Contactless Acoustic Manipulation and Sorting of Particles by Dynamic Acoustic Fields

Andrade, Marco A. B.; Skotis, G. D.; Ritchie, Scott A.; Cumming, David R. S.; Riehle, Mathis O.; Bernassau, A.L.

doi:10.1109/tuffc.2016.2608759

Cited by 15 publications

(5 citation statements)

References 31 publications

(45 reference statements)

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“…Shi et al first used SAWs to separate 4.16 µm particles with an efficiency of 80% [144]. Andrade et al showed that particle separation could be achieved by modulating the relative phase between the ultrasound transducers [145]. This method was capable of discriminating particles of different sizes from a mixture, even when this difference was relatively small.…”

Section: Cell Transportationmentioning

confidence: 99%

Acoustic tweezers

Meng¹,

Cai²,

Li³

et al. 2019

J. Phys. D: Appl. Phys.

136

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Acoustic tweezers are gaining increasing attention as a noncontact method that is capable of handling microparticles and nanoparticles in a controllable manner. By designing the acoustic field, objects, such as cells, bacteria, exosomes, and even worms, could be precisely and flexibly manipulated by the acoustic radiation force. With the advantages of non-invasiveness, label-free operation, and low power consumption, acoustic tweezers have been proven to be crucially important for a diverse range of applications, particularly in the biomedical domain. In this paper, we review the historical development and the current state of the theory of the acoustic radiation force. Furthermore, we introduce recent advancements in acoustic tweezers based on the standing wave, travelling wave, single beam, and arbitrary wave fields; its mechanism and potential applications are also presented. Finally, some perspectives referring to the future development of acoustic tweezers are discussed.

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Section: Cell Transportationmentioning

confidence: 99%

Acoustic tweezers

Meng¹,

Cai²,

Li³

et al. 2019

J. Phys. D: Appl. Phys.

136

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show abstract

“…This interplay of forces induces different trajectories on different particles, and leads, under suitable conditions, to particle fractionation. 20,67 In a system where particles agglomerate at the acoustic nodes, only the large particles experience a strong enough acoustic force and will follow the nodes shifting via the modification in phase. Figure 2 shows two phase modulated signals that are used to separate particles by size.…”

Section: B Phase-modulated Waveform For Particle Separationmentioning

confidence: 99%

Particle separation by phase modulated surface acoustic waves

et al. 2017

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High efficiency isolation of cells or particles from a heterogeneous mixture is a critical processing step in lab-on-a-chip devices. Acoustic techniques offer contactless and label-free manipulation, preserve viability of biological cells, and provide versatility as the applied electrical signal can be adapted to various scenarios. Conventional acoustic separation methods use time-of-flight and achieve separation up to distances of quarter wavelength with limited separation power due to slow gradients in the force. The method proposed here allows separation by half of the wavelength and can be extended by repeating the modulation pattern and can ensure maximum force acting on the particles. In this work, we propose an optimised phase modulation scheme for particle separation in a surface acoustic wave microfluidic device. An expression for the acoustic radiation force arising from the interaction between acoustic waves in the fluid was derived. We demonstrated, for the first time, that the expression of the acoustic radiation force differs in surface acoustic wave and bulk devices, due to the presence of a geometric scaling factor. Two phase modulation schemes are investigated theoretically and experimentally. Theoretical findings were experimentally validated for different mixtures of polystyrene particles confirming that the method offers high selectivity. A Monte-Carlo simulation enabled us to assess performance in real situations, including the effects of particle size variation and non-uniform acoustic field on sorting efficiency and purity, validating the ability to separate particles with high purity and high resolution.

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“…Mass is a fundamental physical quantity that can provide important information about the properties of an object [1]. Generally, measuring the mass of levitated objects in the micron to millimeter range requires placement in a standard laboratory container such as a vial, measuring spoon, or scale [2,3]. However, this method is subject to some limitations.…”

Section: Introductionmentioning

confidence: 99%

Contactless weighing method based on deep learning and acoustic levitation

Wang,

Jiang,

Chen

et al. 2024

Meas. Sci. Technol.

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Acoustic weighing is a promising contactless method for screening the mass of micro-nano objects as it avoids contact contamination and losses. Existing acoustic weighing methods determine the mass of an object by detecting its oscillation trajectory with a laser sensor. However, this method suffers from several limitations, such as short measurement distance, poor accuracy in measuring transparent objects, and inducing damage to photosensitive samples. To solve these issues, this work proposes a contactless weighing method based on location-aware neural network (LANet) and acoustic levitation. The proposed LANet is a deep learning-based image processing method that detects object bit oscillation trajectories completely contactless, regardless of the color, shape, and oscillation distance of the levitated object. We employ a cross-stage aggregation module and cross-mixed feature pyramid strategy to build LANet network depth for enhanced feature extraction. In addition, to create a contactless environment, we built an acoustic levitation system, which drives the oscillation of objects. Finally, we verified the accuracy and effectiveness of the method. The results show that the proposed network can accurately detect the oscillation trajectories of various objects with high detection performance, even for small objects in low-contrast backgrounds. Meanwhile, the proposed method can accurately measure the mass of objects with a percentage error of no more than 7.83%.

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Contactless Acoustic Manipulation and Sorting of Particles by Dynamic Acoustic Fields

Cited by 15 publications

References 31 publications

Acoustic tweezers

Acoustic tweezers

Particle separation by phase modulated surface acoustic waves

Contactless weighing method based on deep learning and acoustic levitation

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