Manipulation of single cells via a Stereo Acoustic Streaming Tunnel (SteAST)

Abstract

At the single-cell level, cellular parameters, gene expression and cellular function are assayed on an individual but not population-average basis. Essential to observing and analyzing the heterogeneity and behavior of these cells/clusters is the ability to prepare and manipulate individuals. Here, we demonstrate a versatile microsystem, a stereo acoustic streaming tunnel, which is triggered by ultrahigh-frequency bulk acoustic waves and highly confined by a microchannel. We thoroughly analyze the generation and features of stereo acoustic streaming to develop a virtual tunnel for observation, pretreatment and analysis of cells for different single-cell applications. 3D reconstruction, dissociation of clusters, selective trapping/release, in situ analysis and pairing of single cells with barcode gel beads were demonstrated. To further verify the reliability and robustness of this technology in complex biosamples, the separation of circulating tumor cells from undiluted blood based on properties of both physics and immunity was achieved. With the rich selection of handling modes, the platform has the potential to be a full-process microsystem, from pretreatment to analysis, and used in numerous fields, such as in vitro diagnosis, high-throughput single-cell sequencing and drug development.

Full text

Yang et al. Microsystems & Nanoengineering (2022) 8:88 Microsystems & Nanoengineering
https://doi.org/10.1038/s41378-022-00424-9 www.nature.com/micronano
ARTICLE Open Access
Manipulation of single cells via a Stereo Acoustic
Streaming Tunnel (SteAST)
Yang Yang
1
,WeiPang
1
, Hongxiang Zhang
1
,WeiweiCui
1
,KeJin
1
, Chongling Sun
1
,YanyanWang
1
,LinZhang
2
,
Xiubao Ren
2
and Xuexin Duan
1
✉
Abstract
At the single-cell level, cellular parameters, gene expression and cellular function are assayed on an individual but not
population-average basis. Essential to observing and analyzing the heterogeneity and behavior of these cells/clusters
is the ability to prepare and manipulate individuals. Here, we demonstrate a versatile microsystem, a stereo acoustic
streaming tunnel, which is triggered by ultrahigh-frequency bulk acoustic waves and highly confined by a
microchannel. We thoroughly analyze the generation and features of stereo acoustic streaming to develop a virtual
tunnel for observation, pretreatment and analysis of cells for different single-cell applications. 3D reconstruction,
dissociation of clusters, selective trapping/release, in situ analysis and pairing of single cells with barcode gel beads
were demonstrated. To further verify the reliability and robustness of this technology in complex biosamples, the
separation of circulating tumor cells from undiluted blood based on properties of both physics and immunity was
achieved. With the rich selection of handling modes, the platform has the potential to be a full-process microsystem,
from pretreatment to analysis, and used in numerous fields, such as in vitro diagnosis, high-throughput single-cell
sequencing and drug development.
Introduction
Research in single cells is a rapidly growing field where
heterogeneous cellular characteristics, such as morphol-
ogy
1
, adhesion
2
, mobility
3
, protein expression
4
and gene
expression
5
, are assessed on the basis of individual cells.
The fundamental advantage of single-cell analysis meth-
ods over bulk assays is that retaining single-cell infor-
mation can reveal rare cell properties and biologically
meaningful heterogeneity between individual cells. The
preparation and manipulation of individual cells, includ-
ing dissociation
6
, trapping
7,8
, rotation
9,10
, staining
11
,
release
12
, and pairing
13
, are essential capacities in bio-
technology that are fundamental for various purposes,
such as single-cell analysis
3,4,9,14
, drug development
15
,
organ-on-chip systems
16
and cell–cell interaction
studies
13
.
Microfluidics-based methods are a highly effective
strategy to achieve single-cell-level manipulations, where
the dimensions of force gradients and physical features
are on the same scale as individual cells. When dealing
with complex biological samples, such as blood
17,18
,
sputum
19
and stool
20
, a micro total analysis system (μ-
TAS), which can be integrated with multifunctional
modules, has shown excellent compatibility and perfor-
mance. Affinity capture is a commonly used strategy
based on affinity ligands, such as antibodies and aptamers,
modified on microstructures
12
. Although this method has
demonstrated excellent performance in capture efficiency
and specificity, it is inferior to the physical characteristics-
based methods in terms of versatility and flexibility. Sev-
eral techniques, divided into passive and active strategies,
have been established. Hydrodynamic methods passively
guide individual cells in continuous flow to design
microstructures that achieve single-cell trapping
13,21–25
.
© The Author(s) 2022
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, whi ch permits use, sharing, adaptation, distribution and reproduction
in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a linktotheCreativeCommons license, and indicate if
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Correspondence: Xuexin Duan (xduan@tju.edu.cn)
1
State Key Laboratory of Precision Measuring Technology and Instruments,
Tianjin University, Tianjin 300072, China
2
Tianjin Medical University Cancer Institute & Hospital, Tianjin Medical
University, Tianjin 300072, China
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1234567890():,;

Regarding active methods, a number of techniques have
been used, including dielectrophoresis
26
, optical twee-
zers
27,28
, magnetic tweezers
14,29–31
, and acoustophor-
esis
32–39
. Among these technologies, acoustic-based
strategies have received considerable attention due to
their biocompatibility, flexibility and low cost
40–44
.
Recently, a new method based on acoustic streaming,
which realizes the handling of particles by weakening the
effect of acoustic waves and amplifying the effect of
acoustic streaming, has been established for motion
45,46
,
enrichment
47
, selective trapping
48–52
, and rotation of
microscale specimens
9,46
. Compared with conventional
acoustophoresis-based strategies, acoustic streaming
provides more dynamic conditions, which significantly
improves the ability to manipulate and analyze sam-
ples
41,47,53
. Although many breakthroughs in the obser-
vation, spatial movement and interaction of single cells
have been achieved, there are still barriers between the
current handling modes and complex requirements in
single-cell research, for example, three-dimensional (3D)
observation without fluorescent labels and dissociation of
doublets. In addition, integrating these handling modes
(rotation, dissociation, separation, and analysis) on one
chip is still a challenge, especially when specific operations
often require multiple valves and pumps to control the
transportation of fluids or substances.
In this study, we utilized an ultrahigh-frequency bulk
acoustic wave device (UHF BAW device) to create 3D
acoustic streaming, called stereo acoustic streaming
(SteAS), which is highly confined by a microchannel to
form a virtual tunnel distributed along the boundary of
the device. “Stereo”is the core feature of our technology
that differentiates it from the classic acoustic streaming-
based acoustofluidic technologies
49,54,55
, which means the
acoustic streaming in our device is three-dimensionally
distributed in the microfluidics and the particles/cells are
trapped into a fixed trapping point (0-dimension) with full
spatial confinement. Cells in the stereo acoustic streaming
tunnel (SteAST) were arranged and migrated along the
tunnel with a spiral trajectory, as shown in Fig. 1a. In
previous studies, although SteAS has been developed for
particle enrichment, the potential for handling biological
a
UHF device
CTC selective trapping
Cluster dissociationReconstruction Pairing
Trapping
point
In-situ analysis
Single cell
Barcode bead
Observation Handling Analysis
Red blood cellTarget cell Acoustic vortices
b
Single cell
SteAST
10
0
-10
10
0
-10 60
40
20
Fig. 1 Schematics and multimode manipulation of the SteAST platform. a A schematic of the SteAST platform. The SteAST platform comprises a
microfluidic channel bonded to a UHF BAW resonator on a silicon substrate. The attenuation of BAWs in a coupled liquid triggers 3D acoustic
streaming vortices. The detailed images show a cartoon profile of SteAST and the stacked image that demonstrates the trajectory of a fluorescent
particle (5 μm) in the tunnel to describe the actual profile of SteAST. bSteAST-based multimode manipulation of single cells. The reconstruction of
the cluster was achieved via rotation manipulation, demonstrating successful 3D observation. As a demonstration of the pretreatment of biological
samples, this platform provides size-based selective trapping of a single cell and shear force-based dissociation of clusters. To show successful
analysis, in situ analysis of single cells by staining and pairing a target cell with a barcode gel bead for downstream analysis was demonstrated with
the cooperation of the customized microfluidic channel. White arrows show the direction of lateral flow. The blue dotted line and blue arc arrows
show the axis and direction of rotation, respectively. The red arrows point to the individual cells after dissociation. The scale bar is 100 µm.
Yang et al. Microsystems & Nanoengineering (2022) 8:88 Page 2 of 18

specimens and the complexity of the spatial distribution
of acoustic streaming vortices have not been exploited. By
understanding the relevant forces and optimizing the
boundary conditions, a virtual tunnel whose diameter
matched the size of single cells was generated. The
migration of cells in the tunnel is the result of the com-
bined and competing effects of lateral flow, acoustic
streaming, and acoustic waves and interactions. Multiple
effects were utilized to realize the multimode manipula-
tion of individual cells in one chip, including rotation,
dissociation, selective trapping, controllable release and
particle pairing. Based on these modes, a variety of
paradigms from observation to analysis were achieved, as
shown in Fig. 1b. Moreover, to demonstrate the system’s
application in clinical and biological research, we pro-
posed a strategy to separate and in situ analyze circulating
tumor cells (CTCs), a kind of rare cell in cancer patient
blood, from patients’undiluted blood through the inte-
gration of these operations. To the best of our knowledge,
there is no existing microfluidic device that has estab-
lished the capacity to achieve such complex and precise
manipulation of single cells. We believe that the SteAST
platform, which provides a brand-new method for the
multimode manipulation of single cells, will benefit var-
ious biomedical and biological applications.
Results
Working principle and design of the SteAST system
To fulfill the requirements of single-cell manipulations,
the SteAST system was designed by integrating a UHF
BAW device into a microfluidic channel. The geometry of
the channel and the shape, position and alignment of the
device in the microchannel were optimized to create a
tunable 3D AST, which is discussed thoroughly in this
section (Fig. 2) and functions as a dynamic single-cell-
sized potential well (Fig. 1a). This is the core design to
achieve size-selective and tunable cell trapping. Cell
trapping was achieved due to the balance between the
strength of SteAS and lateral flow, which can be con-
trolled by tuning the power applied to the BAW device
and the lateral flow rate. This results in a dynamic cell
manipulation system, where cell trapping, solution
exchange, on-site cell analysis, and cell release can be well
controlled under continuous flow conditions without the
use of extra valves. In addition, this platform could pro-
vide a stable and adjustable shear force to dynamically
trap cells by optimizing the spatial position of the tunnel
and lateral flow parameters. As a proof of concept,
manipulations including cell rotation, cluster dissociation,
cell reconstruction, and cell-particle assembly were
demonstrated with the SteAST system (Fig. 1b).
First, we discuss the details of the working and design
principles of the SteAST system. The optical image, SEM
image and cartoon section view of the GHz BAW device
are shown in Supplementary Fig. S1a–c. The device is a
typical thin film piezoelectric resonator that contains a
Bragg mirror structure, a bottom electrode, a piezoelectric
layer and a top electrode. The resonant frequency of the
device is shown in Supplementary Fig. S1d. The
mechanical displacements result in a standing acoustic
field in the body of the piezoelectric layer by applying
resonant frequency signals across the piezoelectric layer
(Supplementary Fig. S1e). As the BAW device is placed in
direct contact with the liquid, efficient acoustic energy
coupling from the piezoelectric layer to the surrounding
liquid is guaranteed. The simulation results of the dis-
tribution of the acoustic waves at 2 GHz and 200 MHz are
shown in Supplementary Fig. S2a. The difference in the
distribution and decay length of the acoustic waves at
these two frequencies can be clearly observed. The non-
linear attenuation of oscillating displacements in dis-
persive media results in a body force (F
B
) at the z-axis,
which pushes the liquid in the direction of acoustic wave
propagation and then generates a stable liquid flow
(acoustic streaming)
56
. Since F
B
∝ω
4
(ωis the angular
frequency), the strength of F
B
generated by UHF BAWs is
much stronger, which is due to the enhanced local energy
density
57–59
. In addition, the rather small footprint of the
UHF device (dozens to millions of square microns) results
in a more focused acoustic wave beam
60
.Asβ
−1
∝1/ω
2
(β
is the attenuation coefficient and β
−1
is the attenuation
length in liquid media), the decay length of the acoustic
wave is actually less than 20 μm. Thus, there are almost
no standing acoustic waves in the SteAST system.
Due to the particularity of the thickness extension (TE)
vibration mode and high resonance frequency, the fluid
jets rise from the top of the device and impinge on the top
interface of the microchannel; they recirculate vigorously
in a clockwise or counterclockwise direction to form
hourglass-shaped stereo acoustic streaming vortices,
which behave like microscale fountains. As the micro-
vortices are connected, a series of closed microvortices
form a virtual tunnel, whose contour profile is defined by
the shape of the resonator (Figs. 1a, 2a and S2b). Such a
virtual tunnel is the basic component of the SteAST
system. We used finite element simulation software
(COMSOL) to discuss the influence of different boundary
conditions to optimize the SteAST platform. First, we
considered the particles in the system without lateral flow.
As shown in Fig. 2a, they experienced an acoustic radia-
tion force (F
rad
) and a Stokes drag force (F
drag
), which are
induced by 3D acoustic streaming vortices. A 2D simpli-
fied model was used here based on the symmetry of the
acoustic streaming pattern. The acoustic field was dis-
tributed above the device, and the microvortices levitated
around the boundary of the device. The acoustic radiation
force pushed the particles above the device away along the
z-axis, while the drag force drove the particles to move
Yang et al. Microsystems & Nanoengineering (2022) 8:88 Page 3 of 18

along the vortex streamline. Ideally, under the combined
forces, the particles will be translated along a spatial tra-
jectory and trapped in the low-velocity area, which is the
equilibrium position at the center of the vortex.
Tuning the inside conduit diameter of the tunnel to fit
the size of a single cell is the 1st design principle of the
SteAST platform. This can be achieved by adjusting the
boundary conditions of the acoustic streaming. An
acoustic radiation force is triggered by the scattering of
acoustic waves from the BAW device. In the case where
the particle is smaller than the characteristic length scale
of a nonuniform acoustic field, the time-averaged
50
0
50
0
50
0
Pm
0.08 m/s
0.12 m/s
0.04 m/s x
z
m/s
Upstream vortex Downstream vortex
0.00 0.05 0.10 0.15
0
10
20
30
40
50
Z-Axis (
P
m)
Lateral flow (m/s)
Vortex center
Vortex boundary
50
Pm
25
0
50
25
0
ab
cd
e
f
x
z
300
0
150
0 150 300
50
0
500
Pm
100 Pm
x
y
z
x
y
z
m/s m/s
Trapping
point
Trapping
point
m/s
01020304050
0.00
0.05
0.10
0.15
0.20
0.25
Velocity (m/s)
Z-Axis (
P
m)
Velocity
-1.5 ×
×
10
6
-1.0
×
10
6
-5.0
×
10
5
0.0
5.0
×
10
5
1.0
×
10
6
1.5
×
10
6
Pressure
Pressure (Pa)
D1 = 36° D2 = 18°
AST
Frad
RAST
Fdrag
Pa m/s
×106
1.5
1
0.5
0
-0.5
-1
-1.5
0.2
0.15
0.1
0.05
0
0.2
0.15
0.1
0.05
0
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
0
×10-3
30
25
20
15
10
5
0
×10-4
10
9
8
7
6
5
4
3
2
1
0
α1α2
Fig. 2 (See legend on next page.)
Yang et al. Microsystems & Nanoengineering (2022) 8:88 Page 4 of 18

radiation force exerted on a spherical specimen can be
expressed as
61,62
Frad ¼∇U
U¼4π
3r3f1
κl
2p2
in

f2
3ρl
4v2
in

hi
f1¼1κp
κl
f2¼
2ρp
ρl
1

2ρp
ρl
þ1
where Uis the force potential field, which is determined
by the particle parameters and characteristics of the fluid;
ris the particle radius; f
1
and f
2
represent the monopole
and dipole scattering coefficients, respectively, which
relate to the bulk and directional vibration in an
oscillating field; κ
p
and κ
l
are the compressibilities of the
particle and liquid, respectively; ρ
p
and ρ
l
are the densities
of the particle and liquid, respectively. The equation
indicates that the radiation force on the particle is
determined by the spatial gradient of the force potential
field, which is proportional to r
3
. Thus, the acoustic
radiation force is strongly dependent on the distance from
the surface of the BAW device and the radius of the
particle. The Stokes drag force induced by acoustic
streaming can be estimated as
Fdrag ¼6πμrv
where μis the dynamic viscosity of the medium and vis
the nonoscillatory velocity of the particle relative to the
liquid.
Although the relevant factors of the force are clear,
quantitative calculations of the radiation force applied to
the trapped particles are rather difficult since it is highly
related to the spatial position of the particle. Here, we
qualitatively discuss the influence of the boundary con-
ditions and the force status of the trapped particles by
simulation. Once the device was fixed, the strength and
distribution of the acoustic streaming were mainly
determined by the geometry of the microchannel
59,63,64
.
We then calculated the distribution of the acoustic field in
2D models under different geometric confinements, as
shown in Supplementary Fig. S3. Since the width of the
microchannel is often larger than its height, the model
was simplified as being confined at the top. Supplemen-
tary Fig. S4 shows the acoustic pressure at the center and
velocity of the acoustic streaming on the boundary of the
UHF device confined by different heights. When the
height of the flow channel is larger than 25 μm, the dis-
tribution of acoustic waves is dominated by the attenua-
tion effect and is no longer related to the height of the
flow channel (reflection effect). Correspondingly, when
the height is less than 25 μm, the velocity of the acoustic
streaming decreases, which indicates that the acoustic
energy cannot be completely converted into fluid kinetic
energy. Therefore, to obtain the ideal intensity of acoustic
streaming while avoiding the negative effects of the
standing waves, the height of the microchannel should be
higher than 25 μm. In addition, when the height is higher
than 100 μm, the acoustic waves cannot reach the center
of the vortex, which is the point of minimum velocity (at
approximately one-third in the z-axis; shown in Supple-
mentary Figs. S3 and S4). Therefore, the radiation force is
not strong enough to push the particles into the vortex
center, which manifests as the expansion of the inside
conduit diameter of AST. Therefore, a microchannel with
a height of 50 μm was chosen as an ideal boundary con-
dition for generating the right AST targeting for single-
cell manipulations. In this case, the acoustic waves can
cover the center of the acoustic streaming vortex and
create a single-cell-sized potential well at one-third of the
height of the microchannel (Fig. 2b). The center of the
SteAST is the center of the acoustic streaming vortex
marked by the blue line, and the boundary of the SteAST
is determined by the position where the F
rad
cannot
(see figure on previous page)
Fig. 2 Design of the SteAST platform. a Simulation results of the distribution of the acoustic field (1.8 GHz) and acoustic streaming in the
microchannel. The acoustic radiation force and drag force on particles are highlighted by red and blue arrows, respectively, in the SteAS platform. The
length of the arrow represents the magnitude of force. The position of the UHF BAW device is represented by yellow rectangles. bDistribution of
the acoustic field and velocity of acoustic streaming along the height in a 50 μm high microchannel. R
AST
is the inside conduit radius of the AST. cThe
distribution of the flow field in the microchannel under lateral flow at different velocities (0.04, 0.08, and 0.12 m/s). The white arrow points in the
direction of lateral flow. The position of the device is shown by yellow rectangles. The upstream and downstream vortices are highlighted by green
and black arrows, respectively. The center and boundary of the downstream vortex are represented by black points and red dotted cycles,
respectively. dThe height of the center and boundary of the acoustic streaming vortex at the downstream boundary of the device with lateral flow
at different velocities. eThe 3D simulation result of the SteAST field generated by the pentagonal UHF device under the restriction of the
microchannel. The color bar on the left corresponds to the velocity in the x-y plane, and the color bar on the right corresponds to the x-z and y-z
planes. The height of the image in the x-y plane is 17 μm, which is approximately one-third the height of the microchannel (50 μm). The AST is
highlighted by cylinders and cycles in the top and side views, respectively, as indicated by the cyan arrows. The center and wall of the AST are the
low-velocity and high-velocity zones in SteAS, respectively. fThe trajectories and velocity spectrum of particles trapped by SteAS under different
angles between the UHF device and lateral flow, which is defined by α. When αis 36°, the trapping point is biased toward the vertex near the
downstream, and when it is 18°, the trapping point is at the center of the tunnel.
Yang et al. Microsystems & Nanoengineering (2022) 8:88 Page 5 of 18

further drive particles away from the device. Since F
rad
is
related to the particle size, acoustic properties and sound
pressure, it is difficult to give an accurate boundary; here,
we define the boundary as the position where the sound
pressure decays rapidly, which is marked by a red line. In
the actual experiment, the applied power can be adjusted
to precisely tune the boundary. Again, tuning the geo-
metric confinement of the microchannel to achieve the
right conduit diameter of AST is the 1
st
design principle
of the SteAST system for accurate and stable manipula-
tion of single cells.
Then, we consider the lateral flow effect. From an
energy point of view, the particles trapped in the AST are
affected by the kinetic energy of the lateral flow. When the
kinetic energy exerted on the particles is higher than the
energy barrier of the potential well induced by acoustic
waves and vortices, the particles will leave the tunnel and
move downstream along with the lateral flow. Notably,
the trapping stability can be dynamically tuned on
demand by changing the power applied to the device and
the flow rate, thus enabling a versatile cell manipulation
tool, where trapping, reaction, incubation and analysis of
the cells can be achieved on the same chip under con-
tinuous flow conditions. The balance between trapping
and releasing represents the 2nd design principle.
Next, we discuss the details of the fluid interactions
between the lateral flow and acoustic streaming based on
a 2D model. Due to the particularity of the TE mode of
the BAW device, the jetting flow and lateral flow form an
orthogonal relationship in a highly confined environment
(Fig. 1a); thus, the symmetric fountain-like acoustic
streaming vortices could be affected by the lateral flow
according to their spatial position with the flow direction.
As shown in Fig. 2c and Supplementary Fig. S5, due to the
interactions with the lateral flow, the upstream vortex will
be lifted while the downstream vortex will be pressed
down; thus, asymmetric acoustic streaming vortices result
in the x-z plane. To further analyze the effects of asym-
metric vortices on particle trapping, we calculated the
velocities of the upstream and downstream vortices. As
shown in Supplementary Fig. S6a, by fixing the power
applied to the device, the upstream vortex moves away
from the device center and continues to weaken until it
disappears as the lateral flow rate is increased. This
indicates that cells are more difficult to capture at a high
lateral flow rate since the trapping point (center of the
acoustic streaming vortex) moves away from the acoustic
radiation force area. For the downstream vortex, the
velocity of the reflux fluid below the equilibrium position
is slightly suppressed as the lateral flow rate increases,
while the flow velocity above the flow channel increases
rapidly (Supplementary Fig. S6b). The flow above the
equilibrium position has both a vortex part that transports
particles back to the acoustic radiation force region and a
lateral flow part that takes the particles downstream. To
decouple the two parts, we extracted the height of the
vortex center and the upper boundary of the vortex at
different flow rates, which is displayed in Fig. 2d. The
boundary of the vortex is calculated based on the con-
servation of flux in the vortex section. This shows that as
the lateral flow velocity increases, the height of the vortex
center and the boundary both decrease, and the latter
decreases faster. This brings about two effects: one is that
the capture position approaches the device, which will
result in an increase in the acoustic radiation force by
pushing the particles out of the vortex center. The other
effect is the shrinking of the AST area and expansion of
the lateral flow area. The AST and lateral flow are actually
in a competitive relationship. Thus, the weakening of the
former corresponds to the enhancement of the latter,
which will reduce the trapping stability. Especially when
the particle size is larger than the size of the shrinking
AST, the particles will inevitably be directly affected by
the lateral flow, resulting in the failure of trapping.
From this part of the analysis, the trapping status of the
particles (trapping or releasing) can be controlled by
tuning the energy balance between the lateral flow and
acoustic streaming. Specifically, their interactions result in
an asymmetric vortex pattern, which will further affect the
performance (capture efficiency, trapping stability, etc.).
Taking into account the transport effect of lateral flow
and the stability of the vortex, the flow rate needs to be
optimized to ensure that all the particles will be deflected
by the upstream vortex, which is the prerequisite for
trapping in the downstream vortices.
After understanding the fluidic channel confinement
and lateral flow effects on particle trapping, we further
considered the arrangement of the AST and its effects on
particle behaviors, which gives the 3
rd
design principle of
the SteAST. The shape of the device determines the
profile of the AST. In this work, we take the best per-
formance (quality factor, resonant frequency) as the
priority principle of the device design; thus, a pentagonal
UHF device with an area of 20 k μm
2
was used in this
system
65,66
. Here, a 3D simulation model was applied to
deeply analyze the interactions between lateral flow and
the AST in 3D space. As shown in Fig. 2e, a pentagonal-
shaped AST was clearly observed, which exactly followed
the periphery of the device. Once the shape of the device
is fixed, the relative arrangement of the device with the
microchannel will affect the behavior of particles in the
AST, which in turn affects its trapping performance.
As discussed above, in a stable trapping process of
SteAST, all the particles were deflected by the upstream
vortices first and then passed through the AST before
reaching the end trapping position. To further analyze the
migration process of particles in the AST, the velocity
spectrum and trajectories were thoroughly analyzed
Yang et al. Microsystems & Nanoengineering (2022) 8:88 Page 6 of 18

(Fig. 2f). The particles were initially evenly distributed in
the microfluidic channel before meeting the front vortex.
From the top view, after contact with the front vortices
and being dragged by the lateral flow, the trajectories of
particles were only distributed on the boundary of the
UHF device, where the AST sits. In the end, they were
statically trapped at one point in the tunnel (the trapping
point), which is highlighted in Fig. 2f. From the side view,
it is noted that the particles were also focused in the z-axis
at the center of acoustic streaming vortices without con-
tact with the substrate. This analysis gives a clear picture
of the trapping process. Once in contact with the front
vortices, the particles entered the AST and moved
downstream under the action of the drag force induced by
lateral flow while being concentrated at the equilibrium
position. When the particles arrived at the boundary
downstream, regardless of the initial position of the par-
ticles, all the particles were concentrated in the center of
the tunnel, which provides a 3D focusing condition, as
shown in the detailed image in Fig. 2f and SI-Movie-1. It is
worth emphasizing that, unlike trapping through an
individual potential well, SteAST can decrease the velocity
of the particles through continuous hydrodynamic action
before entering the stable trapping point, which we call
the buffering effect. 3D focusing combined with the buf-
fering effect provides a unique and reliable dynamic
trapping strategy. Next, we discuss the influence of the
angle between the device and the lateral flow on the
particle trajectory. As shown in Fig. 2f and SI-Movie-2,
the final trapping position in the downstream boundary
actually moves with the angle between the flow direction
and device, which is defined by the angle α. The simula-
tion results show the trapping process with αvalues of 36
degrees and 18 degrees and the migration of trapping
points. Due to the poor continuity of the AST at the apex
of the device, the trapping point near the apex is unstable.
Based on this, when dealing with complex samples with
strong interactions between particles, we can tune the
relative angle to move the trapping point away from the
vertex to achieve better performance. This part will be
further discussed in the experimental part of the selective
cell trapping in undiluted blood.
Quasi-static trapping and 3D reconstruction of a cell
cluster
After establishing the design principles, we tested the
SteAST system for cell trapping. First, cell trapping
without lateral flow was tested. Unlike the capture based
on microstructures, the cells trapped by SteAS are not
stationary in the AST, but they rotate along the direction
of the vortex streamline on the axis of the equilibrium
position. This phenomenon is called quasi-static trapping.
According to the 1st design principle, we used a
microchannel with a height of 50 μm. To better
demonstrate the actual working state of the SteAST sys-
tem, confocal microscopy (Leica, Germany) and 5 μm
fluorescence polystyrene (PS) beads were used to char-
acterize the spatial location and size of the AST. When
power was applied, particles were observed to be stably
trapped and suspended in the microchannel, which was
approximately 15 μm above the device, as shown in Fig. 3a
and SI-Movie-3. The trapping positions exactly match the
equilibrium positions in the simulations (Fig. 2). After the
power was turned off, the particles moved up to 45 μm
due to the combined action of buoyancy and gravity, as
shown in Fig. 3b. To further observe the trajectory of a
particle and the extent of the equilibrium position, the x-
z-t mode of the confocal microscope was applied, where
the imaging speed reached 37 frames per second. A
composite stacked image (6 images, 27 ms apart) is shown
in Fig. 3c. The original images and the videos are shown in
Supplementary Fig. S7 and SI-Movie-4. The red point
indicates the center of the particle in each frame, the
green dotted circle represents the range of particle
motion, and the red arrows indicate the direction of the
particle motion. The result demonstrates that the particle
was faithfully trapped in the tunnel. It is noted that the
diameter of the equilibrium position is approximately
15 μm, which is at the same scale as a single cell. This
provides the key prerequisite for precise single-cell
manipulation. This also proves that SteAST-based cell
manipulation is a contactless process, which is essential
for the maintenance of cell viability and prevention of
contamination issues.
Next, the trapping of individual HeLa cells was
demonstrated. As mentioned before, the vortices induced
by the UHF BAW were connected to adjacent vortices
and assembled into an AST along the boundary of the
device. The results shown in Fig. 3d and SI-Movie-5
illustrate that the individual cells were trapped in the
equilibrium position and patterned as the shape of the
device, which means that SteAS creates a suspended
trapping tunnel where its conduit diameter is comparable
to the single cell size and profile is determined by the
shape of the device.
Interestingly, the trapped cells are rotated in the AST.
This is due to the shear effect of the acoustic streaming
vortices acting on the cell surface; a torque is generated,
which makes the spatial position of trapped cells sta-
tionary, but rotation occurs. Therefore, the axis of the cell
rotation is the axis of the tunnel, and the direction of
rotation is the direction of the vortices (Fig. 3e). Based on
this behavior, we then realized the 3D observation of cells
or clusters.
Spatial localization is a key determinant of cellular
behavior and an important parameter to understand
heterogeneity and cell–cell interactions in clusters, tissues
and organs. The most common method for obtaining
Yang et al. Microsystems & Nanoengineering (2022) 8:88 Page 7 of 18

spatial information is scanning confocal microscopy,
which realizes 3D reconstruction by rebuilding fluor-
escent image slices. Using out-of-plane rotational
manipulation to observe 3D spatial information is an
alternative method. Although single-cell-level rotational
manipulation has been reported for rotating C. ele-
gans
9,67
, rotational manipulation and reconstruction for
irregularly shaped cell clusters without fluorescent labels
has remained a significant challenge. To achieve recon-
struction, movement in the x-y plane should be sup-
pressed, the rotation axis must be fixed without waggling,
and the speed of rotation should be tunable and suffi-
ciently uniform. These requirements are well met by the
SteAST platform. A high-speed camera (Photron, Japan)
was used to capture the process and state of cells trapped
in the AST. A single cell and a dimer of HeLa cells were
utilized to evaluate the stability of the SteAS-based rota-
tional manipulation, as shown in Supplementary Fig. S8
and SI-Movie-6. The image sequences showed that the
cells were strictly confined in the AST without movement
and rotated at a uniform speed in a complete rotation
cycle. The speed of rotation can be adjusted by tuning the
applied power, and the relationship between them is
shown in Supplementary Fig. S9. Moreover, a cell tetra-
mer was also chosen as a demo of a cluster for 3D
reconstruction. The trapped cluster was suspended and
rotated in the out-of-plane direction, as shown in Fig. 3f.
Since the profile of the SteAST is patterned by the edge of
the UHF device, there are gray zones (silicon) and white
zones (gold) in the background of the image. To obtain a
better background image, we processed the original
image, and the images before and after processing are
shown in detail in Fig. 3e. The processes are demonstrated
in Supplementary Fig. S10. Similar to the strategy of
reconstruction based on layer-layer slice images in a
Cartesian coordinate system through positioning by
15 μ
μ
m
UHF device
Power ON
15
μ
m
a
c
50
μ
m
d2 s 13 s 19 s 28 s
100
μ
m
0 s
b
45 µm
Power OFF 50
μ
m
e
Image
processing
100
μ
m
μ
m
μ
m
f
0
40
30
y (μm)
z (μm)
z (μm)
x (μm)
x (μm)
x (μm)
y (m)
20
10
50
0
40
30
20
10
50
0
20
10
0
20 40 60 80 100 120 140 160 180
0 20 40 60 80 100 120 140 160 180 200 220
40
100
0
0 20 40 60 80 100 120 140 160 180
10
10
0
–10 60
40
20
0
–10
Fig. 3 Quasi-static trapping and 3D reconstruction of cells. a SteAS-based trapping of a single fluorescent PS particle (5 μm). When the power
was applied, particles are trapped and suspended in the microchannel. bWhen the power is turned off, the particles settle to the surface. cA
suspended particle is trapped and rotated in the AST under the combined effect of radiation force and drag force. The stacked image sequences (6
images, 27 ms apart) are captured at approximately 10 mW. The green dotted circle represents the range of trapping points. The red arrows show the
direction of particle rotation. The yellow dotted rectangle shows the position of the UHF device. dPattern of individual cells based on the AST. HeLa
cells stained with calcein-AM (green) are used to represent the size and profile of the trapping point. The white arrow represents the direction of
lateral flow, the red arrows show the trajectories of individual cells in SteAS, the white dotted pentagon is the position of the UHF device, and the
blue curved rectangles represent the profile of the AST. eA single cluster trapped in the AST. The cells are highlighted by pseudocolor (red). The
detailed images show the images before and after image processing. The rotation axis and direction are represented by a blue dotted line and a blue
arrow, respectively. fThe result of 3D reconstruction.
Yang et al. Microsystems & Nanoengineering (2022) 8:88 Page 8 of 18

height information, 3D reconstruction can be performed
in a polar coordinate system based on rotational slice
images through positioning by angle information. The
interval angle among image sequences was calculated by
dividing a period (2π) by the number of pictures in a
period to determine the relative position of each picture in
a polar coordinate system. The reconstructed graphics
can be obtained through coordinate transformation, as
shown in Fig. 3f. The image processing and 3D recon-
struction were achieved by MATLAB software (USA).
Dynamic cell trapping and quantum release
After achieving cell trapping with the SteAST system
under static conditions, we then demonstrated cell trap-
ping under lateral flow conditions. According to the 2
nd
design principle, the balance between the AST and lateral
flow will determine the cell trapping status, and the
transportation and shearing effects of lateral flow actually
provide more possibilities for cell manipulations in this
platform. The SteAS-based trapping of cells in continuous
flow is called dynamic trapping. Here, “dynamic”has two
meanings. The first is that selective trapping or con-
trollable release can be achieved through the dynamic
adjustment of lateral flow and acoustic streaming; the
second is that the specimens or reagents transported by
lateral flow can be dynamically controlled in time and
space to meet the complex requirements in different
applications. In this part, we first verified the buffering
effect during cell trapping by analyzing the trajectories of
the cells. Selective cell trapping and controlled release are
demonstrated, and the relationship between the number
of captured cells and the lateral flow effect is emphasized.
To analyze the process of cell trapping under lateral
flow conditions, individual HeLa cells were injected into
the microchannel as tracking particles, as shown in Fig. 4a
and SI-Movie-7. The stacked images demonstrated the
process of dynamic trapping of three individual cells in
different initial positions. The velocity spectrum of the
cells was calculated by the position and interval time of
the cell in the adjacent images. We divided the trapping
process into three phases that occur in regions (a)~(c). In
region (a), the cells move at a uniform speed in the lateral
flow. In region (b), the cell meets the front microvortex,
where their flow direction and velocity are changed dra-
matically. As the trapped cells are dragged into the AST,
they move along a fixed pathway (the boundary of the
UHF device) while being 3D focused in the channel. The
velocity of the cell is chaotic in region (b) due to the
randomness of the initial position of the cells; however,
after going through 3D focusing, they all enter the next
area at the same speed and trajectory. Here, we refer to
region (b) as the focusing zone. In region (c), the velocity
of the cell decreases gradually until it arrives at the
trapping point. Thus, region (c) is called the buffering
zone. At the trapping point, the cell is trapped in a fixed
position where the drag force and acoustic radiation force
balance each other. The experimental results are rather
consistent with the simulation, which proves the com-
plexity of dynamic trapping based on SteAST. Compared
with other 2D-based trapping, 3D focusing and buffering
effects make this platform more robust and widely
applicable.
Next, we discuss the size-selective cell trapping enabled
by the balance between the drag and radiation forces.
Based on the theoretical discussion, the trapped cells in
the AST were affected by both drag and radiation forces.
Due to F
rad
/F
drag
∝r
2
, larger specimens are displaced
more substantially than smaller specimens; thus, larger
specimens are trapped in the center of vortices, while
smaller specimens leave the AST under the action of
lateral flow, which is the theoretical basis of size-based
selective trapping. This theory was verified through both
simulations and experiments, as shown in Supplementary
Fig. S11 and SI-Movie-8. A 3D simulation model was built
to analyze the trajectories of particles with different sizes.
The red particles (15 μm) were trapped at the boundary of
the device, while blue particles (2 μm) escaped the trap.
The experimental results of selective trapping of PS par-
ticles (5 μm and 2 μm) are shown in Supplementary Fig.
S11c. We speculated that the resolution of separation in
the simulation was worse than that in the actual experi-
ment since their interactions were totally ignored in the
simulation model. In real situations, smaller particles have
fewer chances to enter the AST as larger particles enter
the trapping position much faster. In addition, since larger
particles could be more stably trapped, smaller particles in
the potential well would be easily squeezed out and
replaced by larger particles.
To further observe the dynamic selective trapping
process in the presence of cell interactions, HeLa cells
were spiked into diluted whole blood to represent a
complex biological sample. The trajectory of the trapped
HeLa cells was demonstrated in the composite stacked
image, and the velocity spectrum is shown in Fig. 4b. As
explained in the previous discussion, the cells underwent
the 3D focusing and deceleration process in the focusing
and buffering zones. Due to the smaller size of the red
blood cells, the radiation force was not strong enough to
confine them within the AST, and the hydrodynamic
force dominated, which resulted in their passing through
the device downstream without being trapped. Thus, the
SteAST system provides a versatile size-based cell
separation system by trapping larger cells while ignoring
smaller cells. The capture efficiency is the key parameter
for such a cell separation platform. The capture efficiency
results with different applied powers and lateral flow rates
are shown in Fig. 4c. The capture efficiency increased with
applied power and decreased with increasing lateral flow
Yang et al. Microsystems & Nanoengineering (2022) 8:88 Page 9 of 18

33.1mW
33.1mW
33.1mW 20.9mW 16.6mW 6.6mW 0.1mW
20.1mW 16.5mW 0.1mW
2 CTCs
4 CTCs
3 CTCs
13.2mW 0.1mW
b
cba
ab c
ab c
Trapping
point
Slow zone
Focusing
zone
Trapping
point
abc
0.0 0.5 1.0 1.5 2.0 2.5 3.0
0
100
200
300
400
500
600
700
800
900
Velocity (micron/s)
Time (s)
a
-20 0 20 40 60 80 100 120 140 160 180
0
20
40
60
80
100
0.5 uL/min
1 uL/min
2 uL/min
3 uL/min
Capture efficiency (%)
Power (mW)
-20 0 20 40 60 80 100 120 140 160 180
0
5
10
15
20
25
30
Number of trapped cells
Power (mW)
0.5 uL/min
1 uL/min
2 uL/min
3 uL/min
c
d
e
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4
0.0
5.0 ×
×
10
2
1.0 ×
×
10
3
1.5 ×
×
10
3
2.0 ×
×
10
3
2.5 ×
×
10
3
Velocity (um/s)
Time (s)
30mW
30mW
30mW
0mW
OFF ON
One
CTC Two
CTCs
Three
CTCs
Three CTCs
f-1 f-2 f-3 f-4 f-5 f-6
f
Fig. 4 (See legend on next page.)
Yang et al. Microsystems & Nanoengineering (2022) 8:88 Page 10 of 18

rate. The reason is that the increasing lateral flow triggers
a stronger shear force and decreases the stability of the
AST, while the increasing applied power generates
acoustic streaming vortices at a higher velocity and
impairs the lateral flow, which is explained in Fig. 2.To
create a stable trapping point with high resolution, the
applied power and lateral flow rate should be well
balanced. Our platform can maintain the capture effi-
ciency at a high level with a lateral flow rate from
0.5~3 µL/min. It should be noted that although high
power leads to high capture efficiency, it sacrifices the
purity of trapped cells because smaller cells will be mis-
takenly trapped as well. In addition, to ensure that the
cells in the lateral flow pass through the SteAS area, we
calculated the actuating range of acoustic streaming
under different power and flow rates, called the capture
range, as shown in Supplementary Fig. S12. One side of
the UHF device was parallel to the direction of lateral
flow, called the target side. The boundary of the fluor-
escent fluid (rhodamine B) overlapped with the target side
through the sheath flow, and the capture range was cal-
culated by measuring the length between the target side
and the boundary of the dye, which was transported by
acoustic streaming vortices. Then, the introduction of
focus by sheath flow strictly limited the sample flow
within the capture range to improve the efficiency.
Beyond trapping, release is a necessary step for down-
stream in-depth cell analysis. However, controlled release
is still a challenge due to the inherent problems of
separation strategies, such as surface adhesion or
microstructure-based capture
12
. Moreover, the retrieval
process is often random, as the local flow in the micro-
fluidic chip is difficult to precisely control and cell-to-
interface adhesion may occur randomly
68–71
. Controlled
cell release has been largely studied using active approa-
ches by applying changing magnetic
3
, dielectric
72
or
acoustofluidic fields
49
; however, all of the trapped cells are
released at the same time. The characteristics of tunable
noncontact trapping and the AST where only trapped
cells were arranged one by one at each section of the
tunnel make ‘quantum release’of multiple trapped cells
possible. First, we discussed the relationship between the
number of trapped cells and the applied power and flow
rate, as shown in Fig. 4d. The relevance of the capture
capacity is similar to that of the capture efficiency, which
increases as the power increases and decreases as the flow
rate increases. The images in Fig. 4d show that as the
power increases, SteAS dominated the movement of cells,
and the trapping point expanded from a specific point to
the entire AST, which is the direct reason for the increase
in capture capacity. Moreover, the capture capacity and
applied power at different flow rates show an excellent
linear correlation. Based on this, the release of multiple
cells was achieved digitally via tunable AST. When there
are multiple trapped cells in the AST, the force analysis of
cells at the trapping point is more complex than that of an
individual trapped cell due to the interaction between
cells. Under the action of lateral flow, the cells in the AST
have a tendency to move toward the trapping point, as
shown in Fig. 2f. Since the cells are arranged in the tunnel,
the thrust on the cell at the trapping point will increase as
the number of cells increases. When the thrust force is
dominant, the cell at the trapping point will be pushed out
of the tunnel and released downstream. The number of
trapped cells is determined by the balance between the
strength of the acoustic tunnel and the thrust effect. As
shown in Fig. 4e and SI-Movie-9, different numbers of
HeLa cells were trapped by SteAS at the beginning. Then,
the cells were released one by one by gradually reducing
the applied power. As a demonstration, we tried to con-
trollably release two, three and four cells at a time. Ideally,
by gradually reducing the power, the cell that enters the
SteAST first would be released first at the fixed release
point following a ‘first enter first release sequence’.
However, in the actual experiment, due to the large initial
power applied to prevent cell adhesion, the release
sequence was not controlled enough. The strong
streaming vortices caused the position exchange of cells
(see figure on previous page)
Fig. 4 Dynamic cell trapping and size-based separation. a The stacked images demonstrate the trapping process of the single cell in different
initial positions via SteAST. The graph shows the velocity spectrum of individual cells in the trapping process. The trapping process is divided into
three stages: the lateral flow zone (region (a)), focus zone (region (b)), and buffering zone (region (c)). The cells are finally captured at the trapping
point. bThe trajectory of trapped single HeLa cells in diluted blood. The stacked image is created by merging 41 frames. The graph shows the
velocity spectrum of trapped single HeLa cells. cCapture efficiency of HeLa cells stained with calcein-AM (Invitrogen, USA) at different applied
powers and flow rates. The fluorescence field was observed, the number of cells trapped by SteAST and the number of cells flowing through were
counted, and the capture efficiency was calculated based on the ratio of the two. dThe relationship among the number of trapped cells (capture
capacity), applied power and flow rate. The images show the expansion of the trapping position as the power increased. eDigital release of the
trapped cell. Multiple cells (2, 3, 4 HeLa cells dyed by calcein-AM) are trapped in SteAST, and the digital controllable release of the individual cells one
by one is achieved by gradually reducing the power to regulate the capturing capacity. fSelective trapping of HeLa cells (CTCs) in undiluted whole
blood. (f-1) Hydrodynamic focusing of a whole blood sample. (f-2) Blood cells release when the power is turned on. (f-3) ~ (f-5) Selective trapping of
individual CTCs. The stacked image sequences demonstrate the trajectories of trapped CTCs. (f-6) The merged image shows that the three CTCs were
stably trapped while the blood cells were released from SteAST. The ratio of double focusing fluid and cell fluid is 1:1:1. The total flow rate was 1 µL/
min. The scale bars are 100 μm.
Yang et al. Microsystems & Nanoengineering (2022) 8:88 Page 11 of 18

during the trapping and release process. However, there is
still an opportunity to control the sequence of release
through optimization of power regulation, cell pretreat-
ment and the shape of the device. Next, the combination
of selective trapping and controllable release was also
achieved as a proof of concept. With coordination of
lateral flow, HeLa cells were extracted from diluted blood
into a buffer and released through power regulation, as
shown in Supplementary Fig. S13.
Rare cell separation from undiluted blood by tuning the
device angle
Thus far, we have systematically used the 1st and 2nd
design principles to achieve size-based selective single-cell
trapping, separation, and release. To improve the stability
of separation in complex biological samples, we optimized
the SteAST platform based on the 3rd design principle.
Rare cells are low-abundance cells in a much larger
population of background cells, such as CTCs, circulating
fetal cells, and cells infected by a virus or parasite, which
are highly important for various applications, such as
liquid biopsy, prenatal diagnosis and identification of
infection
73,74
. Various microfluidic strategies based on
immune affinity
70
, microstructures
68
, hydrodynamics
71,75
,
viscoelasticity and external fields
76
have been attempted
to achieve the separation of rare cells. In the SteAST
system, the UHF BAW device is used to generate the AST,
which selectively traps larger cells. Due to the excellent
stability and biocompatibility for long-term trapping and
the limited volume of the tunnel, it is actually suitable for
rare cell separations. Here, we demonstrated rare cell
separation directly from whole blood samples using
SteAST. A major focus is on the effect of the relative
tunnel position and angles to the microchannel.
Calcein-AM-stained HeLa cells were spiked into undi-
luted blood to mimic CTCs in the peripheral blood of
cancer patients. CTCs are rare cells, with as few as one
cell per 10
9
blood cells in cancer patient blood, and have
received tremendous research interest as emerging bio-
markers for in vitro diagnosis
70
. Compared to diluted
blood samples, undiluted whole blood is a more challen-
ging sample. In view of the physical parameters, whole
blood is more viscous and turbid. In addition, the high
density of unwanted cells, especially red blood cells (10
9
/
mL), may cause intense interactions among cells that
change the trajectory of specimens and influence the
stability of cell trapping. In the case of SteAS used in
whole blood samples, the cells fall away from the vortices
at the apex of the device, called the release points, as
shown in Supplementary Fig. S14. The reason is that the
continuity of the AST is interrupted at release points,
which makes the cells more likely to separate. To decrease
the negative effects induced by the cell–cell interactions,
the relative angle between the UHF device and the
microchannel was optimized to divide the trapping point
and releasing points, as discussed in the 3
rd
design principle
in Fig. 2f. Using the previous structure, the release point was
close to the trapping point, which facilitated the release of
trapped cells, while the cell–cell interaction was violent.
However, if we rotated the UHF device into symmetry along
the lateral flow, then the trapping point was in the center of
the edge near the downstream. In this case, the overlap of
the trapping point and releasing point can be largely avoi-
ded. After this optimization, size-based separation of CTCs
from whole blood was achieved, as shown in Fig. 4fandSI-
Movie-10.ThestackedimagesshowedthatCTCswere
stably trapped in the trapping point, while the blood cells
were released at the release points as designed.
Cell manipulations by combining dynamic and quasi-static
trapping
Based on the above discussion, the SteAST platform has
two different working modes: quasi-static and dynamic. In
quasi-static mode, the particles are trapped, arranged and
rotated in a virtual tunnel under the action of torque
induced by hydrodynamic forces. In the dynamic mode,
lateral flow brings a tunable shearing effect and material
transport effect. Combined with the unique handling
characteristics, size-based selective cell trapping and
controlled release of individual cells were successfully
achieved in different samples. Next, we combined the
above two operation modes and further demonstrated the
online cell pretreatment, reaction and analysis.
Clusters are ubiquitous at the pretreatment step of
various biosamples, including cultured cells and clinical
samples, which often have a negative impact on manip-
ulation or diagnosis. In single-cell manipulation and
analysis platforms based on microfluidics, clusters are
often the cause of microchannel blockage and a high
multiplet rate. By the quasi-static mode of the single-cell-
sized tunnel, the trapped clusters can be squeezed and
dissociated in the tunnel, which provides a new strategy
for preparing high-quality single-cell samples. When
clusters entered the SteAST, because the cluster size was
larger than the tunnel, the part outside the tunnel was
sheared by acoustic streaming and squeezed by UHF
BAWs. Finally, under the combined action of the two
effects, the cell cluster was dissociated into individuals
and arranged in the tunnel. This process was recorded by
a high-speed camera and is shown in Fig. 5a. Compared to
dissociation under quasi-static conditions, dynamic dis-
sociation due to the expansion of the trapping point under
the action of lateral flow makes the process slightly dif-
ferent. Under the action of lateral flow, the acoustic
streaming vortices are compressed, while the acoustic
wave area remains unchanged, which makes the equili-
brium position of the particles change from a fixed point
to a ring. This is the reason why the capture state of the
Yang et al. Microsystems & Nanoengineering (2022) 8:88 Page 12 of 18

particles changes from rotation to revolution. Even so,
dynamic dissociation at the single-cell level is still
achieved. Clusters of HeLa cells stained with calcein-AM
were used to demonstrate this process. When a cluster
was trapped in the SteAST, it was continuously dis-
sociated into individual cells, as shown in Fig. 5b and SI-
Movie-11. Compared with enzyme-based dissociation, the
mechanical force-based method is more convenient and
reliable without the need for centrifuge-based extraction
and strict control of processing time. Compared with the
filter-based pretreatment solution, SteAST provides an
automatable technology that is suitable for processing
samples in a small volume and integration with com-
mercial analysis platforms, such as flow cytometry and
high-throughput single-cell sequencing platforms.
Compared with cell trapping, online analysis of trapped
cells is rather important since it can provide rich cellular
information. The combination of precise control of the
delivered materials in the dimension of time and space
and contactless, label-free dynamic trapping brought by
microfluidics and SteAST enables efficient online cell
analysis. Herein, we introduce two different single-cell
analysis modes: dye-based in situ single-cell analysis and
sample preparation compatible with downstream com-
mercial single-cell sequencing technologies.
Multiphase flow driven by syringe pumps was intro-
duced into the system to achieve staining-based analysis
of trapped cells. Herein, trypan blue (a vital stain used to
selectively tag dead tissues or cells) was used as a probe to
evaluate the viability of trapped cells, as shown in Sup-
plementary Fig. S15. HeLa cells were trapped stably, and
the cell membrane still had permanent selectivity after
560 s. The extraction processes were repeated three times
to demonstrate the multistep analysis: Trypan blue buffer
0 ms 3.75 ms 7.5 ms 11.25 ms9.375 ms
50 µm
Single cell Single cell
Gel bead
Gel bead
HeLa
cell
Single gel bead &
HeLa assembly
Trapping Pairing Release
d
b
c
b-1 b-2
10 min 20 min 30 min0 min 1 min 5 min
a
Fig. 5 Dissociation and analysis of single cells. a Dissociation and arrangement of a cluster based on AST (blue zone). The cluster is dissociated
into a single cell and aligned under the action of SteAS. The cells are highlighted by pseudocolor (red). The applied power is 66 mW, and the scale
bar is 50 μm. bDissociation of the cluster in continuous flow. (b-1) The HeLa cell cluster (dotted cycle) is attracted to the AST. (b-2) The trapped
cluster is dissociated into individual cells (indicated by red arrows). The flow rate was 2 μL/min, and the applied power was approximately 15 mW. cIn
situ analysis of a single cell via SteAS. By switching between different lateral flow materials (HeLa cells and reagents), fluorescence-based analysis of
trapped single cells is realized. dPairing of a single cell and a barcode gel bead via AST. By switching between different lateral flow specimens (HeLa
cells and gel beads), a single cell and a barcode gel bead are trapped in AST and contact each other at the trapping point. When the device is turned
off, the assembled cell and bead are released together to move downstream. The white arrow points in the direction of lateral flow. The dotted
pentagon represents the position of the UHF device. The scale bar is 100 μm.
Yang et al. Microsystems & Nanoengineering (2022) 8:88 Page 13 of 18

at t =30 s, t =313 s and t =560 s and DMEM/PBS buffer
at other times. Furthermore, with a fluorescence micro-
scope and double stain kit (calcein-AM/propidium iodide
(PI)), in situ analysis of single cells was achieved, as shown
in Fig. 5c. By controlling the applied power precisely, a
single HeLa cell was trapped. Then, calcein-AM and PI
were injected into the microchannel. The trapped cells
showed good viability after 30 min of trapping, which also
illustrated the stability and biocompatibility of the SteAST
system. This in situ analysis technology has good com-
patibility with different types of staining kits, which gives
this platform the potential to be applied in the fields of
cell subpopulation profiling, immunoassays and rapid
detection of pathogens.
Among all single-cell analysis techniques, single-cell
RNA sequencing (scRNA-seq) has become one of the
most powerful approaches that enables unprecedented
temporal and spatial resolution
77
. In recent years, high-
throughput scRNA-seq has been established and com-
mercialized by integrating droplet microfluidics technol-
ogy and barcoded primer beads. At present, all three
methods (inDrop, Drop-seq, 10X Genomics Chromium
(10X)) use similar designs to generate droplets, on-bead
primers with barcodes to distinguish individual cells, and
unique molecular identifiers (UMIs) for bias correction.
Although a process for encoding tens of thousands of cells
has been realized, the process of pairing cells and barcode
gel beads is random. For example, in Drop-seq, a prob-
abilistic model of a barcode bead or a single cell packaged
in a droplet conforms to Poisson distribution models,
which allows only limited pairing efficiency
78
. Even the
best-performing technology (10X) requires millions of
barcode gel beads to complete the encoding of tens of
thousands of cells. Moreover, in some cases, the number
of cells is limited, and a loss of even one cell may affect the
final result. This unobservable assembly method cannot
guarantee that the target cells are successfully paired with
gel beads. Based on this, we believe that the introduction
of the SteAST platform to realize the observable and
controllable pairing of barcode beads and cells can over-
come the bottleneck of a low pairing rate and sample
compatibility. Herein, the assembly of a single cell and a
barcode bead (10X) was demonstrated as a proof of
concept. Samples of HeLa cells and gel beads were diluted
to ensure that only a single cell or gel bead passed through
the main channel at a time. First, a single cell entered the
main channel and was trapped by SteAS, as shown in Fig.
5d. Then, the pump for driving cells was turned off, while
that for gel beads was turned on. A single barcode was
injected into the main channel and trapped in the trap-
ping point. The single HeLa cell and gel bead contacted
each other at the trapping point to complete the pairing
process. Under the action of the SteAST and lateral flow,
an interaction between the single cell and the gel bead
occurred, and then they were assembled together. When
the assembly was achieved, the applied power was turned
off, and the assembled cell and gel bead could be released
for downstream analyses (to continue the standard pro-
tocol of 10X Genomics). The entire process is shown in
SI-Movie-12.
In situ analysis of CTCs from patient samples
To further prove the potential of multimode manip-
ulation based on SteAST in practical applications, we
tried to separate and analyze CTCs in the undiluted blood
of patients at the single-cell level. The heterogeneity and
kinds of CTCs in patient blood are more complex and
abundant than those in cultured cells, which makes CTC
separation from patient blood more difficult than blood
samples spiked with cultured cancer cells. This makes it
difficult to obtain high-purity CTCs from the patient’s
blood by separation methods based solely on size or
immunity. Benefitting from the multimode handling
mentioned above, we proposed a strategy for on-chip
CTC separation from undiluted patient blood based on
principles of both physics and immunity. The complete
process is shown in Fig. 6a. First, the SteAST platform was
used to selectively trap CTCs from the patient’s whole
blood. Then, a fluorescently coupled antibody was injec-
ted into the microchannel to realize in situ immune-based
analysis of the trapped cells. Finally, when the selectively
trapped cells passed both physical and immunological
identification, they were washed in situ to obtain a high
purity and optionally released for subsequent analysis.
Notably, due to the heterogeneity of CTCs in the actual
patient, a higher strength of SteAST was used here to
ensure the capture efficiency, and the final purity of CTCs
was ensured at the washing step.
Stage IV lung cancer patient blood (n=3) was chosen
for these experiments. The dye mixed with calcein-AM
and anti-epithelial cell adhesion molecule (anti-EpCAM)-
labeled red fluorescence (Biolegend, USA) was injected
into the channel to identify the type of trapped cell, as
shown in Fig. 6a and SI-movie-13. EpCAM plays a role in
the tumorigenesis and metastasis of carcinomas, so it can
act as a diagnostic marker for various cancers and as a
potential target for immunotherapeutic strategies
79
. The
three-inlet (PBS buffer, blood sample and dye) and single-
outlet microchannel was used here. When the power was
applied, the blood cells were divided into two fluids by
SteAST. After capturing the target cells, the inlets of
blood and PBS buffer were closed, and dye was injected to
identify the trapped cells. After staining, the dye inlet was
closed, and PBS buffer was used to wash the remaining
blood cells and dye. Calcein-AM (green) represents the
viability and position of trapped cells, while anti-EpCAM-
labeled red fluorescence represents EpCAM in the
membrane of trapped cells. The results in Fig. 6b and
Yang et al. Microsystems & Nanoengineering (2022) 8:88 Page 14 of 18

Supplementary Fig. S16 show a trapped single CTC
cluster from patient No. 1’s blood and 3T3 cell lines,
which is a low-expression EpCAM cell line and was
chosen as a target of the negative control group
80
. The
results demonstrated that both CTCs and 3T3 cells were
stained by calcein-AM and that CTCs were stained by
anti-EpCAM, while 3T3 cells did not dye red due to the
low expression of EpCAM, which indicates that the
identification method is reliable. The procedures of in situ
staining and washing are shown in Fig. 6b. After the single
cell selectively trapped by SteAST was further identified as
a CTC by immune recognition after 10 min, pure indivi-
dual CTCs were obtained by power modulation and
buffer washing. The results of selected trapped CTCs and
clusters from patients No. 2 and No. 3 are shown in
Supplementary Fig. S17.
Discussion
In summary, starting from the basic theory, we dis-
cussed the relationship among acoustic streaming,
acoustic fields and lateral flow through simulation to
experiments to design a SteAST system for multimode
manipulation at the single-cell level. Benefiting from the
UHF BAWs in TE vibration mode and the small footprint
of the device, highly confined SteAS is triggered by the
attenuation of BAWs in liquid media. The scale of
acoustic streaming vortices is tuned by microfluidics to
adapt to the requirements for single-cell handling. Due to
the UHF frequency, there is a short attenuation length
(under 15 μm for 1.8 GHz), and thus the influence of
standing acoustic waves can be ignored. Under the com-
bined action of the acoustic radiation force and the drag
force induced by vortices and lateral flow, a virtual tunnel
is generated along the boundary of the UHF device, and
quasi-static and dynamic modes are developed. Based on
the two modes, basic cell manipulation is achieved,
including selective trapping, rotation, dissociation, quan-
tum release and pairing. SteAST is applicable over a range
of lateral flow rates and can be rapidly tuned by applying
power to adjust the strength of acoustic streaming.
Notably, the migration and trapping processes in SteAST
are repeatable without adhesion because the trapping
point is suspended in the microchannel, which keeps
trapped cells away from the device. To verify the possi-
bility of multiple pretreatments and analyses in this
platform, 3D reconstruction, separation, fluorescence-
based in situ analysis and pairing with barcode gel beads
for downstream analysis are demonstrated. Moreover, the
selective trapping of CTCs in the undiluted patient’s
blood based on both physical and immune detection is
also achieved. Compared with other CTC separation
technologies, SteAST can obtain extremely high purity
(~100%) with high separation efficiency (Supplementary
Table S1), and this two-dimensional identification based
on physical and immunofluorescence avoids the bias of
purely immune-based separation and the poor specificity
in purely physical-based separation.
Although we have completed the preliminary verifica-
tion of multimode handling, there are still many areas that
need to be improved and problems that need to be
resolved in actual applications. For example, in rotation-
based reconstruction of a cluster, the image quality is
poor, and the algorithm is rudimentary. In CTC trapping
from whole blood, the fibers and detritus in the blood are
entangled with the trapped cells under long-term pro-
cessing, which affects the observation and subsequent
quantum release process. Also, the inefficient and time-
consuming pairing process relies on manual control.
These problems can be optimized by system updates of
both software and hardware in future work, including
optimization of device shape, geometry of microfluidics
and introduction of automatic fluid switching modules. At
the same time, the platform has the potential to be
developed. From the perspective of the platform itself,
aOFF ON
PBS Blood
Waste
Dye
Trapping
Single CTC
Analysis Wash
b
Blood cells
Bright field Calcein-AM Anti-EpCAM Merge
5 min
10 min
15 min
Fig. 6 Separation and identification of CTCs from patient blood.
aProcess of single CTC separation from patient blood. The
microchannel consists of three inlets and one outlet. The direction of
flow is shown by white arrows. After CTCs are trapped in SteAS, dye is
injected to achieve immune-based identification. The identified cells
were washed to improve purity. bProcess of staining and washing
step. The trapped cells were stained green and red, which means that
the cells demonstrated good viability and were CTCs from the
perspective of immunology. The scale bars in the images and detailed
images are 100 μm and 50 µm, respectively.
Yang et al. Microsystems & Nanoengineering (2022) 8:88 Page 15 of 18

with a small footprint based on an IC-compatible process,
the multi-UHF device integrated chip has the potential to
be utilized in a multistep handling system and allows for
easy integration with on-chip sensors for further char-
acterization. Another advantage of the small footprint is
that a large number of UHF devices can be integrated into
one chip to improve the throughput and reduce costs.
Limited by the performance-first design principle, the
current shape of the UHF device is pentagonal, which
makes the interaction between the tunnel and the lateral
flow relatively fixed. From the perspective of the appli-
cation, in conjunction with fluorescent image-based
reconstruction, cells stained by kits can be subtyped and
analyzed on a subcellular scale from both 3D bright fields
and fluorescent fields. In addition, the existing dissocia-
tion procedure causes the loss of spatial information that
is necessary for reconstructing the spatial organization of
single-cell genomic and transcriptomic landscapes in a
cluster/tissue. Based on a single-cell-scale tunnel, if the
manipulation of 3D reconstruction, visualized dissocia-
tion and controllable release are integrated, then there is
an opportunity to convert the spatial position information
of each cell into time sequence information to achieve the
dissociation of clusters without losing spatial information.
Previous studies based on UHF BAWs in microfluidics
chips have mainly focused on the enrichment effect of
particles. When SteAST interacts with biological particles,
due to the heterogeneity of sizes and morphology, the
characteristics are highlighted, including the effects of
rotation, 3D focusing, and dissociation, which make
multimode manipulation for complex applications in
biological research possible. Altogether, we believe this
platform, as a versatile tool, shows great potential as a μ-
TAS or pretreatment module to be integrated into exist-
ing single-cell analysis processes for applications in liquid
biopsy, personalized cancer therapy, drug discovery and
high-throughput scRNA-seq.
Materials and methods
Design and fabrication of the device
The UHF BAW resonator is designed and fabricated by
simulation software and IC-process. More details are
provided in the SI.
System setup
The acoustic resonator was controlled by a sinusoidal
signal (1.8 GHz), which was generated by a signal gen-
erator (Agilent, N5171B) and amplified by a power
amplifier (Mini-Circuits, ZHL-5 W-422+). The resonator
was wire-bonded to evaluation boards for signal trans-
mission. The performance of the UHF device was tested
by a vector network analyzer (Agilent, N50171C). The
PDMS channel was fabricated by a standard soft litho-
graphy process and assembled with the silicon substrate
by pressure. The inlet and outlet holes in the PDMS
channel were created by a syringe needle. The sample was
driven by a syringe pump (Harvard, 70-4504). The syringe
was connected to a microchannel by a Teflon tube (the
inner diameter was 0.3 mm). The signal generator and
syringe pump were controlled by LabVIEW software. The
experiments proceeded on the stage of a fluorescence
microscope (Olympus, BX53) with a CCD camera
(Olympus, DP73) or a high-speed camera (Photron,
UX50) and confocal microscope (Leica, SP8).
Finite element simulation
A 3D model of the UHF device was built in COMSOL
Multiphysics 5.5. (COMSOL Inc., USA)
81
. More details
are provided in the SI.
Sample preparation
PS particles (Macklin) were diluted with DI water and
sonicated for 5 min to improve the monodispersity. HeLa
cells and 3T3 cells were grown in Dulbecco’s modified
Eagle medium (DMEM) supplemented with 10% fetal
bovine serum and 1% penicillin–streptomycin in an
incubator at 37 °C and 5% CO
2
, followed by dissociation
with trypsin. Then, suspended cells were extracted in
isotonic phosphate-buffered saline (PBS) solution by
centrifugation (500 × g, 6 min for HeLa and 800 × g, 4 min
for 3T3). Ethics approval for sample collection was
approved by Tianjin Medical University Cancer Institute
& Hospital Ethics Committee (E2016055). Blood from
healthy donors and patients was acquired from Tianjin
Medical University Cancer Institute & Hospital. Blood
samples were collected in vacutainer tubes containing
anticoagulant ethylenediaminetetraacetic acid (EDTA)
and processed within 2 days. For the experiment of CTC
separation from diluted blood, HeLa cells were trypsi-
nized and resuspended at the desired concentration
(1 × 10
5
cellsper mL) in PBS buffer, added to human blood
samples, diluted 100-fold with PBS buffer (10~100 HeLa
cells/10
4
red blood cells) and mixed for 10–15 min at
room temperature. For CTC separation from the patient’s
blood, undiluted whole blood was injected into the
microchannel.
3D reconstruction
The 3D reconstruction procedure can be divided into
image processing and reconstruction. More details are
provided in the SI.
Acknowledgements
The authors gratefully acknowledge the National Key R&D Program of China
(2018YFE0118700), the National Natural Science Foundation of China (NSFC
No. 62174119, 21861132001), Tianjin Applied Basic Research and Advanced
Technology (17JCJQJC43600) and the 111 Project (B07014) for funding and the
support from Ms. Jihong Liu (Leica) and Dr. Xiaofeng Liu (Tianjin Medical
University) in imaging with confocal microscopy and immune staining. Y.Y.
Yang et al. Microsystems & Nanoengineering (2022) 8:88 Page 16 of 18

thanks Ms. Haolin Li for company and support. Y.Y. wledge financial support
from the Zhejiang Lab’s International Talent Fund for Young Professionals.
Author contributions
Conceptualization: Y.Y. Methodology: Y.Y., L.Z. Investigation: Y.Y., H.Z., W.C., C.S.
Visualization: Y.Y. Supervision: W.P., Y.W., X.R., X.D. Writing—original draft: Y.Y.
Writing—review & editing: Y.Y., X.D.
Data availability
All data are available in the main text or the supplementary materials. Further
information is available from the corresponding author upon reasonable
request.
Conflict of interest
X.D. has three C.N. patents (CN112080420A, CN112076808A, CN112080385A)
and three PCT patents (PCT/CN2020/096176, PCT/CN2020/096178, PCT/
CN2020/096131) related to stereo acoustic streaming and acoustofluidics. All
other authors declare they have no competing interests.
Supplementary information The online version contains supplementary
material available at https://doi.org/10.1038/s41378-022-00424-9.
Received: 20 February 2022 Revised: 28 June 2022 Accepted: 29 June 2022
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