A digital microfluidic device with integrated nanostructured microelectrodes for electrochemical immunoassays

Lab on a Chip ◽  
2015 ◽  
Vol 15 (18) ◽  
pp. 3776-3784 ◽  
Author(s):  
Darius G. Rackus ◽  
Michael D. M. Dryden ◽  
Julian Lamanna ◽  
Alexandre Zaragoza ◽  
Brian Lam ◽  
...  
Keyword(s):  
Microfluidic Device ◽  
Digital Microfluidics ◽  
Digital Microfluidic ◽  
Electrochemical Immunoassays

Nanostructured microelectrodes (NMEs) combined with digital microfluidics (DMF) for automated electroimmunoassays.

A droplet-to-digital (D2D) microfluidic device for single cell assays

Lab on a Chip ◽  
2015 ◽  
Vol 15 (1) ◽  
pp. 225-236 ◽  
Author(s):  
Steve C. C. Shih ◽  
Philip C. Gach ◽  
Jess Sustarich ◽  
Blake A. Simmons ◽  
Paul D. Adams ◽  
...  
Keyword(s):  
Single Cell ◽  
Microfluidic Device ◽  
Digital Microfluidics ◽  
Microfluidic Platform ◽  
Cell Assays ◽  
Digital Microfluidic

We have developed a new hybrid droplet-to-digital microfluidic platform (D2D) that integrates droplet-in-channel microfluidics with digital microfluidics for performing multi-step single cell assays.

Method for Characterization of Passive Mechanical Filtration of Particles in Digital Microfluidic Devices

2014 ◽  
Author(s):  
Peter D. Dunning ◽  
Pierre E. Sullivan ◽  
Michael J. Schertzer
Keyword(s):  
Microfluidic Device ◽  
Vision System ◽  
Low Cost ◽  
Digital Microfluidics ◽  
Microfluidic Devices ◽  
Comb Filter ◽  
Enzyme Linked Immunosorbent Assay ◽  
Reaction Site ◽  
Digital Microfluidic

The ability to remove unbound biological material from a reaction site has applications in many biological protocols, such as those used to detect pathogens and biomarkers. One specific application where washing is critical is the Enzyme-Linked ImmunoSorbent Assay (ELISA). This protocol requires multiple washing steps to remove multiple reagents from a reaction site. Previous work has suggested that a passive mechanical comb filter can be used to wash particles in digital microfluidic devices. A method for the characterization of passive mechanical filtration of particles in Digital MicroFluidic (DMF) devices is presented in this work. In recent years there has been increased development of Lab-On-A-Chip (LOAC) devices for the automation and miniaturization of biological protocols. One platform for further research is in digital microfluidics. A digital microfluidic device can control the movement of pico-to nanoliter droplets of fluid using electrical signals without the use of pumps, valves, and channels. As such, fluidic pathways are not hardwired and the path of each droplet can be easily reconfigured. This is advantageous in biological protocols requiring the use of multiple reagents. Fabrication of these devices is relatively straight forward, since fluid manipulation is possible without the use of complex components. This work presents a method to characterize the performance of a digital microfluidic device using passive mechanical supernatant dilution via image analysis using a low cost vision system. The primary metric for performance of the device is particle retention after multiple passes through the filter. Repeatability of the process will be examined by characterizing performance of multiple devices using the same filter geometry. Qualitative data on repeatability and effectiveness of the dilution technique will also be attained by observing the ease with which the droplet disengages from the filter and by measuring the quantity of fluid trapped on the filter after each filtration step.

Analytical Models to Determine the Electric Field Characteristics of a Multi-Electrode Impedimetric Immunosensor in a Digital Microfluidic Device

2014 ◽  
Author(s):  
Steffen O. P. Blume ◽  
Michael J. Schertzer ◽  
Ridha Ben Mrad ◽  
Pierre E. Sullivan
Keyword(s):  
Microfluidic Device ◽  
Digital Microfluidics ◽  
Electrode Array ◽  
Analytical Models ◽  
Element Analysis ◽  
Numerical Simulation Methods ◽  
Mapping Techniques ◽  
On Chip ◽  
Digital Microfluidic ◽  
Impedimetric Immunosensor

The level of integration of digital microfluidics is continually increasing to include the system path from fluid manipulation and transport, on to reagent preparation, and finally reaction detection. Digital microfluidics therefore has the capability to encompass all steps of common biochemical protocols. Reported here is a set of analytical models for the design of a coplanar interdigitated multi-electrode array to be used as an impedimetric immunosensor in a digital microfluidic device for on-chip chemical reaction detection. The models are based on conformal mapping techniques, and are compared to results obtained from finite element analysis to discuss limitations of the model. The analytical models are feasible and inexpensive surrogates for numerical simulation methods.

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 Microfluidic Device for Mixing Organic Droplets

2020 ◽  
Vol 49 (3) ◽  
pp. 284-286
Author(s):  
Hirotada Hirama ◽  
Takahiro Iida ◽  
Yusuke Komazaki ◽  
Toru Torii ◽  
Harutaka Mekaru
Keyword(s):  
Microfluidic Device ◽  
Digital Microfluidic

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.

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