Microfluidic Routing via Dynamic Optical Lattices
Ryan L. Smith*, G. C. Spalding*, M. P. MacDonald, S. L. Neale, K. Dholakia
*Department of Physics, Illinois Wesleyan University, P.O. Box 2900, Bloomington, IL
USA 61702-2900.
SUPA, School of Physics and Astronomy, University of St Andrews, North Haugh, St.
Andrews, Fife, KY16 9SS
ABSTRACT
All optical manipulation has been shown to provide unprecedented non-invasive control
over a variety of different substances in the micro regime. It is especially useful for
passive sorting of colloid in a microfluidic flow. When sorting a flow it is not only how
well the particles intended to be routed are routed but also the throughput of the system.
Any commercial system needs the time it takes the colloid to be sorted to be practical in
order for mainstream acceptance. We investigate injection widths as well as various
methods of lattice control to maximize efficiency throughput for microfluidic sorting.
1. INTRODUCTION
Non-invasive control at the micro-scale has become a subject of great interest and
enormous promise. Methods utilizing optical forces alone offer a number of clear
advantages, including ease of integration and reconfigurability. In particular, several
geometries have recently been demonstrated for sorting materials entrained in
microfluidic flows. All-optical chromotagraphy has now been used to sort designed
proxies for anthrax spores and other bioterrorism agents from a background of pollen and
other species1. Elsewhere, the response to optical forces has been used to separate
metastatic cancer cells from less aggressive cancer cells and from normal cells2 and,
separately, to sort stem cells out from a background of differentiated cells. These new
approaches have been incorporated into lab-on-a-chip technology for clinical trials that
are currently underway.
2. SORTING IN STATIC OPTICAL LATTICES
Our own approach3, which holds potential for higher throughput screening, has
centered upon the use of passive optical lattices. Optical lattices of this type can be
generated in a number of ways. One method is through use of a spatial light modulator
(SLM) to modify the phase of your light. Real-time 3D control over multiple trapping
sites has been shown (cite Miles, Jean-Marc’s Talbot effect). In addition, the use of a 3D
lattice with multiple trappable particles has been used to create assisted self-assembly of
3D lattices (cite alfons). Jesper Gluckstad has demonstrated the fine level of control by
using an SLM to modify the phase of the light and thus change the position, size, shape
and intensity of each individual trap (cite OE paper by Jesper).
Although SLMs provide precision control over multiple optical traps, for some
applications multibeam interference has its advantages. We interfere between two and
five beams to create a symmetric lattice of varying geometries5. The beams are created by
passing a single beam through a static diffractive optical element (DOE). This is ideal in
many cases due to the fact that they are relatively cheap to produce and allow the setup to
be fairly compact compared to the table space required for a setup using an SLM. In
addition using multibeam interference grants control that is not attainable using an SLM.
We require a polarization change on a single one of the incident beams. SLMs cannot
grant you this level of control and thus are not ideal for our setup. In addition, for many
applications the refresh rates attainable by liquid crystal phase modulating SLMs are not
fast enough.
We have used studies of “wide-band” injection of monodisperse colloid into optical
lattices to determine the optimal injection and collection geometries for microfluidic
devices.
Fig. 1. Collection into optical channels vs. flow speed.
Fig. 2. We observe a one-third micron shift in the deflected output for each
microliter/hour increase in flow speed
It is evident from Figure 2 that increasing the flow speed will reduce the uptake
stream centriod in a linear manner. This is important when trying to maximize efficiency
throughput for a given stream due to the fact that as we increase throughput, we reduce
efficiency.
Fig. 3. Measure of efficient throughput for different injector centers and an injection
width of 6 microns
In addition we analyzed the efficient throughput based on where the injector
center is located. We also did analysis on lateral velocity based on position in the lattice.
That is shown in Figure 4 below.
Fig. 4. Y velocity vs Y position. It is evident that the lateral velocity is at a maximum
when the colloid is in the center of the Gaussian lattice profile.
One of the main problems with filling a close-packed lattice of traps is that the
periphery traps fill with colloid and then block the interior traps from being filled (cite
Ming Wu). A similar problem occurs in our setup at lower flow rates. As colloid is being
passed through the lattice, if the gradient force from the light is stronger than the force
exerted by stokes drag, the particles will not exit the lattice and “jamming” will occur.
This problem is countered by using the Angular Doppler (AD) effect to translate the
lattice. This effectively eliminates the jamming that was evident in the static lattice.
3. SORTING IN DYNAMIC LATTICES
From this we can introduce a frequency shift by using a rotating waveplate and
the AD effect (cite Arlt, kishan, mike, etc). To produce this effect we used circularly
polarized incident light. We then select one of the five incident beams and pass it though
a half-waveplate. Under normal circumstances this would simply switch the
“handedness” of the circularly polarized light from   to   . In our setup we have the
half-waveplate rotating. This rotation grants a constant phase shift that is equivalent to a
frequency change in the beam that is passing through the half-waveplate. When this beam
interferes with the other beams that are not observing the frequency shift, it creates a
dynamic three-dimensional lattice that translates in a certain direction. We investigate
how this effects three-dimensional routing of colloid passing through the lattice in a
microfluidic flow.
We first examined a lattice with a 10-degree orientation with respect to the input
flow. From this data we were able to gather that the static lattice provided a lower failure
rate when the injection stream was set at 30 pixels. With this said, it was evident that the
particles that were being routed in the AD stream were being routed further up in the y
direction than necessary. Based on this observation, we looked at the routing efficiency
for larger input stream values. As we suspected, increasing the size of the input stream
made the efficiency of the Angular Doppler data greater than that of the static lattice.
Fig 5. Routing efficiency for the static lattice (left) and the AD lattice (right) at a lattice
angle of 10 degrees. The yellow portion is the injection width, the red tracks are
unrouted tracks and the green tracks are routed tracks.
We also examined the tracks at a lattice angle of 35 degrees. From this data we
found that for narrower input streams the AD lattice offered a higher routing efficiency
but for wider input streams the static lattice offered greater routing efficiency. This is
displayed in Figure 6.
Fig 6. Routing efficiency vs. Injection width for a static and AD lattice.
4. CONCLUSION
In two dimensions, we have successfully demonstrated an approach that allows
optical forces alone to assemble and/or guide large ensembles of microparticles over
macroscopic areas4. The formation of static three-dimensional structures pose greater
challenges, as the scattering of light by particles in one layer perturbs the optical
landscape that is applied to particles in subsequent layers. At powers low enough to avoid
unacceptable heating/convection, optical forces are typically weak, and scattering greatly
complicates efforts to build 3D static structures via optical trapping alone. Early efforts at
filling a 3D lattice of optical traps led to an appreciation for the dynamics of injected
microparticle streams, which yield a surprisingly successful method of sorting or rerouting within microfludic environments3.
We have investigated the optimal injection widths to maximize efficiency
throughput of sorted colloid in a microfluidic flow. In addition we have introduced a
novel method for translating the lattice in an effort to prevent jamming in the flow.
Although results from this method are not currently conclusive, the method overall
provides a promising landscape for future studies.
5. ACKNOWLEDGEMENTS
R.L.S. and G.C.S. were supported by a grant from the Petroleum Research Fund.
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