supplementary information - nature research · supplementary figure 2. fluorescent polystyrene...

NATURE NANOTECHNOLOGY | www.nature.com/naturenanotechnology 1

SUPPLEMENTARY INFORMATIONDOI: 10.1038/NNANO.2016.134

Nanoscale Lateral Displacement Arrays for Separation of Exosomes and Colloids

Down to 20nm

Benjamin H. Wunsch, Joshua T. Smith, Stacey M. Gifford, Chao Wang, Markus Brink, Robert Bruce, Robert H.

Austin, Gustavo Stolovitzky, and Yann Astier

SUPPLEMENTAL INFORMATION

1. Array structures

Nanofluidic chips were fabricated on 200 mm wafers (Supplementary Fig. 1a) to enable high-quality

fluorescence imaging of nanoscale polymer beads and bio-colloids when coupled with a custom fluidic

jig as described elsewhere.1

Optical contact lithography followed by a combination of electron beam (e-

beam) and deep-ultra violet (DUV) lithography schemes were utilized consecutively to define

microchannel and nanofluidic pillar array features (Supplementary Fig. 1b), respectively, in an SiO2

hard mask on bulk silicon substrates. Following hard mask definition, all features were transferred into

silicon in tandem using a reactive-ion etch (RIE).

Two dimensional Fast Fourier transform (FFT) analysis of the arrays (Supplementary Fig. 1c)

confirmed a maximum angle, θmax, of 5.8° very close to the design value of 5.7°. θmax = 5.7° was chosen

as it corresponds to a relatively small row shift fraction δ = 0.1 leading to a well-defined row repeat N =

10, where θmax = tan-1

(δ) and N = 1/ δ.2

Having a precise N simplifies design criteria while a small δ

increases the efficiency of a particular gap size in sorting the smallest possible particle, since the critical

diameter Dc to sort a particle in the parabolic flow model is given by Dc = 2αGδ with α being a scaling

factor depending on the flow profile and G is the distance between pillars. This sorting efficiency

becomes crucial to induce sorting of very small entities such as proteins, particularly as gaps are scaled

in the tens of nanometers regime, pushing the limits of fabrication and ability to effectively wet these

features.

Supplementary Figure 1d shows the cross-sectional SEM image of a G = 134 nm pillar array. Gap

sizes for each array tested were determined by measuring 3 randomly chosen sets of 5 adjacent gaps

across the ~35 µm width of the pillar arrays (an average of 15 gaps per array), including 1 set chosen

near the array center and the other 2 sets nearer to each edge of the array. Gap variation from pillar top

to bottom was minor but not negligible so measurements were taken at pillar mid-height as indicated by

the dotted line in Supplementary Figure 1d. Thermal oxidation after pillar etching on parallel-processed

wafers permitted controllable means of tuning of the gap size to effectively narrow the gap to a desired

width based on the results from an SEM cross-section of a send-ahead wafer for each array fabricated.

Nanoscale lateral displacement arrays forthe separation of exosomes and colloids

down to 20 nm

© 2016 Macmillan Publishers Limited. All rights reserved.

http://dx.doi.org/10.1038/nnano.2016.134

2 NATURE NANOTECHNOLOGY | www.nature.com/naturenanotechnology

SUPPLEMENTARY INFORMATION DOI: 10.1038/NNANO.2016.134

Supplementary Figure 1. Fabricated fluidic chips containing sorting arrays with maximum angle θmax = 5.7º. (a)

Fluidic chips printed on a 200mm wafer using mixed DUV and electron beam lithography. (b) Optical image

showing microfluidic channels joined by nanochannel features, including pillar-sorting arrays. (c) 2D FFT

confirming successful patterning of the design angle θt (d) Scanning electron microscope image of a sorting array

with pillar pitch λ = 400nm and G = 134nm. Gap scaling and uniformity is demonstrated through RIE optimization

and thermal oxidation of the Si posts, permitting well-controlled gap widths.





2. Fluorescent bead size distribution

Supplementary Figure 2. Fluorescent polystyrene beads. (a-c) Example SEM images of DP = 110 nm (a), 50 nm

(b) and 20 nm (c) beads coated with a layer of evaporated Ti / Au (1 nm / 10 nm). Scale bars represent 200

nm. (d) Histograms of bead diameters measured from SEM images. (e) Properties of bead samples used in

nanoDLD experiments. a: Mean diameter ± standard deviation.





3. Analysis of nanoDLD fluorescence microscopy images for particle behavior

3.1 Analysis of fluorescent polystyrene bead displacement:

Fluorescence image videos of the array outlet are analyzed using custom software to determine the

migration angle of the displaced particle flux. In the current array configuration, the flux of particles

across the array is displaced towards the collection wall, forming a fluorescent, triangular pattern (white

triangle on Supplementary Fig. 3a). A depletion region, where particles have been displaced out,

appears on the opposite side of the array from the collection wall (dark triangle in Supplementary Fig.

3a). The extent of this depletion region at the outlet of the array determines the lateral displacement,

∆W, of the particle flux. Determination of the lateral displacement is complicated by the fact that the

edge of the particle flux, seen in the cross-section of fluorescence intensity across the array outlet, has

a continuous form with no sharp cut-off. We estimate the “edge” of the particle flux, and thus ∆W, using

the inflection point of the fluorescence intensity (Supplementary Fig. 3b). This assumes that the

fluorescent intensity distribution corresponds to the particle density distribution.

Supplementary Figure 3: Determination of lateral displacement from particle fluorescence images. (a) Schematic

of nano-DLD array showing particle flux entering from left (inlet) to right (outlet). Particles are displaced upwards

towards the collection wall of the array, forming a fluorescent triangle pattern (wedge), from which the migration

angle, θ, and lateral displace, ∆W, can be measured. The lateral displacement is taken at the outlet of the array.

In the schematic, the particles are completely displacing (bumping mode) so θ = θmax = 5.7º, the maximum angle

of the arrays used in this work. (b,c) Plots of fluorescent line profiles taken at the outlets of arrays for (b) complete

displacement and (c) partial displacement modes. The red lines show the 1st

derivative of the fluorescent line

profiles after smoothing, whose maximum corresponds to the inflection point (black dot). The lateral displacement,

∆W, is taken as the distance between the bottom wall of the array (opposite the collection wall) and the inflection

30 32 34 36

0.00

0.03

0.06

No

rm

alized

C

ou

nt (A.U.)

Lateral Position (µm)

-0.06

0.00

0.06

1st D

erivative

No

rm

alized

C

ou

nt (A.U.)

0 12 24 36

0.000

0.005

0.010

No

rm

alized

C

ou

nt (A.U.)

Lateral Position (µm)

-0.002

-0.001

0.000

0.001

1st D

erivative

No

rm

alized

C

ou

nt (A.U.)

Triangle (Particle Fluorescence)

Inlet Outlet

Flow

Collection Wall

Displacement

θ

Nanopillar Array

∆W

L





point. Using the length of the array, L, and the lateral displacement, ∆W, the migration angle can be calculated

from tan(θ) = ∆W/L. The blue line in (c) is the 1st

derivative taken before a 50-point smooth of the data (red line).

The migration angle, θ, is defined as tan(θ) = ∆W L-1

, where L is the length of the array. For a completely

displaced particle sample, all particles end up at the collection wall at the end of the array, and θ = θmax

= 5.7°, the maximum angle of the array. For no displacement, the particle flux covers the entire outlet,

and θ = 0.

The displacement efficiency is defined as:

� =

∆�

�

=

tan�

tan��

~

�

��

=

�

100

To compare the effectiveness of sorting particles for a given DP and G, a figure of merit, FOM, is defined

as the ratio between the lateral displacement of the particles, and the distance needed to fully displace

the particles across the array:

�� = tan � = ηtan��

From the definition of the figure of merit, the full-displacement length can be defined as:

��=

�

��

The parameter LC is the length of an array required to fully bump a particle to the collection wall,

assuming the particle starts at the far wall of the device channel.





Supplementary Figure 4. Polystyrene fluorescent bead displacement as a function of particle diameter, DP,

compared to critical diameter needed for displacement in a parabolic flow according to the lane model of DLD.

Bead values are given for a given row shift fraction, δ = 0.10, and scaling ratio DPG-1

. Value shading represents

the percentage maximum angle, P. The black line is the calculated critical diameter scaling ratio, DCG-1

~1.16 δ0.5

.3

According to the lane model of DLD, beads with scaling ratios below the critical line should exhibit zigzag mode,

P = 0%, and not displace within the array, while those above should show complete displacement, P = 100%.

0.0 0.1 0.2

0.0

0.1

0.2

0.3

0.4

0.5

0.6

110

50

50

50

50

2020

20

20

20

Sc

alin

g R

atio

, D

P

G

-1

Row Shift Fraction, ε

0.000

20.00

40.00

60.00

80.00

100.0

P

Zigzag Mode

Bump Mode

δ





Supplementary Figure 5. (a) (Left) Optical microscope image, 20x magnification, of a typical full-width injection

nanoDLD device, showing the overall configuration of the array. (Center) SEM images of inlet and outlet regions

bordering the nanoDLD array. (Right) Fluorescence microscopy images of fluorescent polystyrene beads flowing

into the inlet region (top row) and exiting the array outlet region (bottom row), corresponding to those shown in the

SEM images. The lateral displacement modes for zigzag, partial, and bumping are shown for Dp = 20 nm / G =

214 nm, Dp = 50 nm / G = 134 nm, and Dp = 110 nm / G = 235 nm, respectively. The migration angle, θ, indicates

the lateral displacement of the particle flux in the array. (b) Percentage maximum angle of fluorescent polystyrene

beads displaced in nano-DLD arrays as a function of the scaling ratio between particle diameter and gap size.

Nominal bead diameters are 110 nm (red squares), 50 nm (cyan circles) and 20 nm (blue triangles). Error bars

represent the standard deviation of at least three independent experiments. The line at DpG-1

= 0.37 represents

the theoretical critical diameter DC, calculated according to the DLD lane model in parabolic fluid flow, at which

beads are expected to be in bumping mode. P = 100% corresponds to complete displacement of beads (bumping

mode), P = 0% corresponds to no displacement (zigzag mode), and 0% < P < 100% indicates partial displacement

mode.





Supplementary Table 1. Performance parameters for nanoDLD displacement of fluorescence

polystyrene beads.

3.2 Analysis of Exosome Displacement:

For exosomes, single-particles trajectories are recorded in fluorescence microscope images, instead of

a flux density, as in the case of fluorescent polystyrene beads. We obtain a distribution of single-particle

events instead of a continuous distribution determined by the average fluorescence density. In general,

flowing particles form a streak or “trace” in a given video frame. For each particle observed, the location

of the head of the particle’s trace is manually marked per frame of video. The collection of x,y-coordinate

pairs taken from the combined number of frames (typically 200) defines the trajectory of the particle

within the image frame of the video. From the collected θ of all the single-particle trajectories, a

histogram of the distribution of particles based on their deflection can be generated. This distribution

gives the spread of particle positions after traveling 70 µm from the inlet. From the histogram the

migration angle, θ, can be obtained as tan(θ) = ∆W / 70. Supplementary Figure 6 shows the main

steps in the data analysis.

Particle Diameter,

DP

(nm)

Array Gap

Size, G (nm)

Scaling Ratio,

DP/G

Percent Maximum

Angle, P (%)

Displacement

Efficiency, η

Figure of

Merit, FOM

Full Displacement

Length, LC

(mm)

110 235 0.47 99.1 ± 1.4 99.1% 0.099 0.36

50 235 0.21 22.0 ± 1.8 21.9% 0.022 1.64

50 214 0.23 32.6 ± 4.5 32.5% 0.032 1.11

50 134 0.37 56.0 ± 10.5 55.9% 0.056 0.65

50 118 0.42 88.0 ± 15.7 87.9% 0.088 0.41

20 42 0.48 31.9 ± 4.8 31.8% 0.032 1.13





Supplementary Figure 6. Exosome particle analysis in nanoDLD array. (a) Composite fluorescent microscopy

image of a typical exosome particle trajectory in a G = 235 nm array. Scale bar is 10 µm. For each frame of the

trajectory, the position of the particle’s trace is recorded. The combined coordinates for each trajectory can be

offset to form a unified starting position plot, (b), which shows the spread in the exosome particle ensemble. The

black line at lateral position W = 0 µm is the ideal zigzag mode trajectory, and at W = 8.1 µm the ideal bump

mode trajectory. The dashed line at W = 4.8 µm is the ideal trajectory at the mean ending lateral displacement,

∆W. The displacement of each trajectory can be calculated to generate the histogram in (c) which gives the

distribution of exosome particles in the lateral direction of the nanoDLD after traveling 70 µm.





4. Electron Microscopy of Exosomes

For scanning electron microscopy, SEM, sample preparation was carried out by first applying 1 droplet

of exosome solution on a glass slide and letting it dry in a sterile environment. A 2 nm conductive metal

layer was sputtered onto the sample using a Hummer Sputter System (Anatech Ltd.) with a Au:Pd, 60:40

target. Imaging was performed with a Zeiss Leo 1560 Scanning Electron Microscope at 5k eV.

Cryo-electron microscopy was contracted out to the Electron Microscopy Resource Laboratory in the

Perelman School of Medicine, University of Pennsylvania. Sample preparation and imaging was carried

out by Dr. Dewight Williams. For sample preparation, 10 µL of as-obtained human urine derived

exosomes were diluted to 25 µL using PBS. Supplementary Figure 7 shows a typical EM image of the

as-obtained exosomes.

Supplementary Figure 7. Cryo-electron microscopy image of as-obtained human urine derived exosomes.





5. Modeling of Exosome Displacement Distribution

The simulated exosome displacement distribution was generated to compare with the measured

displacement histogram. As the simulated distribution makes use of the exosome size distribution, this

model allows us to determine if the measured exosome particle size distribution taken from SEM is

consistent with the displacement dynamics which depends of particle size. The model is based on the

same principles used by Heller and Bruss.4

The displacement histogram gives the lateral displacement

measured for each exosome trajectory after travelling a distance ∆L = 70 µm from the array inlet, at vob

= 253 µm s-1

(the average speed of the exosomes). It is important to note that the measured

displacement histogram is based on offsetting all particle trajectories to a single starting origin, ∆W = 0.

Lateral displacement can cause the particle distribution to shift to positive x, while diffusion will spread

the distribution in both positive and negative x. For modeling, the particle sizes were taken from the

binning of the SEM data, with Dp = 20-140 nm, with ∆Dp = 10 nm. For each particle size, the scaled

distribution was modeled with a Gaussian function. The model accounts for diffusion by computing the

Stokes-Einstein bulk diffusivity for each particle size.

� =

��3��

�

With T = absolute temperature, k = Boltzmann’s constant, and µ is the shear viscosity of water (1·10-5

kg cm-1

s-1

) The full-width at half max, w, of the Gaussian was determined from the diffusion over the

given time, τ, calculated from the distance and speed of travel.

� = ∆��

� = 2.355√2��

The position of the mean of the Gaussian, x0, was determined from the parameterized percentage

maximum angle, P, data taken for the polystyrene beads in a G = 235 nm nanoDLD array. The lateral

displacement, ∆W, is calculated from the parameterized P.

��= Δ� = Δ� tan��

��

With θmax = 5.7⁰. The distribution Fi for the ith particle size was calculated at each lateral displacement

position, ∆W = [-15,15] µm, and the distributions summed to form the final displacement distribution, F.





��Δ�� =

1.17��

��

�

�

��.��

��

�

��

�� = ��Δ��

�

With Ai the normalized frequency of the ith particle size as measured from SEM.

Supplementary Figure 8 shows a plot of final displacement distribution, F, and individual Gaussians,

Fi, showing the major contribution of the distribution density comes from particles with Dp = 50-80 nm.

Supplementary Figure 8. Modeled exosome displacement distribution. Plot of the total summed curve (dashed

red line) and individual Gaussian distributions (black line, red shading), normalized by the summed curve

integrated area. The main Gaussians contributing to the model distribution are labeled with the binned exosome

size, Dp, showing that the majority of the model curve comes from contributions of particles between 50-80 nm.

-10 -5 0 5 10

0.00

0.05

0.10

0.15

Summed Curve

90 nm

80 nm

70 nm60 nm

50 nm

Normalized Particle Count

Exosome Displacement, ΔW (μm)





6. Fractionation of Exosomes

Supplementary Figure 9. Hypothesis testing of the null hypothesis that the before and after separation particle

size distributions were the same, against the alternative hypothesis that the after separation would be shifted to

smaller values. A Student’s t-test yielded a P-value< 0.0475, and a Kolmogorov Smirnov test resulted in a P-

value of 0.0498. This supports the rejection of the null hypothesis in favor of the alternative that exosome particle

size distributions after separation are enriched in smaller urine derived exosomes compared to the before

separation samples.

7. Particle Volume Fraction

Supplementary Table 2. Volume fractions of fluorescence polystyrene beads.

For all devices, the pillar height was 400 nm except for G = 42 nm, in which case it was 200 nm.

Nominal

Particle Size,

DP

(nm)

Experimental

Concentration

(particles·mL-1

)

Volume

Fraction

(%)

Particles per Array Unit Cell

nanoDLD Gap Size, G (nm)

235 214 134 118 42

110 1·1011

0.0070 5.5·10-3

- - - -

50 1·1012

0.0065 5.5·10-2

5.3·10-2

4.2·10-2

3.9·10-2

-

20 4·1013

0.017 - 2.1 1.7 1.6 0.47





8. Estimation of Particle Induced Distortion of Flow

In cases when the particle concentration is high (particle-laden flows), it is clear that the effects of other

particles on a single particle can change that particle trajectory. But this can happen even in very dilute

particle suspensions. Indeed, even the presence of a single finite size particle modifies the boundary

condition of the fluid system, which now has to verify the non-slip boundary condition at the surface of

the particle.

The motion of a particle in a fluid flow is described by the Maxey-Riley equation:

Where mp and mf denote the mass of the particle and the mass of the liquid displaced by the particle

respectively, a is the radius of the particle (assumed to be a sphere), and µ and � are the dynamic and

kinematic viscosities, respectively. gi denotes the ith

component of the gravitational acceleration vector

and ui denotes the jth

component of the undisturbed velocity field which is a function of position and time.

The vector Y(t) denotes the spatial coordinates of the particle center of mass at time t. Wi is the ith

component of the difference between the particle center-of-mass velocity vi, and the undisturbed velocity

field (i.e., the velocity field without a particle) such that Wi = vi(t) – ui(Y(t), t). The term

��

��

is shorthand

for the time derivative of a fluid element:

��

��= �

��

��+ �

�

��

��

��

We will call U0 the typical unperturbed fluid velocity scale. Likewise, W0 is taken to be a representative

velocity scale for Wi. L will denote the characteristic length scale in the unperturbed flow. The equation

above is an approximation valid when the particle Reynolds number Rp=aW0/� and the shear Reynolds

number Rs=Re a

2

/L2

are small, where Re= LU0/� is the unperturbed flow Reynolds number.

L1 L2

R1 R2 R3 R4 R5 R6

L3





In our experiments U0 is 2·10-4

m/sec (we’ll take the later as an upper bound when we calculate the

Reynolds numbers), and L is half the gap size. We will take U0 to be an upper bound for W0. The

diameter of the particle ranges from 20 nm to 100nm, and in what follows we will take L = 2.4·10-8

m

and a = 1·10-8

m (notice that this is the smallest particle radius and gap size tested).

Using the numbers described above, and the kinematic viscosity of water to be 10-6

m2

·s-1

we have that

for our system:

��=

��

�

<

��

�

=2.0·10-6

�� =

��

�

= 4.8·10-6

��= ��

�

��

= 0.8·10-6

Therefore, the conditions that Rp<<1 and Rs<<1 are verified and we can proceed with the Maxey-Riley

formulation.

We will assume that the density of the particles is the same as the density of the solvent (nearly true for

polystyrene particles and exosomes). Dividing the Maxey Riley equation by 6πaµU0 we can estimate

the relative order of importance of each term. We get from each of the terms of the equation:

�1~ ��

�

��

��

�2~ ��

�

��

� ��

��

�3~�

�

��

�1~ ��

�

�2~ ��

�

�3~0

�4~ ��

��

��

�5~ ��

��

�

��

�6~ ��

��

�

��

� ��

��





It can be observed that except for the term resulting from Faxén’s correction (R4), all the other terms

are a function of the shear Reynolds number, and smaller than 3·10-3

(That is, were it not for Faxén’s

correction, which accounts for the curvature of the flow field, the velocity of the particle would differ from

the velocity of the fluid by < 0.3%). As expected, Faxén’s correction would become less important as

the size of the particle decreases for a fixed gap size. Neglecting the smaller terms, the simplified

Maxely-Riley form is given by:

��

=

��

��

~

1

6

��

��

Where ∆v is the difference in the fluid velocities between the particle laden and undistributed flows, Dp

is the particle diameter, and G is the gap size of the pillar array. As the scaling factor

��

�

approaches 0.5

(close to the empirically observed threshold for bumping), ∆v ~ 4% of the undisturbed velocity. This

suggests the particle induced disturbance of the local fluid flow is small, and that the effect of this

perturbation on the nanoDLD operation is minimal.

We recognized that the simplicity of a dimensional analysis argument, while allowing an estimate of the

magnitude of the particles’ effect on the fluid flow, does not take into account the full complexity of the

nanoDLD system. The fluid passing through the pillar gaps leads to regions of compact streamlines, in

which small disturbances of the flow may have greater impact on determining the partitioning of particles

between the bump and zigzag mode. In addition, small disturbances in the flow may be amplified by the

fact that a single particle encounters thousands of pillar gaps in its trajectory across the device, and

therefore the small effects may become cumulatively larger.

Some effects are neglected in the Maxey-Riley formulation. The sphere is assumed to be far from the

walls, and therefore particle-boundary interactions are excluded. The effect of this interaction is an

added drag and lift force, as well as the potential for lateral displacement of fluid. The Stokes drag, taken

in the formula above to be the one corresponding to a uniform flow far from boundaries, should be

modified to take into account the additional drag created by such boundaries.5

This can be considered

to be an increase in the viscosity and therefore would result in a still smaller Reynolds numbers which

does not modify our basic conclusion. The lift force, perpendicular to the local flow direction, can be

estimated to have an effect smaller than the shear Reynolds number and therefore it is of the same

order of the corrections discussed lines above.6

Particle-induced lateral transport comes from an

asymmetry in the flow around the particle which leads to a net displacement of fluid to the side of the

particle as it traverses along a boundary.7

The effect scales with a3

as well as the particle Reynolds





number, and thus is expected to be negligibly small in the current nanoDLD system.

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deterministic lateral displacement. Science (80-. ). 304, 987–990 (2004).

3. Inglis, D. W., Davis, J. A., Austin, R. H. & Sturm, J. C. Critical particle size for fractionation by

deterministic lateral displacement. Lab Chip 6, 655–658 (2006).

4. Heller, M. & Bruus, H. A theoretical analysis of the resolution due to diffusion and size

dispersion of particles in deterministic lateral displacement devices. J. Micromechanics

Microengineering 18, 075030 (2008).

5. Leach, J. et al. Comparison of Faxén’s correction for a microsphere translating or rotating near

a surface. Phys. Rev. E 79, 026301 (2009).

6. Liu, C., Xue, C., Sun, J. & Hu, G. A generalized formula for inertial lift on a sphere in

microchannels. Lab Chip 16, 884–892 (2016).

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