scholarly journals Digital Microfluidics: Paper-Based Digital Microfluidic Chip for Multiple Electrochemical Assay Operated by a Wireless Portable Control System (Adv. Mater. Technol. 3/2017)

2017 ◽  
Vol 2 (3) ◽  
Author(s):  
Nipapan Ruecha ◽  
Jumi Lee ◽  
Heedo Chae ◽  
Haena Cheong ◽  
Veasna Soum ◽  
...  
Keyword(s):  
Control System ◽  
Microfluidic Chip ◽  
Digital Microfluidics ◽  
Electrochemical Assay ◽  
Digital Microfluidic

Paper-Based Digital Microfluidic Chip for Multiple Electrochemical Assay Operated by a Wireless Portable Control System

2017 ◽  
Vol 2 (3) ◽  
pp. 1600267 ◽  
Author(s):  
Nipapan Ruecha ◽  
Jumi Lee ◽  
Heedo Chae ◽  
Haena Cheong ◽  
Veasna Soum ◽  
...  
Keyword(s):  
Control System ◽  
Microfluidic Chip ◽  
Electrochemical Assay ◽  
Digital Microfluidic

Numerical Simulation of Multi-Physical Fields Coupling and Design of a Digital Microfluidics Chip

2012 ◽  
Vol 503 ◽  
pp. 359-365 ◽  
Author(s):  
Tao Chen ◽  
Li Guo Chen ◽  
Ming Qiang Pan ◽  
Ming Xiang Ling ◽  
Li Ning Sun
Keyword(s):  
Numerical Simulation ◽  
Electric Field ◽  
Microfluidic Chip ◽  
Stokes Equations ◽  
Driving Forces ◽  
Geometric Model ◽  
Digital Microfluidics ◽  
Electrowetting On Dielectric ◽  
Physical Fields ◽  
Digital Microfluidic

Due to its simple structure, low consumption of energy but strong driving forces, Electrowetting on Dielectric (EWOD) is used most frequently in digital microfluidics for manipulation and control of droplets. In this paper, the internal mechanism of EWOD is explained though establishing the geometric model of the unipolar board structure digital microfluidic chip. And the boundary conditions of equations are determined. Three coupling physical fields: electric field, flow field and temperature field in the digital microfluidic chip are simulated and analyzed. With the electric field equation coupled, Navier-Stokes equations and energy equation of the temperature control, the numerical simulation of the chip is conducted. The results show that the internal flow of micro-droplets is counterclockwise and swirling flow. The external flow velocity of micro-droplet is greater than the internal velocity. In addition, micro-droplets near the electrode applied temperature are higher than the internal temperature. Surface micromachining technologies are employed to fabricate the chip. Experimental results show that the droplet can be driven in a velocity of 25cm/s. It will possibly provide an effective solution to the manipulation of droplets.

Drop driving on digital microfluidic chip

2020 ◽  
Vol 28 (11) ◽  
pp. 2488-2496
Author(s):  
Hong WANG ◽  
◽  
Jie ZHENG ◽  
Yan-peng YAN ◽  
Song WANG ◽  
...  
Keyword(s):  
Microfluidic Chip ◽  
Digital Microfluidic

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.

An integrated digital microfluidic chip for multiplexed proteomic sample preparation and analysis by MALDI-MS

Lab on a Chip ◽  
2006 ◽  
Vol 6 (9) ◽  
pp. 1213 ◽  
Author(s):  
Hyejin Moon ◽  
Aaron R. Wheeler ◽  
Robin L. Garrell ◽  
Joseph A. Loo ◽  
Chang-Jin ?CJ? Kim
Keyword(s):  
Sample Preparation ◽  
Microfluidic Chip ◽  
Maldi Ms ◽  
Digital Microfluidic

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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