Acoustofluidic Trapping in Structured Microchannels Using Lateral Transducer Modes

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Abstract

Acoustofluidic particle trapping in a circular resonant cavity in a microfluidic channel was performed using a lateral mode of two equal piezoceramic plate transducers. In order to achieve two-dimensional particle focusing in the cavity, the transducers were mounted to the chip with a 90° tilt with respect to each other, so that each transducer is responsible for generating a standing wave either in the longitudinal or transversal direction with respect to the channel axis. The chip has multiple cavities with different diameters and thus different eigenfrequencies, which are arranged consecutively along a microfluidic channel. It was intended to trap particles dependent on the actuation frequencies at the corresponding resonant cavities. In the experiments described in this work trapping was only observed in one cavity, whose eigenfrequency matched the lateral transducer resonance. Due to low field intensity generated by the transducer, when driven off a resonance, particle trapping was not possible in the other cavities. Besides the cavity-trapping, we also found particle trapping within the channel sections connecting the individual cavities. By superposing a standing wave along the channel and a second one transversal to it, we achieved two-dimensional multi-nodal focusing here. We believe that the cavities partially act as acoustic reflectors thus supporting the formation of standing waves along the channel sections at certain frequencies. This phenomenon is not observed in this intensity in a straight channel without cavities.
Original languageEnglish
Title of host publicationProc. of IEEE Sensors 2023
Number of pages4
Publication statusPublished - 2023

Fields of science

  • 202019 High frequency engineering
  • 202021 Industrial electronics
  • 202036 Sensor systems
  • 203017 Micromechanics
  • 202 Electrical Engineering, Electronics, Information Engineering
  • 202027 Mechatronics
  • 202028 Microelectronics
  • 202037 Signal processing
  • 502058 Digital transformation

JKU Focus areas

  • Digital Transformation

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