Droplet Size-Aware and Error-Correcting Sample Preparation Using Micro-Electrode-Dot-Array Digital Microfluidic Biochips

Zipeng Li*, Kelvin Yi Tse Lai, Krishnendu Chakrabarty, Tsung Yi Ho, Chen-Yi Lee

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Sample preparation in digital microfluidics refers to the generation of droplets with target concentrations for on-chip biochemical applications. In recent years, digital microfluidic biochips (DMFBs) have been adopted as a platform for sample preparation. However, there remain two major problems associated with sample preparation on a conventional DMFB. First, only a (1:1) mixing/splitting model can be used, leading to an increase in the number of fluidic operations required for sample preparation. Second, only a limited number of sensors can be integrated on a conventional DMFB; as a result, the latency for error detection during sample preparation is significant. To overcome these drawbacks, we adopt a next generation DMFB platform, referred to as micro-electrode-dot-array (MEDA), for sample preparation. We propose the first sample-preparation method that exploits the MEDA-specific advantages of fine-grained control of droplet sizes and real-time droplet sensing. Experimental demonstration using a fabricated MEDA biochip and simulation results highlight the effectiveness of the proposed sample-preparation method.

Original languageEnglish
Article number8053917
Pages (from-to)1380-1391
Number of pages12
JournalIEEE Transactions on Biomedical Circuits and Systems
Volume11
Issue number6
DOIs
StatePublished - 1 Dec 2017

Keywords

  • Digital mirofluidics
  • error recovery
  • micro-electrode-dot-array
  • optimization algorithm
  • sample preparation

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