Deterministic Lateral Displacement Separation Research Articles

Numerical Study on High Throughput and High Solid Particle Separation in Deterministic Lateral Displacement Microarrays

Deterministic lateral displacement (DLD) is a high-resolution passive microfluidic separation method for separating micron-scale particles according to their size. Optimizing these microsystems for larger throughputs and particle concentrations is of interest for industrial applications. This study evaluates the limitations of the functionality of the DLD separation principle under these specific conditions. For this reason, different particle volume fractions (up to 11%) and volumetric flow rates (corresponding to Reynolds numbers up to 50) were varied within the DLD microsystem and tested in different combinations. Resolved two-way coupled computational fluid dynamics/discrete element method (CFD-DEM) simulations including spherical particles were performed. The results show a general increase in the critical diameter with increasing volume fraction and decreasing separation efficiency. The largest tested Reynolds number (Re = 50) results in the highest separation efficiency, particularly at low volume fractions, and is only slightly less efficient than low Reynolds numbers as the volume fraction increases. The results indicate that by limiting the volume fraction to a maximum of 3.6%, the flow rate and the associated separation rate can be increased while maintaining a high separation efficiency.

Low-frequency electrokinetics in a periodic pillar array for particle separation

Deterministic Lateral Displacement (DLD) exploits periodic arrays of pillars inside microfluidic channels for high-precision sorting of micro- and nano-particles. Previously we demonstrated how DLD separation can be significantly improved by the addition of AC electrokinetic forces, increasing the tunability of the technique and expanding the range of applications. At high frequencies of the electric field (>1 kHz) the behaviour of such systems is dominated by Dielectrophoresis (DEP), whereas at low frequencies the particle behaviour is much richer and more complex. In this article, we present a detailed numerical analysis of the mechanisms governing particle motion in a DLD micropillar array in the presence of a low-frequency AC electric field. We show how a combination of Electrophoresis (EP) and Concentration-Polarisation Electroosmosis (CPEO) driven wall-particle repulsion account for the observed experimental behaviour of particles, and demonstrate how this complete model can predict conditions that lead to electrically induced deviation of particles much smaller than the critical size of the DLD array.

Multichannel impedance cytometry downstream of cell separation by deterministic lateral displacement to quantify macrophage enrichment in heterogeneous samples.

The integration of on-chip biophysical cytometry downstream of microfluidic enrichment for inline monitoring of phenotypic and separation metrics at single-cell sensitivity can allow for active control of separation and its application to versatile sample sets. We present integration of impedance cytometry downstream of cell separation by deterministic lateral displacement (DLD) for enrichment of activated macrophages from a heterogeneous sample, without the problems of biased sample loss and sample dilution caused by off-chip analysis. This required designs to match cell/particle flow rates from DLD separation into the confined single-cell impedance cytometry stage, the balancing of flow resistances across the separation array width to maintain unidirectionality, and the utilization of co-flowing beads as calibrated internal standards for inline assessment of DLD separation and for impedance data normalization. Using a heterogeneous sample with un-activated and activated macrophages, wherein macrophage polarization during activation causes cell size enlargement, on-chip impedance cytometry is used to validate DLD enrichment of the activated subpopulation at the displaced outlet, based on the multiparametric characteristics of cell size distribution and impedance phase metrics. This hybrid platform can monitor separation of specific subpopulations from cellular samples with wide size distributions, for active operational control and enhanced sample versatility.

Deterministic Lateral Displacement (DLD) Analysis Tool Utilizing Machine Learning towards High-Throughput Separation.

Deterministic lateral displacement (DLD) is a microfluidic method for the continuous separation of particles based on their size. There is growing interest in using DLD for harvesting circulating tumor cells from blood for further assays due to its low cost and robustness. While DLD is a powerful tool and development of high-throughput DLD separation devices holds great promise in cancer diagnostics and therapeutics, much of the experimental data analysis in DLD research still relies on error-prone and time-consuming manual processes. There is a strong need to automate data analysis in microfluidic devices to reduce human errors and the manual processing time. In this work, a reliable particle detection method is developed as the basis for the DLD separation analysis. Python and its available packages are used for machine vision techniques, along with existing identification methods and machine learning models. Three machine learning techniques are implemented and compared in the determination of the DLD separation mode. The program provides a significant reduction in video analysis time in DLD separation, achieving an overall particle detection accuracy of 97.86% with an average computation time of 25.274 s.

Effect of Viscosity on High-Throughput Deterministic Lateral Displacement (DLD)

Biosample analysis often requires the purification, separation, or fractionation of a biofluid prior to transport to the biosensor. Deterministic lateral displacement (DLD) is a size-based microfluidic separation technique that shows promise for biosample preparation. Recently, high-throughput DLD separation has been demonstrated with airfoil-shaped pillars at higher flow rates, but this also changes separation dynamics as the Reynolds number (Re) increases. In this work, the particle trajectories in the airfoil DLD with two different angle-of-attacks (AoAs) were studied at a range of Re with alterations of fluid viscosity to mimic biological fluids. Previous studies have found that the critical diameter (Dc) decreases as Re climes. We demonstrated that variations of the fluid viscosity do not alter the separation dynamics if the Re is kept constant. As the associated Re of the flow increases, the Dc decreases regardless of viscosity. The negative AoA with an airfoil DLD pillar design provided the stronger Dc shift to negate pressure increases.

Deterministic Lateral Displacement Using Hexagonally Arranged, Bottom-Up-Inspired Micropost Arrays.

Size-based separation of particles in microfluidic devices can be achieved using arrays of micro- or nanoscale posts using a technique known as deterministic lateral displacement (DLD). To date, DLD arrays have been limited to parallelogram or rotated-square arrangements of posts, with various post shapes having been explored in these two principal arrangements. This work examines a new DLD geometry based on patterning obtainable through self-assembly of single-layer nanospheres, which we call hexagonally arranged triangle (HAT) geometry. Finite element simulations are used to characterize the DLD separation properties of the HAT geometry. The relationship between the array angle, the gap spacing, and the critical diameter for separation is derived for the HAT geometry and expressed in a similar mathematical form as conventional parallelogram and rotated-square DLD arrays. At array angles <7°, HAT structures demonstrate smaller particle sorting capability (smaller critical diameter-to-gap spacing ratio) compared to published experimental results for parallelogram-type DLD arrays with circular posts. Experimental validation of DLD separation confirms the separation ability of the HAT array geometry. It is envisioned that this work will provide the first step toward future implementation of nanoscale DLD arrays fabricated by low-cost, bottom-up self-assembly approaches.

Cell Sorting Using Electrokinetic Deterministic Lateral Displacement.

We show that by combining deterministic lateral displacement (DLD) with electrokinetics, it is possible to sort cells based on differences in their membrane and/or internal structures. Using heat to deactivate cells, which change their viability and structure, we then demonstrate sorting of a mixture of viable and non-viable cells for two different cell types. For Escherichia coli, the size change due to deactivation is insufficient to allow size-based DLD separation. Our method instead leverages the considerable change in zeta potential to achieve separation at low frequency. Conversely, for Saccharomyces cerevisiae (Baker’s yeast) the heat treatment does not result in any significant change of zeta potential. Instead, we perform the sorting at higher frequency and utilize what we believe is a change in dielectrophoretic mobility for the separation. We expect our work to form a basis for the development of simple, low-cost, continuous label-free methods that can separate cells and bioparticles based on their intrinsic properties.

A Microfluidic Prototype System towards Microalgae Cell Separation, Treatment and Viability Characterization.

There are a huge number, and abundant types, of microalgae in the ocean; and most of them have various values in many fields, such as food, medicine, energy, feed, etc. Therefore, how to identify and separation of microalgae cells quickly and effectively is a prerequisite for the microalgae research and utilization. Herein, we propose a microfluidic system that comprised microalgae cell separation, treatment and viability characterization. Specifically, the microfluidic separation function is based on the principle of deterministic lateral displacement (DLD), which can separate various microalgae species rapidly by their different sizes. Moreover, a concentration gradient generator is designed in this system to automatically produce gradient concentrations of chemical reagents to optimize the chemical treatment of samples. Finally, a single photon counter was used to evaluate the viability of treated microalgae based on laser-induced fluorescence from the intracellular chlorophyll of microalgae. To the best of our knowledge, this is the first laboratory prototype system combining DLD separation, concentration gradient generator and chlorophyll fluorescence detection technology for fast analysis and treatment of microalgae using marine samples. This study may inspire other novel applications of micro-analytical devices for utilization of microalgae resources, marine ecological environment protection and ship ballast water management.

Numbering-up Strategies for Microfluidics-assisted Water Treatment Processes: Deterministic Lateral Displacement for the Removal of Bacteria and Parasites as a Case Study

Microfluidic channels filled with spatially periodic arrays of impermeable obstacles have been proved successful for the size-based continuous separation of mesoscopic objects suspended in a buffer solution with unprecedented resolution. To date however, this technique - referred to as Deterministic Lateral Displacement (DLD) - has been implemented only for small volume samples, mainly for analytical purposes. In this article, we investigate the feasibility of the DLD separation technique for water purification from bacteria. The accurate numerical solution of the three-dimensional Stokes flow problem is used to establish the hydraulic resistance of several different geometries of the unit periodic cell. Results suggest that DLD-based microfilters resulting from numbering-up DLD microseparation units could provide sizeable flowrates and could prove competitive when compared to membrane-based modules.

Vortex-free high-Reynolds deterministic lateral displacement (DLD) via airfoil pillars

One essential step in biosample analysis is the purification, separation, or fractionation of a biofluid prior to transport to the biosensor. Deterministic lateral displacement (DLD) has demonstrated the potential for continuous size-based separation of numerous medically relevant particles and organisms, such as circulating tumor cells, red blood cells, and even viral particles. Recently, high-throughput DLD separation has been demonstrated by utilizing higher flow rates, but this also results in changing separation dynamics as the Reynolds number (Re) increases. It has been observed that the critical diameter (Dc) for a DLD device decreases as Re climbs, and theorized that both streamline compression and vortex emergence may contribute to this phenomenon. The precise mechanism for this shift has been difficult to isolate, however, due to the coupled nature of vortex emergence and streamline compression in high-Re DLD devices with circular pillars. To decouple these effects, we have characterized the performance of a DLD device with symmetric airfoil pillars that do not produce vortices up to Re = 100. In demonstrating a complete particle trajectory shift at Re = 51, we have shown that vortex effects are not a predominant contributor to this Dc shift, thus streamline evolution is likely to be the primary mechanism. Furthermore, we have compared the performance of this device to a similar device with rotated pillars having a negative 15° angle of attack, and found that separation effectiveness declines as streamlines become highly asymmetric and small particles exhibit significant variation in their trajectories.

Deterministic displacement of particles and oil droplets in a cross-flow microsieve module

Our investigation aims to apply Deterministic Lateral Displacement (DLD) to separate (deformable) particles or droplets from dispersions on industrial scale. DLD is a promising technique because it can separate particles smaller than the pores. Previous work shows how to manipulate the critical particle diameter in a sieve-based lateral displacement system by modifying the hydrodynamics. In this study, we apply this fundamental understanding of the DLD separation principle to deterministically displace particles in a cross-flow microsieve module. First, two-dimensional simulations of the fluid dynamics in this cross-flow module were performed to investigate the hydrodynamic conditions required for particle displacement. Next, these simulations were compared with the flow fields visualized in the experimental setup. In addition, high speed recordings confirmed deterministic displacement of particles and oil droplets over the microsieve surface. Last, the systems performance was evaluated by measuring the transmission of rigid PMMA particles and deformable hexadecane droplets and the particle size distribution for different operation conditions. These results clearly demonstrate that the DLD principle can be effectively applied in a cross-flow microsieve module. With this, the application of this microfluidic separation principle to separate particles or droplets (1–20 µm) from dispersions on industrial scale has become realistic.

Purification of complex samples: Implementation of a modular and reconfigurable droplet-based microfluidic platform with cascaded deterministic lateral displacement separation modules.

Particle separation in microfluidic devices is a common problematic for sample preparation in biology. Deterministic lateral displacement (DLD) is efficiently implemented as a size-based fractionation technique to separate two populations of particles around a specific size. However, real biological samples contain components of many different sizes and a single DLD separation step is not sufficient to purify these complex samples. When connecting several DLD modules in series, pressure balancing at the DLD outlets of each step becomes critical to ensure an optimal separation efficiency. A generic microfluidic platform is presented in this paper to optimize pressure balancing, when DLD separation is connected either to another DLD module or to a different microfluidic function. This is made possible by generating droplets at T-junctions connected to the DLD outlets. Droplets act as pressure controllers, which perform at the same time the encapsulation of DLD sorted particles and the balance of output pressures. The optimized pressures to apply on DLD modules and on T-junctions are determined by a general model that ensures the equilibrium of the entire platform. The proposed separation platform is completely modular and reconfigurable since the same predictive model applies to any cascaded DLD modules of the droplet-based cartridge.

DLD pillar shape design for efficient separation of spherical and non-spherical bioparticles.

Particle sorting methods in microfluidic platforms are gaining momentum for various biomedical applications. Bioparticles are found in different shapes and sizes. However, conventional separation techniques are mainly designed for separation of spherical particles. Thus, there is a need to develop new methods for effective separation of spherical and non-spherical bioparticles for various applications. Deterministic lateral displacement (DLD) microfluidic methods have become popular for high separation resolution, simplicity, and predictability. However, shape sorting in the DLD separation methods is not well researched. Recently, we explored this area and found that pillar shapes in DLD significantly affect bioparticle separation. In this work, we designed a group of different pillar shapes with protrusions and groove structures with the hypothesis that pillar protrusions will induce particle rotation while pillar grooves will confine the particle rotational movement in a directed path for effective separation in a DLD pillar array. Using combinations of protrusions and grooves, 3-dimensional spherical particles, 2-dimensional planar disc-shaped red blood cells and 1-dimensional rod-shaped bacteria were separated and two interesting phenomena were observed. Firstly, the arrangement of pillar protrusions and grooves induces inertial movements, enhancing the separation of spherical particles. Secondly, non-spherical particles experience dominant rotational movements due to the protrusions and grooves which help in changing their orientations. This gives an opportunity to perform efficient separation based on the desired orientation (the longest dimension of the particles) by restricting or containing their movement within a specific DLD path.