Topographical Manipulation of Microparticles and Cells with Acoustic

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Topographical manipulation of microparticles and cells with acoustic microstreaming Xiaolong Lu, Fernando Soto, Jinxing Li, Tianlong Li, Yuyan Liang, and Joseph Wang ACS Appl. Mater. Interfaces, Just Accepted Manuscript • DOI: 10.1021/acsami.7b15237 • Publication Date (Web): 13 Oct 2017 Downloaded from http://pubs.acs.org on October 14, 2017

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ACS Applied Materials & Interfaces

Topographical manipulation of microparticles and cells with acoustic microstreaming

Xiaolong Lu, a,b Fernando Soto, a Jinxing Li, a Tianlong Li, a Yuyan Liang a and Joseph Wang*a a

Department of Nanoengineering, University of California San Diego, La Jolla, California 92093, United States b

State Key Laboratory of Mechanics and Control of Mechanical Structures, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China *Correspondence to: [email protected]

Abstract: Precise and reproducible manipulation of synthetic and biological microscale objects in complex environments is essential for many practical biochip and microfluidic applications. Here we present an attractive acoustic topographical manipulation (ATM) method to achieve efficient and reproducible manipulation of diverse microscale objects. This new guidance method relies on the acoustically induced localized microstreaming forces generated around microstructures, which are capable of trapping nearby microobjects and manipulating them along a determined trajectory based on local topographic features. This unique phenomenon is investigated by numerical simulations examining the local microstreaming in the presence of microscale boundaries under the standing acoustic wave. This method can be used to manipulate a single microobject around a complex structure, as well as collective manipulation of multiple objects moving synchronously along complicated shapes. Furthermore, The ATM can serve for automated maze solving, by autonomously manipulating microparticles with diverse geometries and densities, including live cells, through complex maze-like topographical features, without external feedback, particle modification or adjusting operational parameters.

Key Words: Micromachine, Topographical Manipulation, Acoustic Microstreaming, Microrotor, Dynamic Assembly, Biological Isolation,

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INTRODUCTION The recent development of manipulation technologies in the micro/nanoscale offers considerable promise in nanomachines, microfactories, lab on chip systems, cell biology and tissue engineering.1-3 For practical applications, robust control over the propulsion and directionality are essential to steer and navigate micro/nano objects towards their destination. To date, conventional manipulation methods have been reported to be successful in specific applications, including the use of optical tweezers,4-10 external magnetic fields,11-18 electrokinetic forces,19-24 hydrodynamic flows25-28 and surface acoustic waves.29-32 Although optical tweezers have been successfully used to manipulate micro objects, there may be irreversible damage to the sample by laser-induced heating.4-10 The use of magnetic field manipulation offers fast propulsion and orientation control, but requires complex systems to operate, magnetized materials and sophisticated feedback actuation strategies for achieving guidance of a single element.11-18 Electrokinetic forces are determined by particle conductivity and can destroy biological species by current-induced heating.19-24 Hydrodynamic interaction can use grooves or steps to give rise to sliding and directional motion,25-28 yet, micro objects can only temporally be steered along simple pathways. Surface acoustic waves are capable of precisely manipulating diverse microobjects, but the reproducible navigation with complex topographical guidance remains an unmet challenge.29-32 Recent advances in acoustofluidics have made it possible to collect or sort microparticles in a simple manner but cannot address the challenging guiding problems in complex topographical structures.33-34 Executing a wide range of complex topographical guidance on diverse microobjects for future applications will require new methods that offer simple, controllable, non-specific and long lasting operation. Herein, we present an attractive Acoustic Topographical Manipulation (ATM) methodology to efficiently and reproducibly manipulate diverse micro objects. This new acoustic guidance method relies on the localized microstreaming forces generated around a topographical feature, which are capable of trapping nearby microobjects and manipulating them by moving along the topological boundaries of the feature. Finite element method (FEM) simulations are used to confirm this unique phenomenon and to study the local microstreaming in the presence of microscale boundaries under the standing acoustic wave. 2


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The micro object path is determined by the boundary of the feature shape, which leads to precise positioning and repeatable orbit trajectories during multiple manipulation cycles. This behavior allows the moving microparticle to be used as rotatory microengines due to their high angular speed and controllability. This unique phenomenon can also be extended to manipulate objects around a single complex structure, as well as towards the complex collective action of multiple objects moving synchronously. Furthermore, the ATM can serve for automated maze solving, by guiding microparticles, typical artificial microrobots with diverse geometries, and biological species, autonomously through complex maze-like topographical features, without the need of external feedback or modifying operational parameters. The attractive behavior of the new topographical manipulation depends on various critical parameters, such as particle size, shape and topographical boundaries. Such guidance of diverse microobjects could pave the way to complex manipulations for micromachines relevant to active colloidal assemblies, lab-on-chip architectures, along with microfluidic and nanoelectromechanical systems.

RESULTS AND DISCUSSION The working principle and applicability of ATM method will be clearly depicted in the following sections, going from simple to complex topographical features. Figure 1a illustrates the setup used to generate the ATM. First, we studied the working principle using a simple topographical feature consisted of polystyrene spherical (PS) particles (10 µm) in aqueous solution. These particles are introduced to the system and sediment on the bottom of the cell surface. After sedimentation, the particles are uniformly distributed over the substrate, with some of them forming obstacles attached to the surface via electrostatic and Van der Waals interactions.35,36 Application of a standing acoustic wave field forms an ambient acoustic streaming in the cell, leading to a localized microstreaming around the obstacle shape which cannot be detached by the acoustic field. Details of the experimental cell configuration and thevibration pattern at resonance are provided in Figure S2 of the SI. A combination of acoustic microstreaming and radiation forces can trap nearby microparticles, compared to the acoustic microstreaming force alone that propels these microparticles around the obstacle,37as illustrated schematically in Figure 1a and experimentally in Figure 1b taken from Video S1, 3



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using a single-microparticle obstacle (colored in blue) that serves as the topographical pathway of the microparticle (colored in red). The mean speed of the microparticle is 105 µm/s at 504 kHz and 15 Vp-p (peak-to-peak voltage value). To validate the working principle, we rely on Finite Element Method (FEM) for modeling the microstreaming generated around the obstacle. Details of this simulation can be found in the Supporting Note (see the Supporting Information). Using theoretical computing methods for calculating acoustic streaming driven by the Reynolds stress,38-43 we obtained a typical counterclockwise vortex. Figure 1c displays the localized microstreaming around the obstacle site, which is significantly stronger than the ambient streaming in other areas. This was also confirmed experimentally by stacked moving trajectories of fluorescent particles, shown in Figure 1d. The microparticle’s moving directionality can be tailored by applying different frequencies. It was observed that the microparticle moves in a counterclockwise direction around the obstacle using a frequency of 504 kHz, (see Figure 1e taken from Video S2). When the applied frequency is changed to 520 kHz, the propulsion orientation is switched to a clockwise direction (see Figure 1e, taken from Video S2, and Figure S3 for FEM simulation, showing the reversed acoustic microstreaming vortex). Such behavior is attributed to the change of the acoustic cell’s vibrating pattern.44-46 At different applied frequencies, the cell provides different types of acoustic-wave patterns. Consequently, the location of the exciting source and corresponding boundaries will change, leading to the localized reversed direction of the acoustic streaming vortex. Furthermore, the microparticle’s velocity can also be tuned on demand, by modulating the applied voltage and frequency of the acoustic transducer. Figure 1f illustrates the effect of modulating the applied frequency upon the mean velocity while keeping the applied voltage constant. The maximum speed is observed when the applied frequency approaches 504 kHz, which is one of the resonant frequencies of the acoustic cell. At this resonance frequency, the vibration magnitude of the acoustic cell is the highest, leading to the highest acoustic pressure and hence to the maximum velocity. Figure 1g illustrates the velocity modulation obtained by changing the applied voltage while maintaining a constant applied frequency of 504 kHz. These results illustrate that the mean velocity of the microparticle increases nearly linearly upon increasing the applied voltage. The slight variation between the theoretical and 4


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experimental results may be attributed to other forces at play,41 and to the amplifier that can lead to hysteresis and plateau, especially at higher voltages. Automated guidance of the moving microparticle around the obstacle can act as a rotary microengine with high angular speed and tunability realized by adjusting the driving frequency and voltage of the acoustic transducer.

Figure 1 Operating process of Acoustic Topographical Manipulation (ATM). (a) Schematic illustration showing the setup and working principle used to generate the ATM. (b) Schematic (top) indicating the microparticle and the obstacle, along with actual microscopy images (bottom), taken from the Video S1 at 0.1 sec intervals (I-III), illustrating the topographic guidance of a microparticle (red) moving around the obstacle (blue). Scale bar, 10 µm. US field parameters: 15 Vp-p, 504 kHz. (c) FEM simulation illustrating the localized acoustic microstreaming vortex as the manipulating force. (d) The localized acoustic streaming represented by overlapped fluorescent microscopic sequences of 1µm particles. Scale bar, 10 µm. US field parameters: 15 Vp-p, 504 kHz. (e) Modulation of the guidance orientation from the counterclockwise circular motion (US field parameters: 15 Vp-p, 504 kHz) to clockwise circular motion (US field parameters: 15 Vp-p, 520 kHz), taken from the Video S2 at 0.3 sec intervals. Scale bars, 10 µm. (f) Dependence of the manipulating velocity on the driving frequency over the 500 to 510 kHz range using a constant voltage of 15 Vp-p. (g) Dependence of the manipulating velocity on the driving voltage over the 0 to 30 Vp-p range with a frequency of 504 kHz. 5



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As the ATM is accomplished by the local streaming around closed boundaries, such operating principle can be extended to the guidance of a microparticle around sphericalassembled obstacles with increasing complexity (Figure 2). Figure 2a-b, taken from Video S3, display a microparticle guided around different obstacle shapes with increased complexity, from a 3-microparticle ensemble to a 5-microparticle ensemble (using 30 Vp-p and 504 kHz). Similar orientations are observed, indicating that the configuration of the obstacle does not affect the ATM directionality under similar actuation conditions. However, the average angular speed for the two obstacles shapes decreases from 6.3 rad/s to 5.9 rad/s, respectively. It is well known that with the same tangential velocity, one microparticle will have a higher angular speed upon decreasing the guiding radius. The new guidance principle has been further extended to achieve collective movement of multiple microparticles around the same obstacle with localized gated speed control. The schematic illustration of Figure 2c shows a complex topographical feature consisted of eleven microparticles (colored in blue) and one gate microparticle (colored in black) placed close to the main feature at a 10 µm distance. Simultaneous guidance of four different microparticles (multicolor) around this complex feature can be achieved. The actual image of Figure 2c taken from Video S4 illustrates the motion trajectories of each of these microparticles, represented by different colored track lines based on these microparticles (using 30 Vp-p and 504 kHz). The trajectories of microparticles’ movement are almost identical and follow closely the shape boundary of the obstacle structure. By recording the exact location of every microparticle each time and overlaying them together in the x-y plane, we observed that during the movement, the microparticle’s position is determined by the topographical boundary and that all the trajectories are nearly identical (Figure 2d). Such behavior means that multiple microparticles can operate synchronously around a complex topographical feature with accurate position identification. Interestingly, the presence of the “gate particle” could periodically modulate the moving speed, creating “speed bumps” in the microparticle path. Figure 2e shows the dependence of the microparticles’ velocity on the operating time. These data illustrate that the velocity is not constant and that the peak velocity is around 32 µm/s. The microparticle is dramatically decelerated upon approaching the “gate” 6


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microparticle and is rapidly accelerated to its maximum speed after passing through this gate area. Such “bumping” phenomenon illustrates that the presence of “gate particle” in the vicinity of the main structure disrupts the local microstreaming and modulates the microparticle velocity. Overall, these results indicate that microparticles with ATM are capable of cooperative work with dynamically changing behaviors.

Figure 2 Acoustic Microstreaming based Topographical Manipulation of microparticles around obstacles with increased complexity. (a&b) Microscopy images (taken from Video S3) illustrating the ATM of a microparticle around obstacles of 3 (a), and 5(b) microparticles. Particles highlighted in blue (for obstacles) and red (for microparticle). (c) Schematic (left) and microscopy image (right, taken from Video S4), illustrating the joint and cooperated movement of multiple microparticles around a complex topographical feature (blue) with a gate particle (black) nearby. (d) Trajectories of microparticles moving along the microparticle-assembled feature in the x-y plane. (e) Time-dependent linear velocity of the four microparticles with the presence of the “bump”. Scale bar, 10 µm. US field parameters, 30 Vp-p and 504 kHz.

The ATM approach can also serve for automated guidance of particles through complex paths with diverse topological features, without the need of external feedback or modifying operational parameters. Figure 3a-b illustrate the topographical manipulation of colloidal particles through complex maze structures achieved by ATM. One 10 µm PS particle firstly approaches to the maze structure and then be captured by the localized acoustic streaming and 7



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steered in close contact with the maze wall. As shown in Figure 3b and Video S5, the PS particle travels successfully from the entrance to the exit and follows the red track-line without extra delay, indicating that ATM is highly efficient for navigation through a complex path. Some particles are trapped in some regions of the maze, where there are no strong and continuous acoustic streaming and the electrostatic interaction between the trapped particles and the maze walls is stronger than the ambient acoustic field (Figure S4). These components are in the same size scale range as the SEM micrograph shown in Figure 3c, which displays a 10 µm PS particle closely contacted with the inner wall of the maze. The FEM simulations in Figure 3d demonstrate that the acoustic microstreaming generated along the inside wall boundaries of the maze is the driving force for realizing such the topographical guidance. The figure illustrates also the velocity profile of the microstreaming generated within the maze structure, showing that the particle path is defined by the topographical feature. The part with small arrows or no arrows means that no obvious streaming are formed, which agrees well with our data on the topographical manipulation of particles. Detailed streaming profile with streamlines at the dead end and zoomed arrows at the pathway are provided in Figures S5 and S6. Furthermore, in Figure 3e we illustrate the acoustic streaming generated by the topographic patterns using a stack of overlapping fluorescent microscopic sequences, which track the displacement of fluorescent beads at the jump point of the maze. Microparticles guided through maze have reproducible paths and long operating time as shown in figure 3f, which illustrates the XY plane position of four different path loops followed by a single microparticle. The average path distance of a cycle is 948 µm, and the deviation of the path trajectories is less than 2%, demonstrating that this method can retain the particles in the structures over long periods (3 minutes for this test but not limited to this value) and multiple cycles. Figure S7 illustrates the dependence of the locomotion velocity on the particle size. PS microparticles of 2, 5 and 10 µm display speeds of 16.3 ± 5.9, 32.2 ± 7.8, and 35.1± 5.5 µm/s, respectively, which indicate that the locomotion velocity decreases upon decreasing the particle diameter. Besides that, a collective work of multiple microparticles is also effective for achieving accurate topographic guidance through the maze. So far, intensive research efforts have been focused on motion control of micro/nano robots via magnetic navigation, which needs complicated adjustment of external magnetic 8


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field and feedback loops.47 The ATM provides an alternate and attractive method to put forward micro/nano robots towards autonomous topographical manipulation or transportation. In this section, we tested the maze solving abilities for four different geometries of the most fashionable microrobots, including, Au Nanowires (AuNWs),48,49 Graphene platinum (Gph/Pt) microengines,50,51 Polystyrene platinum (PS/Pt) Janus motors52-54 and Polystyrene platinum (PS/Pt) Janus assembly, as shown in Figure 3gand Video S6. It can be seen that all of these synthetic microobjects successfully pass through the maze. Specifically, AuNWs and Gph/Pt microengines are easy to be trapped in the corner and after several reorientations, they will move back towards the exit with the guidance of microstreaming. Janus micromotors and their assembly behave similarly as the PS particles for maze solving, which indicates the asymmetrical density of spheres can be ignored using ATM method. Interestingly, due to the clear visual asymmetry of Janus particles and triples (black and with section), we observed that the particles also present a self-spin movement while traveling through the maze. This behavior can be attributed to the gradient of acoustic microstreaming force, which is extremely strong at the surface of maze walls and dramatically decreases with the increased distance to the walls. The automated and reproducible path guidance could help generating micro assembly lines.

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Figure 3 Automated topographical guidance of colloidal particles through complex maze structures under acoustic microstreaming manipulation. (a) Schematic and (b) actual microscopy image taken from Video S5, illustrating a 10µm microparticle navigating through a maze. Scale bar, 60 µm. US field parameters, 30 Vp-p and 134 kHz. (c) SEM image indicating a microparticle (red) contacted with the inside wall (blue). Scale bar, 20 µm. (d) FEM simulation illustrating the acoustic microstreaming generated along the inside wall boundaries of the maze as the driving force to accomplish topographical guidance. (e) Acoustic streaming at the jump point represented by overlapped fluorescent microscopic sequences of 1µm particles. Scale bar, 10 µm. US field parameters, 30 Vp-p and 134 kHz. (f) Comparison of 4 loops trajectories of a microparticle reproducibly passing through the maze-like topographical feature in the x-y plane. (g)Automated ATM guidance of different shapes of micro robots, taken from Video S6, including (I) Au Nanowire, (II) Gph/Pt hollow microengine, (III) PS/Pt Janus motor, and (IV) a PS/Pt Janus triplet assembly. Scale bar, 20 µm. US field parameters, 30 Vp-p and 134 kHz.

Finally, we demonstrated that the ATM methodology can also be used to efficiently manipulate biological species, such as cancer cells (human gastric adenocarcinoma, AGS) and Red Blood Cells (RBCs), as illustrated in Figure 4 and Video S7. These biological species can be guided and maneuvered around the complex topographical features presented in the complex maze structure, including but not limited to 90° corners (Figure 4a-I and 4d-I), 10


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straight lines (Figure 4a-II and 4d-II), line changes over non-connected walls (Figure 4a-III and 4d-III) and 180° turn around (Figure 4a-IV and 4d-IV). We found that the traveling velocity of the biological species varies upon movement through the different topographic features of the maze, as displayed in Figure 4b and Figure 4e. Both the cancer cell and red blood cell display rapid movement while traveling along a straight line and reduce their speeds while traveling at corners. When the cancer cell encounters a change of lanes between disconnected maze walls with a gap of 40 µm (see Figure 4b-III), the traveling velocity is greatly diminished. This effect is due to the weaker microstreaming force at larger distances from the maze wall. Comparatively, the autonomous RBC guidance in Figure 4d was tested using a maze half the size of the original in Figure 4a, resulting in a faster RBC traveling velocity. From Figure 4c and 4f, the velocity of RBC during lane changing at location III is 2 times higher than that of a cancer cell, which is attributed to the smaller size of the gap (20 µm, see Figure 4d-III) between the maze walls. It was also observed that the velocity of RBC at location II oscillates more remarkably than the cancer cell does, which may be caused by the RBC’s irregular shape induced self-rolling and random collisions with the maze walls. This method could serve as an attractive alternative for manipulating biological samples without the need of microfluidic systems and related pumping.

Figure 4 Autonomous maze solving process of biological cells by ATM. Actual microscopy images 11



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(left), taken from Video S7, indicating (a) a cancer cell (scale bar, 60 µm) and (d) a red blood cell (scale bar, 60 µm) passing through a complex maze using different operating patterns including (I) 90° corners, (II) Go straight, (III) Change lane over non connected walls and (IV) 180° turn round. Velocity changes of (b) a cancer cell and (e) a red blood cell during one cycle of movement. Comparison of moving velocity of (c) a cancer cell and (f) a red blood cell at different operating locations. US field parameters, 30 Vp-p and 134 kHz.

CONCLUSIONS In summary, we presented a precise topographical guidance and manipulation method of micro-objects with acoustic microstreaming. This methodology offers autonomous and reproducible guidance of synthetic and biological objects through complex paths with diverse topological features, without the need of external feedback or modifying operational parameters. With numerical simulations, we analyzed the local acoustic streaming around the closed boundaries of different features. This analysis indicates that the actuation relies solely on the local microstreaming produced by the shape boundaries with different shape configurations, enabling to produce tunable, long lasting, and cooperative manipulation. The speed and orientation of traveling microparticles can be easily modulated by changing the applied voltage and frequency. Multiple microparticles can also be synchronously manipulated around a complex assembly. We also demonstrated that the working principle of acoustic microstreaming based topographical manipulation can be extended to automated maze solving. A detailed study of the parameters relevant to microparticle guidance, including particle size and shape, path trajectory, maze size and the distinct wall boundaries features, reveals that this methodology is highly reproducible, and that diverse synthetic and biological objects can be autonomously manipulated. Future research will test the limits of this principle, and will assess the effect of the structure complexity upon the particle manipulation. The attractive capabilities of topographical guidance under acoustic streaming manipulations can play an important role in diverse practical applications, such as autonomous microrobots transportation system, biological sample isolation and low-volume chemical mixing.

Supporting Information Electronic Supporting Information available: Videos of topographical manipulation of 12


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microparticles and cells with acoustic microstreaming are available in the Supporting Information.

AUTHOR INFORMATION Corresponding Author *J.W.: E-mail: [email protected]. Author Contributions X.L., F.S. and J.L. contributed equally to this work. J.W. supervised the project. X.L., F.S. and J.L. conducted the experiments. X.L., F.S., J.L. and Y.L. analyzed the data and cowrote the paper. All authors have given approval to the final version of the manuscript. Notes The authors declare no competing financial interest.

ACKNOWLEDGEMENTS This project was supported by the Defense Threat Reduction Agency Joint Science and Technology Office for Chemical and Biological Defense (Grant Nos. HDTRA1-14-1-0064) and the National Natural Science Foundation of China (No. 51505222). X. L. was supported by the Scholarship Fund from China Scholarship Council (CSC). F. S. acknowledges fellowship from the UC MEXUS-CONACYT. We also thank Wenjuan Liu and Chuanrui Chen for helpful assistance and discussions.

REFERENCES (1) Ashkin, A.; Dziedzic, J. M.; Bjorkholm, J. E.; Chu, S. Observation of a Single-Beam

Gradient Force Optical Trap for Dielectric Particles. Opt. Lett. 1986, 11, 288-290. (2) Chiou, P. Y.; Ohta, A. T.; Wu, M. C. Massively Parallel Manipulation of Single Cells

and Microparticles Using Optical Images. Nature 2005, 436, 370-372. (3) Wang, J. Nanomachines: fundamentals and applications, Wiley-VCH, Weinheim,

Germany, 2013, ISBN 978-3-527-33120-8. 13



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(4) Grier, D. G. A Revolution in Optical Manipulation. Nature 2003, 424, 810-816. (5) MacDonald, M. P.; Spalding, G. C.; Dholakia, K. Microfluidic Sorting in an Optical

Lattice. Nature 2003, 426, 421-424. (6) Curtis, J. E.; Koss, B. A.; Grier, D. G. Dynamic Holographic Optical Tweezers. Opt.

Commun. 2002, 207, 169-175. (7) Garces-Chavez, V.; Dholakia, K.; Spalding, G. C. Extended-Area Optically Induced

Organization of Microparticles on a Surface. Appl. Phys. Lett. 2005, 86, 031106. (8) Yang, A. H. J.; Moore, S. D.; Schmidt, B. S.; Klug, M.; Lipson, M.; Erickson, D. Optical

Manipulation of Nanoparticles and Biomolecules in Sub-Wavelength Slot Waveguides. Nature 2009, 457, 71-75. (9) Zhang, X.; Halvorsen, K.; Zhang, C. Z.; Wong, W. P.; Springer, T. A.

Mechanoenzymatic Cleavage of the Ultralarge Vascular Protein Von Willebrand Factor. Science 2009, 324, 1330-1334. (10) Juan, M. L.; Righini, M.; Quidant, R. Plasmon Nano-Optical Tweezers. Nat. Photonics

2011, 5, 349-356. (11) Yan, J.; Skoko, D.; Marko, J. F. Near-Field-Magnetic-Tweezer Manipulation of Single

DNA Molecules. Phys. Rev. E 2004, 70, 011905. (12) Timonen, J. V. I.; Grzybowski, B. A. Tweezing of Magnetic and Non-Magnetic Objects

with Magnetic Fields. Adv. Mater. 2017, 29, 1603516. (13) Lee, H.; Purdon, A. M.; Westervelt, R. M. Manipulation of Biological Cells Using a

Microelectromagnet Matrix. Appl. Phys. Lett. 2004, 85, 1063-1065. (14) Khademhosseini, A.; May, M. H.; Sefton, M. V. Conformal Coating of Mammalian Cells

Immobilized onto Magnetically Driven Beads. Tissue Eng. 2005, 11, 1797-1806. (15) Manosas, M.; Spiering, M.; Zhuang, Z.; Benkovic, S. J.; Croquette, V. Coupling DNA

Unwinding Activity with Primer Synthesis in the Bacteriophage T4 Primosome. Nat. Chem. Biol. 2009, 5, 904-912. (16) Snezhko, A.; Aranson, I. S. Magnetic Manipulation of Self-Assembled Colloidal Asters.

Nat. Mater. 2011, 10, 698-703. (17) Carias, V.; Porshokouh, Z. N.; Repa, K. S.; Alonso, J.; Srikanth, H.; Rühe, J.; Toomey,

R.; Wang, J. Remotely Controlled Micromanipulation by Buckling Instabilities in Fe3O4 14


Page 14 of 19

Page 15 of 19

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Nanoparticle Embedded Poly(N-isopropylacrylamide) Surface Arrays. ACS Appl. Mater. Interfaces 2016, 8, 28012-28018. (18) Guo, Q.; He, Y.; Lu, H. P. Manipulating and Probing Enzymatic Conformational

Fluctuations and Enzyme-Substrate Interactions by Single-Molecule FRET-Magnetic Tweezers Microscopy. Phys. Chem. Chem. Phys. 2014, 16, 13052-13058. (19) Morgan, H.; Green, N. G.; Hughes, M. P.; Monaghan, W.; Tan, T. C. Large-area

Travelling-Wave Dielectrophoresis Particle Separator. J. Micromech. Microeng. 1997, 7, 65-70. (20) Cabrera, C. R.; Yager, P. Continuous Concentration of Bacteria in a Microfluidic Flow

Cell Using Electrokinetic Techniques. Electrophoresis 2001, 22, 355-362. (21) Hughes, M. P. Strategies for Dielectrophoretic Separation in Laboratory-on-a-Chip

Systems. Electrophoresis 2002, 23, 2569-2582. (22) Pethig, R.; Talary, M. S.; Lee, R. S. Enhancing Traveling-Wave Dielectrophoresis with

Signal Superposition. IEEE Eng. Med. Biol. Mag. 2003, 22, 43-50. (23) Kremser, L.; Blaas, D.; Kenndler, E. Capillary Electrophoresis of Biological Particles:

Viruses, Bacteria, and Eukaryotic Cells. Electrophoresis 2004, 25, 2282-2291. (24) Jamshidi, A.; Pauzauskie, P. J.; Schuck, P. J.; Ohta, A. T.; Chiou, P. Y.; Chou, J.; Yang,

P.; Wu, M. C. Dynamic Manipulation and Separation of Individual Semiconducting and Metallic Nanowires. Nat. Photonics 2008, 2, 86-89. (25) Simmchen, J.; Katuri, J.; Uspal, W. E.; Popescu, M. N.; Tasinkevych M.; Sánchez, S.

Topographical Pathways Guide Chemical Microswimmers. Nat. commun. 2016, 7, 10598. (26) Spagnolie, S. E.; Lauga, E. Hydrodynamics of Self-propulsion Near a Boundary:

Predictions and Accuracy of Far-field Approximations. J. Fluid Mech. 2012, 700, 105147. (27) Uspal, W. E.; Popescu, M. N.; Dietrich, S.; Tasinkevych, M. Self-propulsion of a

Catalytically Active Particle near a Planar Wall: from Reflection to Sliding and Hovering. Soft Matter 2015, 11, 434-438. (28) Spagnolie, S. E.; Moreno-Flores, G.; Bartolo, D.; Lauga, E. Geometric Capture and

Escape of a Microswimmer Colliding with an Obstacle. Soft Matter 2015, 11, 396-411. (29) Ding, X.; Lin, S. S.; Kiraly, B.; Yue, H.; Li, S.; Chiang, I. K.; Shi, J.; Benkovic, S. J.; 15



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Huang, T. J. On-Chip Manipulation of Single Microparticles, Cells, and Organisms Using Surface Acoustic Waves. Proc. Natl. Acad. Sci. USA 2012, 109, 11105-11109. (30) Lenshof, A.; Laurell, T. Continuous Separation of Cells and Particles in Microfluidic

Systems. Chem. Soc. Rev. 2010, 39, 1203-1217. (31) Rezk, A. R.; Qi, A.; Friend, J. R.; Li, W. H.; Yeo, L. Y. Uniform Mixing in Paper-Based

Microfluidic Systems Using Surface Acoustic Waves. Lab Chip 2012, 12, 773-779. (32) Dual, J.; Hahn, P.; Leibacher, I.; Möller, D.; Schwarz, T. Acoustofluidics 6:

Experimental Characterization of Ultrasonic Particle Manipulation Devices. Lab Chip 2012, 12, 852-862. (33) Huang, P. H.; Chan, C. Y.; Li, P.; Nama, N.; Xie, Y.; Wei, C. H.; Chen Y.; Ahmed, D.;

Huang, T. J. A Spatiotemporally Controllable Chemical Gradient Generator via Acoustically Oscillating Sharp-edge Structures. Lab Chip 2015, 15, 4166-4176. (34) Huang, P. H.; Nama, N.; Mao, Z.; Li, P.; Rufo, J.; Chen Y.; Xie, Y.; Wei, C. H.; Wang,

L.; Huang, T. J. A Reliable, Programmable Acoustofluidic Pump Powered by Oscillating Sharp-edge Structures. Lab Chip 2014, 14, 4319-4323. (35) Gady, B.; Schleef, D.; Reifenberger, R.; Rimai, D.; DeMejo, L. P. Identification of

Electrostatic and van der Waals Interaction Forces between a Micrometer-Size Sphere and a Flat Substrate. Phys. Rev. B 1996, 53, 8065-8070. (36) Xu, Q.; Zhao, X. Electrostatic Interactions versus van der Waals Interactions in the Self-

Assembly of Dispersed Nanodiamonds. J. Mater. Chem. 2012, 22, 16416-16421. (37) Ahmed, D.; Ozcelik, A.; Bojanala, N.; Nama, N.; Upadhyay, A.; Chen, Y.; Hanna-Rose,

W.; Huang, T. J. Rotational Manipulation of Single Cells and Organisms Using Acoustic Waves. Nat. commun. 2016, 7, 11085. (38) Muller, P. B.; Barnkob, R.; Jensen M. J. H.; Bruus, H. A Numerical Study of

Microparticle Acoustophoresis Driven by Acoustic Radiation Forces and StreamingInduced Drag Forces. Lab Chip 2012, 12, 4617-4627. (39) Bruus, H. Acoustofluidics 7: The Acoustic Radiation Force on Small Particles. Lab Chip

2012, 12, 1014-1021. (40) Ahmed, D.; Muddana, H. S.; Lu, M.; French, J. B.; Ozcelik, A.; Fang, Y.; Butler, P. J.;

Benkovic, S. J.; Manz A.; Huang, T. J. Acoustofluidic Chemical Waveform Generator 16


Page 16 of 19

Page 17 of 19

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


and Switch. Anal. Chem. 2014, 86, 11803-11810. (41) Ahmed, D.; Baasch, T.; Jang, B.; Pane, S.; Dual J.; Nelson, B. J. Artificial Swimmers

Propelled by Acoustically Activated Flagella. Nano Lett. 2016, 16, 4968-4974. (42) Muller, P. B.; Rossi, M.; Marín, A. G.; Barnkob, R.; Augustsson, P.; Laurell, T.; Kähler,

C. J.; Bruus, H. Ultrasound-Induced Acoustophoretic Motion of Microparticles in Three Dimensions. Phys. Rev. E 2013, 88, 023006. (43) Karlsen, J. T.; Bruus, H. Forces Acting on a Small Particle in an Acoustical Field in a

Thermoviscous Fluid. Phys. Rev. E 2015, 92, 043010. (44) Tang, Q.; Hu, J. Diversity of Acoustic Streaming in a Rectangular Acoustofluidic Field.

Ultrasonics 2015, 58, 27-34. (45) Lu, X.; Hu, J.; Yang, L.; Zhao, C. A Novel Dual Stator-Ring Rotary Ultrasonic Motor.

Sens. Actuators, A 2013, 189, 504-511. (46) Cervenka, M.; Bednarik, M. Variety of Acoustic Streaming in 2D Resonant Channels.

Wave Motion 2016, 66, 21-30. (47) Li, J.; Esteban-Fernandez de Avila, B.; Gao, W.; Zhang, L.; Wang, J. Micro/Nanorobots

for Biomedicine: Delivery, Surgery, Sensing, and Detoxification. Sci. Robot. 2017, 2, eaam6431. (48) Esteban-Fernandez de Avila, B.; Angell, C.; Soto, F.; Lopez-Ramirez, M. A.; Baez, D. F.;

Xie, S.; Wang, J.; Chen, Y. Acoustically Propelled Nanomotors for Intracellular siRNA Delivery. ACS Nano 2016, 10, 4997-5005. (49) Esteban-Fernandez de Avila, B.; Ramirez-Herrera, D. E.; Campuzano, S.; Angsantikul,

P.; Zhang, L.; Wang, J. Nanomotor-Enabled pH-Responsive Intracellular Delivery of Caspase-3: Towards Rapid Cell Apoptosis. ACS Nano 2017, 11, 5367-5374. (50) Martin, A.; Jurado-Sanchez, B.; Escarpa, A.; Wang, J. Template Electrosynthesis of

High-Performance Graphene Microengines. Small 2015, 11, 3568-3574. (51) Jodra, A.; Soto, F.; Lopez-Ramirez, M. A.; Escarpa, A.; Wang, J. Delayed Ignition and

Propulsion of Catalytic Microrockets Based on Fuel-induced Chemical Dealloying of the Inner Alloy Layer. Chem. Comm. 2016, 52, 11838-11841. (52) Walther, A.; Muller, A. H. E. Janus Particles. Soft Matter. 2008, 4, 663-668. (53) Baraban, L.; Tasinkevych, M.; Popescu, M. N.; Sanchez, S.; Dietrich, S.; Schmidt, O. G. 17



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Transport of Cargo by Catalytic Janus Micro-Motors. Soft Matter. 2012, 8, 48-52. (54) Gao, W.; Pei, A.; Feng, X.; Hennessy, C.; Wang, J. Organized Self-Assembly of Janus

Micromotors with Hydrophobic Hemispheres. J. Am. Chem. Soc. 2013, 135, 998-1001.

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Topographical Manipulation of Microparticles and Cells with Acoustic

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