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Acousto-Pi: An Opto-Acoustofluidic System Using Surface Acoustic Waves Controlled with Open-Source Electronics for Integrated In-Field Diagnostics

  • Jethro Vernon
  • , Pep Canyelles-Pericas
  • , Hamdi Torun
  • , Xuewu Dai
  • , Wai Pang Ng
  • , Richard Binns
  • , Krishna Busawon
  • , Yong Qing Fu*
  • *Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

103 Downloads (Pure)

Abstract

Surface acoustic wave (SAW) devices are increasingly applied in life sciences, biology, and point-of-care applications due to their combined acoustofluidic sensing and actuating properties. Despite the advances in this field, there remain significant gaps in interfacing hardware and control strategies to facilitate system integration with high performance and low cost. In this work, we present a versatile and digitally controlled acoustofluidic platform by demonstrating key functions for biological assays such as droplet transportation and mixing using a closed-loop feedback control with image recognition. Moreover, we integrate optical detection by demonstrating in situ fluorescence sensing capabilities with a standard camera and digital filters, bypassing the need for expensive and complex optical setups. The Acousto-Pi setup is based on open-source Raspberry Pi hardware and 3-D printed housing, and the SAW devices are fabricated with piezoelectric thin films on a metallic substrate. The platform enables the control of droplet position and speed for sample processing (mixing and dilution of samples), as well as the control of temperature based on acousto-heating, offering embedded processing capability. It can be operated remotely while recording the measurements in cloud databases toward integrated in-field diagnostic applications such as disease outbreak control, mass healthcare screening, and food safety.

Original languageEnglish
Pages (from-to)411-422
Number of pages12
JournalIEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
Volume69
Issue number1
DOIs
Publication statusPublished - 1 Jan 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Feedback control
  • Fluorescence imagining
  • Integrated acoustofluidics
  • Open-source electronics
  • Piezoelectric thin film
  • Point-Of-Care (POC) diagnostics
  • Surface Acoustic Waves (SAWs)

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