure 8, the maximum fluid velocity vs. time is illustrated at various frequencies. The data show a linear relationship between fluid velocity and time at 10 Hz, where as time increased, fluid velocity also increased. At the 15 s mark, the velocity of the fluid was measured at 40.31 nm/s. This same trend was observed at 100 Hz, where the maximum fluid velocity was 148.98 nm/s. However, 1000 Hz and 10,000 Hz produce different results. In both cases, fluid velocity increases from 0 to 10 s, but the trends show the opposite from 10 to 15 s.
Figure 9 depicts a velocity vs. time graph that shows a constant horizontal line at 10,000 Hz. At 100 Hz, the maximum fluid velocity displays a sinusoidal pattern. At a low frequency (10 Hz), the maximum fluid velocity was measured at 202.11 nm/s at 10 s.
Figure 10 shows no change in velocity vs. time graph for 100 Hz and 10,000 Hz cases. They showed the same trend as at 10 Hz and 1000 Hz, where their maximum fluid velocity was 100 nm/s.
Figure 11 displays the same velocity vs. the time graph at 10, 1000, and 10,000 Hz. The only change observed is at 100 Hz, where the maximum velocity was 211.38 nm/s at 10 s. It is worth noting that the ACEO phenomenon can be observed in
Figure 8,
Figure 9,
Figure 10 and
Figure 11.
To provide an overview, the microfluidic device is designed with a microchannel featuring three inlets and outlets, alongside eight pairs of electrodes on the side walls. The process involves injecting particles and cell mixtures at the bottom inlet, with fluid injection occurring at the middle and top inlets. Asymmetrically placed electrodes facilitate the creation of a non-uniform electric field, which is generated via the application of an AC electric field to the electrodes, resulting in DEP forces. Our study found that a positive DEP force is observed when the electrical polarization of particles and cells is higher than that of the surrounding medium, leading to their attraction. Conversely, an opposing DEP force occurs when the electrical polarization of particles and cells is lower than medium, resulting in their repulsion. Ultimately, the use of positive and negative DEP forces transport particles and cells in different directions, enabling their separation through the dielectrophoretic method.
The numerical results depicted in
Figure 13,
Figure 14,
Figure 15,
Figure 16,
Figure 17,
Figure 18,
Figure 19,
Figure 20 and
Figure 21 showcase the behavior of cells and particles under varying frequencies. At 100 kHz, all particles and cells underwent linear translation and were repelled towards the bottom outlet by negative DEP. At 800 kHz, the particles moved towards the bottom outlet while the MCF 7 and MDA-MB-231 cells were separated in the middle outlet (
Figure 14). The MDA-MB-231 cells experienced DEP at 1000 kHz (
Figure 15), while at the 1200 kHz frequency, particles, MCF 7, and MDA-MB-231 cells were successfully separated (
Figure 16). At 1500 kHz, the MDA-MB-231 cells exhibited rotational movement, while the MCF 7 cells underwent negative DEP force (
Figure 17). At 2200 kHz, particles and MCF 7 cells experienced a negative DEP force, and the MDA-MB-231 cells rotated counterclockwise and they experienced a positive DEP force (
Figure 19). At 4000 kHz, the particles and MCF 7 cells were directed towards the middle and top outlets, respectively, while the MDA-MB-231 cells remained in the microchannel. When the frequency was increased to 100 MHz, all the particles and cells were expelled from the bottom outlet due to negative DEP. The ultimate objective of this project was to effectively separate particles and cells, which was accomplished through the application of various frequencies.
We measured cell and particle separation in microfluidics devices by changing the frequency range from 10 kHz to 100,000 kHz. The cell size, conductivity and permittivity are given in
Table 1. The dielectrophoresis force depends on particle size. The results from the simulations revealed that the ACEO phenomenon plays an almost inconsequential role for cell and particle separations due to the very high frequency applied to electrodes. In this work, there are two forces acting on the cells and particles: one is the horizontal force, and another one is the vertical force. The horizontal force plays an important role when the hydrodynamics and dielectrophoresis forces work on cells/particles. For review, the dielectrophoresis force acts on cells when cells move in a vertical direction. At 100 kHz, the hydrodynamics and dielectrophoresis forces work both cells and particles as they separate at the bottom of the outlet. Both cells separated in the middle outlet, due to the permittivity difference between the cells and medium at 800 kHz; in this condition, both cells also experience more dielectrophoresis force than particles. When 1200 kHz is applied at electrodes, the MDA-MB-231 cells separate to the top outlet, the MCF-7 cells separated to the middle outlet and the particles go through the bottom outlet. In this case, both MDA-MB-231 and MCF-7 cells experience negative dielectrophoresis force due to permittivity of the medium being higher than the permittivity of cells.
Previous research and simulations confirm the efficacy of ACEO in microfluidics. Analytical results indicate that as the inlet velocity increases, the net velocity also increases. Our simulations validate this prediction. However, we observed a phenomenon at high frequencies when attempting to determine the frequency at which our three distinct cells separate. The results indicate that 1200 kHz is the optimal frequency that enables each cell type to exit through their designated outlets. At low frequencies (0.01–500 kHz), our cells exhibit minimal separation and exit through the bottom outlet. When the frequency reaches 1000 kHz, our simulation reveals that the AC affects the particles differently, which is critical for the separation process.
Moreover, our observations indicate that particle trajectory alteration does have a limit beyond which any increase in frequency yields minimal impact on particle trajectory. We discovered that subjecting the electrodes to 100,000 kHz of AC successfully reverted the particle trajectories to their original path of motion, after starting with low frequencies of EF. Additionally, our findings suggest that achieving particle separation is predominantly reliant on frequency rather than inlet velocity. Our simulation revealed a consistent trend of inlet velocity being directly proportional to net velocity, while holding the frequency of EF constant.
Ongoing research efforts are constantly refining microfluidic device designs to meet the changing demands of biomedical applications. The integration of novel technologies from multiple fields is necessary to push the boundaries of microfluidic device functionality and utility. While microfluidic devices are already frequently used for high-throughput screening and analysis, their small sample volumes can lead to issues with sample heterogeneity and accuracy. To address this issue, further research is needed to scale up these devices to handle larger sample volumes while maintaining high levels of precision and accuracy. Further, the construction of a physical device to validate this simulation work would be a meaningful step. Collaborating closely with experts in biology, chemistry, and engineering is essential to the development of microfluidic devices that are optimized for their intended applications. Interdisciplinary collaboration is critical to the continued advancement of microfluidics technology and the potential for groundbreaking discoveries in the field of biomedical research.
5. Conclusions
ACEO has an effective reach, not only in mixing and moving fluids, but also in separating them. We showed that particles can be filtered in a specific range of frequencies using ACEO. This separation depends on the material of the particles and pressure-driven flow. COMSOL offers quick numerical simulations to allow us to pinpoint the most effective frequency and inlet velocity to allow for this particle separation. In conclusion, using the dielectrophoretic method, the microfluidics device with eight pairs of electrodes showed promising results in separating particles and cells. The AC electric field generated using the electrodes created positive and negative DEP forces, which attracted or repelled particles and cells, separating them. The simulation results showed that the frequency of the AC electric field played a crucial role in the separation process. The ACEO phenomenon was also observed, which increased the fluid velocity and vortexes inside the microchannel. The simulation results agreed with the analytical results, which predicted an increase in net velocity with the increase in inlet velocity. This research provides a foundation for developing microfluidic devices for various applications, such as cell sorting, drug delivery, and biosensors. The dielectrophoretic method offers a non-invasive way to manipulate particles and cells, which is crucial in biological and medical applications.
Further research can focus on optimizing the microfluidic device design, electrode placement, and frequency to improve the separation efficiency. Additionally, the study can be extended to investigate the effects of different particle and cell types, sizes, and concentrations on the separation process. Overall, this research demonstrates the potential of microfluidics and dielectrophoresis in advancing biomedical research and applications.