scholarly journals A review of digital microfluidics as portable platforms for lab-on a-chip applications

Lab on a Chip ◽  
2016 ◽  
Vol 16 (13) ◽  
pp. 2376-2396 ◽  
Author(s):  
Ehsan Samiei ◽  
Maryam Tabrizian ◽  
Mina Hoorfar
Keyword(s):  
Digital Microfluidics ◽  
Lab On A Chip ◽  
Microfluidic Platforms ◽  
Digital Microfluidic

This review evaluates the possibility of developing portable digital microfluidic platforms for lab-on-a-chip applications.

Effect of Electrode Geometry on Droplet Splitting in Digital Microfluidic Platforms

2014 ◽  
Author(s):  
Ehsan Samiei ◽  
Hojatollah Rezaei Nejad ◽  
Mina Hoorfar
Keyword(s):  
Aspect Ratio ◽  
Threshold Voltage ◽  
Digital Microfluidics ◽  
Nonlinear Behavior ◽  
Electrode Geometry ◽  
Microfluidic Platforms ◽  
Minimum Threshold ◽  
Aspect Ratios ◽  
Droplet Splitting ◽  
Digital Microfluidic

This paper studies the effect of the electrode aspect ratio on droplet splitting in a digital microfluidics (DMF) chip including an array of 3 electrodes in which the middle electrode is kept square while the two side electrodes have different aspect ratios. The aspect ratio is changed from 0.9 to 1.3 while the surface area of the electrodes is kept constant for all cases. Results show that changing the aspect ratio can severely change the required voltage for splitting with a nonlinear behavior. It is also shown that for a constant gap between the top and bottom plates and a constant volume of the droplet, the relation between the threshold voltage and the aspect ratio is parabolic, for which there is an aspect ratio with a minimum threshold voltage. Changing the volume of the droplet changes the threshold voltage and hence the aspect ratio corresponding to the minimum threshold voltage required for splitting.

scholarly journals Enhanced Solutal Marangoni Flow Using Ultrasound-Induced Heating for Rapid Digital Microfluidic Mixing

2021 ◽  
Vol 9 ◽  
Author(s):  
Beomseok Cha ◽  
Woohyuk Kim ◽  
Giseong Yoon ◽  
Hyunwoo Jeon ◽  
Jinsoo Park
Keyword(s):  
Digital Microfluidics ◽  
Marangoni Effect ◽  
Marangoni Flow ◽  
Sessile Droplet ◽  
Microfluidic Platforms ◽  
Volatile Liquid ◽  
Mixing Method ◽  
Absorbing Layer ◽  
Digital Microfluidic ◽  
Marangoni Flows

Digital microfluidics based on sessile droplets has emerged as a promising technology for various applications including biochemical assays, clinical diagnostics, and drug screening. Digital microfluidic platforms provide an isolated microenvironment to prevent cross-contamination and require reduced sample volume. Despite these advantages, the droplet-based technology has the inherent limitation of the quiescent flow conditions at low Reynolds number, which causes mixing samples confined within the droplets to be challenging. Recently, solutal Marangoni flows induced by volatile liquids have been utilized for sessile droplet mixing to address the above-mentioned limitation. The volatile liquid vaporized near a sessile droplet induces a surface tension gradient throughout the droplet interface, leading to vortical flows inside a droplet. This Marangoni flow-based droplet mixing method does not require an external energy source and is easy to operate. However, this passive method requires a comparably long time of a few tens of seconds for complete mixing since it depends on the natural evaporation of the volatile liquid. Here, we propose an improved ultrasound-induced heating method based on a nature-inspired ultrasound-absorbing layer and apply it to enhance solutal Marangoni effect. The heater consists of an interdigital transducer deposited on a piezoelectric substrate and a silver nanowire-polydimethylsiloxane composite as an ultrasound-absorbing layer. When the transducer is electrically actuated, surface acoustic waves are produced and immediately absorbed in the composite layer by viscoelastic wave attenuation. The conversion from acoustic to thermal energy occurs, leading to rapid heating. The heating-mediated enhanced vaporization of a volatile liquid accelerates the solutal Marangoni flows and thus enables mixing high-viscosity droplets, which is unachievable by the passive solutal Marangoni effect. We theoretically and experimentally investigated the enhanced Marangoni flow and confirmed that rapid droplet mixing can be achieved within a few seconds. The proposed heater-embedded sessile droplet mixing platform can be fabricated in small size and easily integrated with other digital microfluidic platforms. Therefore, we expect that the proposed sample mixing method can be utilized for various applications in digital microfluidics and contribute to the advancements in the medical and biochemical fields.

Efficient One-pass Synthesis for Digital Microfluidic Biochips

2021 ◽  
Vol 26 (4) ◽  
pp. 1-21
Author(s):  
Naser Mohammadzadeh ◽  
Robert Wille ◽  
Oliver Keszocze
Keyword(s):  
Digital Microfluidics ◽  
Lab On A Chip ◽  
Holistic Approach ◽  
Emerging Technology ◽  
Computational Effort ◽  
Synthesis Process ◽  
Pass Design ◽  
Placement And Routing ◽  
Digital Microfluidic ◽  
Individual Design

Digital microfluidics biochips are a promising emerging technology that provides fluidic experimental capabilities on a chip (i.e., following the lab-on-a-chip paradigm). However, the design of such biochips still constitutes a challenging task that is usually tackled by multiple individual design steps, such as binding, scheduling, placement, and routing. Performing these steps consecutively may lead to design gaps and infeasible results. To address these shortcomings, the concept of one-pass design for digital microfluidics biochips has recently been proposed—a holistic approach avoiding the design gaps by considering the whole synthesis process as large. But implementations of this concept available thus far suffer from either high computational effort or costly results. In this article, we present an efficient one-pass solution that is runtime efficient (i.e., rarely needing more than a second to successfully synthesize a design) while, at the same time, producing better results than previously published heuristic approaches. Experimental results confirm the benefits of the proposed solution and allow for realizing really large assays composed of thousands of operations in reasonable runtime.

Magnetic Digital Microfluidics for Point-of-Care Testing: Where Are We Now?

2020 ◽  
Vol 27 ◽  
Author(s):  
Yi Zhang
Keyword(s):  
System Integration ◽  
Diagnostic Tests ◽  
Point Of Care ◽  
Digital Microfluidics ◽  
Controlled Environment ◽  
Point Of Care Testing ◽  
Microfluidic Platforms ◽  
Interface System ◽  
Technical Issues ◽  
Sample System

: Point-of-care (POC) testing decentralizes the diagnostic tests to the sites near the patient. Many POC tests rely microfluidic platforms for sample-to-answer analysis. Compared to other microfluidic systems, magnetic digital microfluidics demonstrate compelling advantages for POC diagnostics. In this review, we have examined the capability of magnetic digital microfluidics-based POC diagnostic platforms. More importantly, we have categorized POC settings into three classes based on “where is the point”, “who to care” and “how to test”, and evaluated the suitability of magnetic digital microfluidics in various POC settings. Furthermore, we have addressed other technical issues associated with POC testing such as controlled environment, sample-system interface, system integration and information connectivity. We hope this review would provide a guideline for the future development of magnetic digital microfluidics-based platforms for POC testing.

scholarly journals Machine Learning Model of Dimensionless Numbers to Predict Flow Patterns and Droplet Characteristics for Two-Phase Digital Flows

2021 ◽  
Vol 11 (9) ◽  
pp. 4251
Author(s):  
Jinsong Zhang ◽  
Shuai Zhang ◽  
Jianhua Zhang ◽  
Zhiliang Wang
Keyword(s):  
Machine Learning ◽  
Learning Algorithms ◽  
Digital Microfluidics ◽  
Flow Patterns ◽  
Machine Learning Algorithms ◽  
Dimensionless Numbers ◽  
Two Phase ◽  
The Difference ◽  
Input Variables ◽  
Digital Microfluidic

In the digital microfluidic experiments, the droplet characteristics and flow patterns are generally identified and predicted by the empirical methods, which are difficult to process a large amount of data mining. In addition, due to the existence of inevitable human invention, the inconsistent judgment standards make the comparison between different experiments cumbersome and almost impossible. In this paper, we tried to use machine learning to build algorithms that could automatically identify, judge, and predict flow patterns and droplet characteristics, so that the empirical judgment was transferred to be an intelligent process. The difference on the usual machine learning algorithms, a generalized variable system was introduced to describe the different geometry configurations of the digital microfluidics. Specifically, Buckingham’s theorem had been adopted to obtain multiple groups of dimensionless numbers as the input variables of machine learning algorithms. Through the verification of the algorithms, the SVM and BPNN algorithms had classified and predicted the different flow patterns and droplet characteristics (the length and frequency) successfully. By comparing with the primitive parameters system, the dimensionless numbers system was superior in the predictive capability. The traditional dimensionless numbers selected for the machine learning algorithms should have physical meanings strongly rather than mathematical meanings. The machine learning algorithms applying the dimensionless numbers had declined the dimensionality of the system and the amount of computation and not lose the information of primitive parameters.

A Framework for Validation of Synthesized MicroElectrode Dot Array Actuations for Digital Microfluidic Biochips

2021 ◽  
Vol 26 (6) ◽  
pp. 1-36
Author(s):  
Pushpita Roy ◽  
Ansuman Banerjee
Keyword(s):  
Formal Analysis ◽  
Digital Microfluidics ◽  
Analysis Method ◽  
Correctness Proofs ◽  
Synthesis Tool ◽  
Laboratory Procedures ◽  
Automated Tools ◽  
Digital Microfluidic ◽  
High Level ◽  
Smooth Transformation

Digital Microfluidics is an emerging technology for automating laboratory procedures in biochemistry. With more and more complex biochemical protocols getting mapped to biochip devices and microfluidics receiving a wide adoption, it is becoming indispensable to develop automated tools and synthesis platforms that can enable a smooth transformation from complex cumbersome benchtop laboratory procedures to biochip execution. Given an informal/semi-formal assay description and a target microfluidic grid architecture on which the assay has to be implemented, a synthesis tool typically translates the high-level assay operations to low-level actuation sequences that can drive the assay realization on the grid. With more and more complex biochemical assay protocols being taken up for synthesis and biochips supporting a wider variety of operations (e.g., MicroElectrode Dot Arrays (MEDAs)), the task of assay synthesis is getting intricately complex. Errors in the synthesized assay descriptions may have undesirable consequences in assay operations, leading to unacceptable outcomes after execution on the biochips. In this work, we focus on the challenge of examining the correctness of synthesized protocol descriptions, before they are taken up for realization on a microfluidic biochip. In particular, we take up a protocol description synthesized for a MEDA biochip and adopt a formal analysis method to derive correctness proofs or a violation thereof, pointing to the exact operation in the erroneous translation. We present experimental results on a few bioassay protocols and show the utility of our framework for verifiable protocol synthesis.

Digital microfluidics using a differentially polarized interface (DPI) to enhance translational force

Lab on a Chip ◽  
2018 ◽  
Vol 18 (21) ◽  
pp. 3293-3302 ◽  
Author(s):  
Md Enayet Razu ◽  
Jungkyu Kim
Keyword(s):  
Low Voltage ◽  
Digital Microfluidics ◽  
Microfluidic Platform ◽  
Digital Microfluidic

A low-voltage and differentially polarized digital microfluidic platform is developed by enhancing the electromechanical force for droplet translation.

Digital microfluidics and nuclear magnetic resonance spectroscopy for in situ diffusion measurements and reaction monitoring

Lab on a Chip ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 641-653 ◽  
Author(s):  
Ian Swyer ◽  
Sebastian von der Ecken ◽  
Bing Wu ◽  
Amy Jenne ◽  
Ronald Soong ◽  
...  
Keyword(s):  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Magnetic Resonance Spectroscopy ◽  
Nuclear Magnetic Resonance Spectroscopy ◽  
Digital Microfluidics ◽  
Resonance Spectroscopy ◽  
Reaction Monitoring ◽  
Digital Microfluidic ◽  
Nuclear Magnetic

We describe a two-plate digital microfluidic method for interfacing with nuclear magnetic resonance spectroscopy (DMF-NMR) for microscale chemical analysis.

scholarly journals Phase separation of multiphase droplets in a digital microfluidic device

2019 ◽  
Vol 7 (1) ◽  
Author(s):  
Mun Mun Nahar ◽  
Hyejin Moon
Keyword(s):  
Phase Separation ◽  
Capillary Number ◽  
Digital Microfluidics ◽  
Separation Performance ◽  
Comprehensive Investigation ◽  
Electrowetting On Dielectric ◽  
Splitting Technique ◽  
Droplet Splitting ◽  
Two Phases ◽  
Digital Microfluidic

Abstract This study reports the first comprehensive investigation of separation of the immiscible phases of multiphase droplets in digital microfluidics (DMF) platform. Electrowetting-on-dielectric (EWOD) actuation has been used to mechanically separate the phases. Phase separation performance in terms of percentage residue of one phase into another phase has been quantified. It was conceived that the residue formation can be controlled by controlling the deformation of the phases. The larger capillary number of the neck forming phase is associated with the larger amount of deformation as well as more residue. In this study, we propose two different ways to control the deformation of the phases. In the first method, we applied different EWOD operation voltages on two phases to maintain equal capillary numbers during phase separation. In the second method, while keeping the applied voltages same on both sides, we tested the phase separation performance by varying the actuation schemes. Less than 2% of residue was achieved by both methods, which is almost 90% improvement compared to the phase separation by the conventional droplet splitting technique in EWOD DMF platform, where the residue percentage can go up to 20%.

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