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About Us

Research in our lab spans the areas of microfluidics, lab-on-chip, bioMEMS, and bioelectronics for medical applications. The common theme in our projects is instrumentation for obtaining diagnostic data from biological systems, from the level of molecules and cells (for example, digital assays) to the level of the individual (for example, wearable sensors). We are motivated by the premise that more data improves our understanding of life, and can help us make better decisions about our health and environment. Current projects involve two thrusts:

Multiphase Microfluidics for High-Throughput Biology

Modern biological research relies on high-throughput screening (HTS) instruments which can perform assays involving large numbers biomolecules or cells. These instruments must be able achieve high speed, low cost, and minimal reagent consumption. Particularly well suited for HTS is a class of microfluidic devices which utilizes water-in-oil droplets as chemical reaction containers. With typical dimensions of <100 micrometers and with volumes on the order of nanoliters to femtoliters, droplet systems have the potential to manage large libraries of chemical reactions while consuming minimal amounts of reagents. Droplet systems have been widely used for modern methods of digital PCR, single cell assays, chemical fractionation, and more. Our work in this area focuses on the physics and applications of multiphase flow and interfacial phenomena, the manipulation and storage of droplets, and label-free biodetection. Applications of these devices include digital assays, including single molecule, single cell, and single organism screening.

Wearable and portable microelectronics for health and environmental monitoring

Microelectronics and microsensors have become pervasive in the modern age, creating a significant opportunity for their use in portable, wearable bioinstruments for distributed and home health monitoring. We are motivated by the use of these devices to help manage chronic disease, which accounts for >65% of US health care costs. Our work in this area takes a translational approach, focused on developing systems to serve needs in healthcare as well as environmental applications. Current projects include ultraminiature wearable biosensors for fitness and stress monitoring, portable biodetection systems for detecting invasive species in foreign vessels entering the Great Lakes, and multiplexed electronics for portable flow cytometry systems.

Sponsors

We are grateful for research funding from the following agencies. NSF disclaimer: Some of our work is supported by the National Science Foundation. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the NSF.

Microfluidics for high-throughput biology

Modern biological research, including the areas of '-omics' and systems biology, relies on high-throughput screening (HTS) instruments which can perform assays involving large number biomolecules or cells. These instruments must be able to do so with high speed, low cost, and minimal reagent consumption. Particularly suited for HTS is a class of microfluidic devices which utilizes water-in-oil droplets as chemical reaction containers. With typical dimensions of <100 micrometers and with volumes on the order of nanoliters to femtoliters, droplet systems have the potential to manage large libraries of chemical reactions while consuming minimal amounts of reagents. Our work in this area focuses on the physics of multiphase flow, the manipulation of droplets using interfacial phenomena, and label-free biodetection.

Wearable and portable microelectronics for health and environmental monitoring

Microelectronics have become pervasive in the information age, creating a significant opportunity for portable, wearable bioinstruments for continuous monitoring. Our work in this area takes a translational approach, focused on developing systems to serve needs in healthcare, environmental, and biological applications. Current projects include ultraminiature wearable biosensors for fitness and stress monitoring, portable biodetection systems for detecting invasive species in foreign vessels entering the Great Lakes, optical microplates for photonic screening of algae, and high-speed electronics for multiplexed flow cytometry.

Selected Research Projects


Cell

Accelerated Imaging Flow Cytometry

A. Vedhanayagam

In this project we perform rapid image-based flow cytometry utilizing GPU-Accelerated computer vision and machine learning. Our systems are designed to meet the throughput demands of liquid biopsy and environmental screening.


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GPU-Accelerated Imaging Flow Cytometry and Sorting

One of the rapidly growing applications of artificial intelligence and machine learning is using computer vision to classify biomedical images. In this project, we are utilizing (GPU) hardware-accelerated computer vision and neural networks to recognize and sort cancer cells in human blood, paving the way towards the so-called 'liquid biopsy' in cancer diagnostics. A modified version of the system can be used for rapid identification of environmental contaminants such as microplastics.

References

  1. A. Vedhanayagam and A.S. Basu, "Flow Focus-Free Image Flow Cytometry by Image Processing and Data Estimation," Micro Total Analysis Systems, October 2020.
  2. A. Vedhanayagam and A.S. Basu, "Real Time Tracking of Particles at >1,200 events per second using GPU-Accelerated Image Processing," Micro Total Analysis Systems, October 2020.
  3. A. Vedhanayagam and A.S. Basu, "Imaging Flow Cytometry at >13K events/s Using GPU-Accelerated Computer Vision," IEEE Sensors, October 2019, Montreal, Canada.
  4. A. Vedhanayagam and A.S. Basu, "Droplet Tracking at >600 Frames per Second Using GPU-Accelerated Image Processing," Micro Total Analysis Systems (MicroTAS), October 2017, Savannah GA.
  5. A. Vedhanayagam and A.S. Basu, "Near Video-Rate Droplet Tracking with Computationally-Efficient Image Processing Software," Micro Total Analysis Systems (MicroTAS), October 2017, Savannah GA.
HTChip

DRAM for Single Cell Analysis

P. Weerappuli

We developed a scalable droplet random access memory (DRAM), a microfluidic device in which droplets and single cells can be addressably stored and released.


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Droplet Random Access Memory (dRAM) for Single Cell Analysis

Single cell analysis methods rely on techniques to manipulate large populations of cells, once cell at a time. In this work, we designed a scalable microfluidic platform in which single cells can be stored and retrieved in a manner analogous to computer memory. A key enabling technology is a novel gas-on-gas multiplexing valve which can be patterned at densities of >1000 valves per device. This enables the control of n on-chip gas valves with log(n) external valves. We also designed a high density array of 10,000 single cell traps, each of which can be controlled independently.

References

  1. Priyan Weerappuli and A.S. Basu, "Novel Monolithic Slightly-Open Doormat (SOD) Valve Enables Efficient Fabrication of Highly-Scalable Microfluidic Gas-On-Gas Multiplexer," accepted for Sensors and Actuators B: Physical, 2019
  2. P. Weerappuli and A.S. Basu, "A Compact and Highly Scalable Storage Unit Designed for Integration within a Microfluidic Random Access Memory (dRAM) Platform," Micro Total Analysis Systems (MicroTAS), October 2017, Savannah GA.
  3. P. Weerappuli and A.S. Basu, “Scalable 256-bit Droplet Random Access Memory (DRAM) Platform for Capture and Release of Single Microdroplets,” Micro Total Analysis Systems (MicroTAS), October 2016, Dublin Ireland.
  4. P. Weerappuli, “The Design and Operation of a Microfluidic Droplet Random Access Memory (dRAM) Platform”. Ph.D. thesis, Wayne State University, February 2019.
HRSensor

Ultraminiature Wearable Heart Rate Sensors

M. Rezaei, A. Mandhare, A. Sunkari, N. Raitu, D. Ulmer, O. Sufi, A. Karaali

TRACE is a novel, earlobe-mounted heart rate monitor which provides beat-to-beat accuracy in fitness and health monitoring applications, based on our patented heart rate sensing method.


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Trace: An Ultraminiature Wearable Heart Rate Monitor with Beat-to-Beat Accuracy

HRSensor

Wearable continuous heart rate monitors (CHRM) are widely used in fitness and health applications. The majority of existing devices are either wristwatches, which utilize photoplethysmography (PPG), or chest-straps, which rely on electrocardiography (ECG). Wristwatches are popular due to their comfortable form factor but are known to have lower accuracy than chest straps and have significant lag, which precludes the ability to track rapid changes in heart rate. We are developing Trace, a fully self-contained, earlobe-mounted, wireless PPG CHRM which is 10-fold smaller than previously reported devices. Placement on the earlobe, where there are no muscles or tendons, is less susceptible to noise artifacts. We demonstrate the tracking of heart rate during high intensity interval training (HIIT), where heart rate changes rapidly and sensor lag cannot be tolerated. Notable is Trace’s ability to measure heart rate recovery (HRR), an advanced metric commonly used by athletes to monitor fatigue, and by physicians to assess cardiovascular risk.

High Intensity Interval Training

Training athletes with accurate heart rate sensors with beat-to-beat accuracy can be used to obtain more precise analytics for athletes, including adaptation and recovery rates. Training athletes with accurate heart rate sensors with beat-to-beat accuracy can be used to obtain more precise analytics for athletes, including adaptation and recovery rates. These analytics go beyond simple heart rate to give athletes a more accurate picture of fitness level and training fatigue.

This project is sponsored by the Michigan Translational Research and Commercialization Fund (MTRAC), developed and managed by the Michigan Economic Development Corporation (MEDC). MTRAC helps advance university discoveries and research to the commercial market.

References

  1. M. Rezaei, Avik Basu, and A.S. Basu, "Trace: An Earlobe Mounted Sensor for Accurate, Continuous Measurement of Heart Rate Dynamics," IEEE Sensors, October 2019, Montreal, Canada.
  2. M. Rezaei and A.S. Basu, "Comparison of Two Low-Power Signal Processing Algorithms for Optical Heart Rate Monitoring," IEEE Sensors, October 2018, Delhi India.
  3. D. Chandrasekar, B. Arnetz, P. Levy, and A.S. Basu, “Plug-and-Play, Single-Chip Photoplethysmography,” IEEE Engineering in Medicine and Biology, August 2012, San Diego, CA.
  4. A.S. Basu, “Sensor and Method for Continuous Health Monitoring,” US Patent application WO2013148753, Wayne State University, March 28th, 2012. Status: pending. URL.

Surfactant Hydrodynamic Retardation Effect Detector (SHRED)

A. Fatima

We are developing a novel, label-free, inline chemical detector based on the surfactant retardation effect, first discovered in the 1960s. By amplifying this effect in microfluidic channels, we can use it to detect proteins and surface-active molecules at ng/mL concentration.


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Surfactant Hydrodynamic Retardation Effect Detector (SHRED)

Inline chemical detectors, commonly used in analytical chemistry, quantify analytes based on a variety of chemical properties, but to date, none can do so based on adsorption or solubility properties. This paper presents a novel inline chemical sensing modality, where analyte adsorption changes the frequency of droplets generated in a microfluidic junction. Proteins and other surface-active agents adsorb to the droplet interface and resist droplet flow by the surfactant retardation effect, thereby reducing the drop frequency. SHRED leverages the amplification of this effect in microfluidic channels. The method is repeatable and can perform linear quantitation of hydrophobic proteins and other surface active analytes with a detection limit of as little as 200 pg.


References

  1. A. Fatima and A.S. Basu, "Binary Constrictions, Tip Elongation and Duty Cycle: Shape-Based Mechanisms for Label-Free Detection in Droplets”, Micro Total Analysis Systems, October 2020
  2. A. Fatima and A.S. Basu, "Label Free Quantitation of Immunoglobulin G using the Stagnant Cap Hydrodynamic Retardation Effect Detector (SHRED)," IEEE Sensors, October 2019, Montreal, Canada.
  3. A. Fatima and A.S. Basu, "Measuring Analyte Desorption using a Surfactant Hydrodynamic Retardation Effect Detector," IEEE Sensors, October 2019, Montreal, Canada.
  4. R. Kebriaei and A.S. Basu, "Droplet Frequency Sensor (DFS): A Biomolecular Detector Based on Surfactant Retardation," Micro Total Analysis Systems (MicroTAS), October 2017, Savannah GA.
  5. R. Kebriaei and A.S. Basu, “Droplet Frequency Sensor: A New Modality for Sensitive, Label-free, Inline Biochemical Detection,” The 19th Intl. Conference on Solid-State Sensors, Actuators and Microsystems (Transducers), June 2017, Kaohsiung Taiwan.
AFIDD

Environmental Biodetection

A. Akram, S. Noman, R. Javid, J. Ram

We are developing systems to detect live organisms in ballast water, for preventing invasive species in the Great Lakes.


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AFIDD Ballast Water Verification System

Foreign vessels entering the Great Lakes sometimes inadvertently bring invasive species which can impact the fragile freshwater ecosystem which supplies 20% of the world's freshwater. As part of Professor Jeffrey Ram's team (Wayne State School of Medicine), we designed AFIDD (Automated Fluorescence Intensity Detection Device), a biodetection system which can detect living organisms in ballast tanks. The system is based on a fluorescein diacetate (FDA) assay developed by Prof. Ram. The Microfluidics and Bioinstrumentation lab helped develop an automated system which captures organisms on a reusable filter, and monitors real-time fluorescence with teh number of organisms. The system has been piloted in Michigan and Maryland.

This project is sponsored by the Great Lakes Protection Fund.

References

  1. A.C. Akram, S. Noman, R. Moniri-Javid, J.P. Gizicki, E.A. Reed, S.B. Singh, A.S. Basu, F. Banno, M. Fujimoto, and J.L. Ram, "Development of an automated ballast water treatment verification system utilizing fluorescein diacetate hydrolysis as a measure of treatment efficacy," Water Research, December 2014. [doi]

Droplet Tracking Software

A. Vedhanayagam

Droplet Morphometry and Velocimetry (DMV) is a video processing software for tracking the droplet size, velocity, trajectory, and other parameters. It is available for free for academic researchers, and is used worldwide.

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Droplet Morphometry and Velocimetry (DMV)

When performing biochemical assays in droplets, a great deal of relevant information is encoded into a droplet's physical characteristics, such its size, shape, velocity, trajectory, and pixel intensity. Indeed, many recent reports utilize such characteristics as quantitative measurements for label-free assays. The challenge for researchers in droplet microfluidics is that much of the analysis must be done manually. DMV is a machine vision software which uses image processing techniques to identify and track droplets in digital videos, providing quantitative, time-resolved, label-free measurements. DMV tracks 20 different parameters, including size, shape, trajectory, velocity, pixel statistics, and nearest neighbor spacing. Our Lab on a Chip paper provides details on DMV and how it can be used to analyze common droplet operations and systems reported by industry and academic labs, including: droplet generators, splitting and merging devices, cell encapsulation, serial dilutions, emulsion packing, size distributions and sorting efficiency. DMV provides throughputs of 2-30 frames per second.


View DMV Users in a larger map

DMV is available free of charge to academic researchers. It is currently in use by 35 labs in 14 countries worldwide for droplet and particle tracking as well other as other applications such as insect flight analysis. To obtain a download link, please fill out the DMV request form, and email Prof. Amar Basu at abasu AT eng DOT wayne DOT edu. Accompanying the software are a video training tutorial, installation tutorial and a playlist of videos showing the application of DMV in various operations. We welcome your feedback and novel applications of DMV.

References:

  1. Razieh Kebraei and A.S. Basu, "Autosizing Closed Loop Droplet Generator Using Morphometric Image Feedback,” Micro Total Analysis Systems (MicroTAS), October 2013, Freiburg Germany.
  2. A.S. Basu, "Droplet Morphometry and Velocimetry (DMV): A video processing software for time-resolved, label-free tracking of droplet parameters," Lab on a Chip, April 2013. [doi, pdf]
  3. A.S. Basu, "Droplet Tracking Velocimetry: Automated Measurement of Droplet Motion and Shape Using Digital Image Processing," Micro Total Analysis Systems (MicroTAS), October 2012, Okinawa Japan.
  4. Lab on a Chip Blog entry describing DMV.

Tensiophoresis

G.K. Kurup

Tensiophoresis is the chemomechanical force on a droplet, which can be used to sort droplets by size and chemical composition.

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Tensiophoresis: Label Free Droplet Sorting

Supported by the NSF Particulate and Multiphase Processes Program under award #CBET-1236764

Sorting droplets based on size and chemical contents is an important capability in droplet-based high throughput screening. We are investigating a novel, label-free sorting technique called tensiophoresis. Tensiophoresis exploits liquid-liquid capillary migration of droplets in a controlled interfacial tension (IFT) gradient in a manner analogous to other phoretic separation techniques. We can generate a sharp IFT gradient by using two laminar streams with differing surfactant concentration. The IFT in the two streams can differ by >10 mN/m, yielding substantial capillary pressures. As a result, droplets near the interface migrate down the IFT gradient toward the upper stream. The migration velocity is dependent on the droplet's size and IFT, enabling sorting based on both of these parameters.

   

The ability to sort droplets by their IFT is particularly interesting, because it is closely linked to the droplet's chemical composition. Droplets containing pure water (left) migrate to the lower bifurcation, while those containing sodium dodecyl sulfate (right) do not. This is the first known label free approach for sorting droplet microreactors based on their biochemical contents.

References:

  1. G.K. Kurup and A.S. Basu, "Deterministic Protein Extraction from Droplets Using Interfacial Drag and Tensiophoresis," Micro Total Analysis Systems (MicroTAS), October 2013, Freiburg Germany.
  2. 3. G.K. Kurup and A.S. Basu, "Size Based Droplet Sorting with Wide Tuning Range Using Tensiophoresis," Micro Total Analysis Systems (MicroTAS), October 2013, Freiburg Germany.
  3. G.K. Kurup and A.S. Basu, "Passive, Label-Free Droplet Sorting based on Chemical Composition using Tensiophoresis," Micro Total Analysis Systems (MicroTAS), October 2012, Okinawa Japan.
  4. G.K. Kurup and A.S. Basu, "Tensiophoresis: Migration and Sorting of Droplets in an Interfacial Tension Gradient," Micro Total Analysis Systems (MicroTAS), October 2011, Seattle WA.
  5. G.K. Kurup and A.S. Basu, Submitted.

Optofluidic Tweezers

G.K. Kurup, A. Doshi

Optofluidic tweezers utilizes balanced thermocapillary flows to trap and manipulate droplets using a focused laser beam. OFT have forces more than 100,000 times greater than traditional optical tweezers.


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Optofluidic Tweezers

Supported by the NSF Electronic, Photonic, and Magnetic Devices Program under award #ECCS-1232226

Optical techniques for manipulating liquids and particles have been a long standing interest in physics and biology. Optical tools are attractive because they provide dynamic manipulation and do not require on-chip structures. Optical tweezers (OT) have been widely used, but are not ideally suited for large scale manipulation because they have relatively low force (pN), and the forces are typically repulsive. Optoelectronic tweezers (OET) can provide larger forces (nN), but they require on-chip electric fields. We are investigating optofluidic tweezers (OFT), where droplets are trapped and manipulated using optically generated, spherically confined thermocapillary flows. This approach can trap droplets with holding forces in the µN range, which are 100 stronger than OET, and >100,000 times stronger than optical tweezers.

References:

  1. G.K. Kurup and A.S. Basu, "Indirect Particle Manipulation using a Scanning Optofluidic Tweezer," Micro Total Analysis Systems (MicroTAS), October 2012, Okinawa Japan.
  2. G.K. Kurup and A.S. Basu, "Optofluidic Tweezers: Manipulation of Oil Droplets with 105 Greater Force than Optical Tweezers," Micro Total Analysis Systems (MicroTAS), October 2011, Seattle WA.
  3. G.K. Kurup and A.S. Basu, "Rolling, Aligning, and Trapping Droplets on a Laser Beam using Marangoni Optofluidic Tweezers," Proc. Intl. Conference on Sensors, Actuators, and Microsystems (Transducers), June 2011, Beijing China.
  4. G.K. Kurup and A.S. Basu, "Optofluidic Tweezers", Wayne State University Tech Transfer, Case 11-1048, patent pending.

Droplet Microfractionation

S. Hamed, P. Sehgal, M. Utomo

Droplet fractionation encapsulates chemically separated compounds into droplets, enabling nL-pL fractions to be collected without physical containers.


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Microfractionation in Droplets

Supported by the NSF Chemical and Biological Separations Program under award #CBET-1032603

Biochemical samples are complex mixtures containing 1000’s of components which often must be fractionated prior to analysis. Conventional fraction collectors, which can only accommodate 10’s of fractions, are not well suited for high throughput analysis. In droplet microfluidics, one of the challenges is how to create a library of droplets containing different chemical compounds. Microfractionation in droplets (µFD) is a scalable microfluidic technique for fractionating complex mixtures into droplet containers. A drop generator, placed downstream from a high performance liquid chromatography (HPLC) column, encapsulates the separated components into a serial array of monodisperse droplets. This prevents dispersion of the separated compounds, and allows thousands of droplet fractions without phsyical containers. The droplet library can be stored and subsequently mixed with a target reagent using a downstream tee junction. In principle, µFD can be coupled to a wide variety of separation processes, enabling high throughput fractionation and screening of complex mixtures in µL to sub-nL volumes.

   

References:

  1. S. Hamed, B. Shay, and A.S. Basu, "Capillary Fractionation of HPLC Substrates by a Microfluidic Droplet Generator for High Throughput Analysis," IEEE Engineering in Medicine and Biology (EMBC), September 2011, Boston MA.
  2. V. Trivedi, A. Doshi, G.K. Kurup, E. Ereifej, P.J. Vandevord, and A.S. Basu, "A Modular Approach for the Generation, Storage, Mixing, and Detection of Droplet Libraries for High Throughput Screening," Lab on a Chip, 2010. [doi, pdf]
  3. P. Sehgal, A. Doshi, and A.S. Basu, "Microfractionation of CE-Separated Compounds into Droplets," Micro Total Analysis Systems (MicroTAS), October 2011, Seattle WA.

Hydrodynamic Particle Concentration in Droplets

G.K. Kurup

This project concentrates particles within droplets by exploiting microvortex flow within the droplet.


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Hydrodynamic Particle Concentration inside a Drop

One of the current challenges in droplet systems is the inability to perform heterogeneous biochemical assays, which require particle concentration, mixing, and washing steps. Although there are many particle concentration techniques in continuous-phase microfluidics, relatively few are available in multiphase microfluidics. Towards this end, we are developing a passive technique for concentrating particles in water-in-oil plugs which relies on the interaction between particle sedimentation and the recirculating vortices inherent to multiphase plug flow. The concentration phenomena is governed by the Shields number, a dimensionless parameter which depends on plug velocity and the particle properties. The two important operations of concentration and mixing can be achieved simply by changing the plug velocity. This is the first field-free technique for particle concentration in discrete plugs.

   

References:

  1. G.K. Kurup and A.S. Basu,"Field Free Particle Focusing in a Microfluidic Plug," Biomicrofluidics Special Issue on Multiphase Microfluidics, vol. 6, pp. 022008, April 2012.
  2. G.K. Kurup and A.S. Basu, "Hydrodynamic Particle Concentration in a Microfluidic Plug," Proc. Micro Total Analysis Systems (MicroTAS), Oct. 2010, Groningen, The Netherlands.
  3. G.K. Kurup and A.S. Basu, "Shape Dependent Laplace Vortices in Deformed Liquid-Liquid Slug Flow," IEEE Engineering in Medicine and Biology (EMBC), September 2011, Boston MA.

Off-the Shelf Droplet Microfluidics

V. Trivedi, A. Doshi, P. Sehgal

We demonstrate that droplet generation, merging, and analysis can be carried out in commercial laboratory tubing.


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Modular Droplet Based Microfluidics

Droplet systems provide a high throughput alternative to the microtiter plate used today in genetic, proteomic, and drug screens. While many such systems are fabricated using standard lithography and polydimethylsiloxane (PDMS), which requires some level of expertise lacking in many biology labs. We showed that simple droplet systems can also be assembled using commercially available components commonly used in conventional biochemistry labs. These modular components can perform the basic unit operations: generation, storage, mixing, and detection of droplet libraries.




   

References:

  1. V. Trivedi, A. Doshi, G.K. Kurup, E. Ereifej, P.J. Vandevord, and A.S. Basu, "A Modular Approach for the Generation, Storage, Mixing, and Detection of Droplet Libraries for High Throughput Screening," Lab on a Chip, 2010. [doi, pdf]

Optical Microplates

T. Mertiri, M. Chen

We developed 96-well plates with the ability to control light intensity in each well. These have been used for screening photosynthetic algae and more recently for optogenetic screening.


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Optical Microplates

 

Biological systems respond not only to chemical stimuli (drugs, proteins) but also to physical stimuli (light, heat, stress). Though there are many high throughput tools for screening chemical stimuli, no such tool exists for screening of physical stimuli. We are building novel instruments for high throughput screening of photosynthesis, a light-driven bioprocess. The optical microplate has a footprint identical to a standard 96 well plate, and it provides temporal and intensity control of light in each individual well. Intensity control provides 128 dimming levels (7-bit resolution), with maximum intensity 120 mE/cm2. Temporal modulation, used for studying dynamics and regulation of photosynthesis, can be as low as 10 µs. We use photonic screening for high throughput studies of algal growth rates and photosynthetic efficiency, using the model organism Dunaliella tertiolecta, a lipid producing algae of interest in biofuel production. Due to the ability to conduct 96 studies in parallel, experiments that would require 2 years using conventional tools can be completed in 1 week. This instrument opens up novel high throughput protocols for photobiology and the growing field of phenomics.

References:

  1. Eric A. Davidson, A.S. Basu, Travis S. Bayer, "Programming Microbes Using Pulse Width Modulation of Optical Signals," Journal of Molecular Biology, August 2013. [doi]
  2. M. Chen, T. Mertiri, T. Holland, and A.S. Basu, "Optical microplates for high-throughput screening of photosynthesis in lipid-producing algae," Lab on a Chip, vol. 12, pp. 3870-3874, September 2012. [doi, pdf]
  3. T. Mertiri, M. Chen, A. Hundich, T. Holland, and A.S. Basu, "Optical Microplates for Photonic High Throughput Screening of Algal Photosynthesis and Biofuel Production," IEEE Engineering in Medicine and Biology (EMBC), September 2011, Boston MA.
  4. A.S. Basu, "Environmental Microplates", Wayne State University Tech Transfer, Case 11-1061, patent pending.

Publications

Please Note: Downloads are for personal use only, and may not be distributed without permission of the publisher.

  1. Priyan Weerappuli and A.S. Basu, "Novel Monolithic Slightly-Open Doormat (SOD) Valve Enables Efficient Fabrication of Highly-Scalable Microfluidic Gas-On-Gas Multiplexer," Sensors and Actuators B: Physical, 2019. [doi, pdf]
  2. G.K. Kurup and A.S. Basu, "Sorting Droplets Using Interfacial Tension Gradients," submitted.
  3. R. Kebriaei, A.S. Basu, “Inline protein detection using droplet shape detector,” in process.
  4. A.S. Basu, “Digital Assays, Part I: Partitioning Statistics and Digital PCR,” Society of Laboratory Automation and Screening (SLAS) Technology Journal (formerly Journal of Laboratory Automation). (Invited review paper for Special Issue on Micro and Nanotechnologies for Quantitative Biology and Medicine) [doi, pdf]
  5. A.S. Basu, “Digital Assays, Part II: Digital Protein and Cell Assays,” Society of Laboratory Automation and Screening (SLAS) Technology Journal (formerly Journal of Laboratory Automation). (Invited review paper for Special Issue on Micro and Nanotechnologies for Quantitative Biology and Medicine) [doi, pdf]
  6. A.C. Akram, S. Noman, R. Moniri-Javid, J.P. Gizicki, E.A. Reed, S.B. Singh, A.S. Basu, F. Banno, M. Fujimoto, and J.L. Ram, "Development of an automated ballast water treatment verification system utilizing fluorescein diacetate hydrolysis as a measure of treatment efficacy," Water Research, December 2014. [doi]
  7. Eric A. Davidson, A.S. Basu, Travis S. Bayer, "Programming Microbes Using Pulse Width Modulation of Optical Signals," Journal of Molecular Biology, August 2013. [doi, pdf]
  8. A.S. Basu, "Droplet Morphometry and Velocimetry (DMV): A video processing software for time-resolved, label-free tracking of droplet parameters," Lab on a Chip, April 2013. [doi, pdf]
  9. M. Chen, T. Mertiri, T. Holland, and A.S. Basu, "Optical microplates for high-throughput screening of photosynthesis in lipid-producing algae," Lab on a Chip, vol. 12, pp. 3870-3874, September 2012. [doi, pdf]
  10. G.K. Kurup and A.S. Basu,"Field Free Particle Focusing in a Microfluidic Plug," Biomicrofluidics Special Issue on Multiphase Microfluidics, vol. 6, pp. 022008, April 2012. [doi, pdf]
  11. V. Trivedi, A. Doshi, G.K. Kurup, E. Ereifej, P.J. Vandevord, and A.S. Basu, "A Modular Approach for the Generation, Storage, Mixing, and Detection of Droplet Libraries for High Throughput Screening," Lab on a Chip, 2010. [doi, pdf]
  12. A.S. Basu and Y.B. Gianchandani, "Microfluidic Doublets in Aqueous Samples Generated by Microfabricated Thermal Probes," Sensors and Actuators A:Physical, vol. 158, pp. 116-120, 2010. [doi, pdf]
  13. A.S. Basu and Y.B. Gianchandani, "A Programmable Array for Contact-Free Manipulation of Floating Droplets on Featureless Substrates by the Modulation of Surface Tension," Journal of Microelectromechanical Systems, vol. 18, pp. 1163-1172, 2009. [doi, pdf]
  14. A.S. Basu and Y.B. Gianchandani, "Nanopatterning: Surfaces Feel the Heat," Nature Nanotechnology, vol. 4, pp. 622-623, 2009. [doi, pdf]
  15. A.S. Basu and Y.B. Gianchandani, "Virtual microfluidic traps, filters, channels and pumps using Marangoni flows," Journal of Micromechanics and Microengineering, vol. 18, pp. 110531, 2008. [doi, pdf]
  16. A.S. Basu and Y.B. Gianchandani, "Shaping High-Speed Marangoni Flow in Liquid Films by Microscale Perturbations in Surface Temperature," Applied Physics Letters, vol. 90, pp. 03410/1-03410-3, 2007. [doi, pdf]
  17. A.S. Basu, S. McNamara, and Y.B. Gianchandani, "Scanning Thermal Lithography: Maskless, Submicron Thermo-Chemical Patterning of Photoresist by Ultracompliant Probes," Journal of Vacuum Science and Technology B, vol. 22, pp. 3217-3220, 2004. [doi, pdf]
  18. S. McNamara, A.S. Basu, and Y.B. Gianchandani, "Ultracompliant thermal probe array for scanning non-planar surfaces without force feedback", Journal of Micromechanics and Microengineering, vol. 15, pp. 237-243, 2004. [doi, pdf]
  1. A. Vedhanayagam and A.S. Basu, "Flow Focus-Free Image Flow Cytometry by Image Processing and Data Estimation," Micro Total Analysis Systems, October 2020.
  2. A. Vedhanayagam and A.S. Basu, "Real Time Tracking of Particles at >1,200 events per second using GPU-Accelerated Image Processing," Micro Total Analysis Systems, October 2020.
  3. A. Fatima and A.S. Basu, "Binary Constrictions, Tip Elongation and Duty Cycle: Shape-Based Mechanisms for Label-Free Detection in Droplets”, Micro Total Analysis Systems, October 2020
  4. A. Vedhanayagam and A.S. Basu, “Real-time tracking of droplets and single cells at 12,000 events per second using GPU-accelerated image processing,” Society of Laboratory Automation and Screening, January 2020, San Diego CA. Selected for Tony B. Travel Award.
  5. A. Vedhanayagam and A.S. Basu, "Imaging Flow Cytometry at >13K events/s Using GPU-Accelerated Computer Vision," IEEE Sensors, October 2019, Montreal, Canada.
  6. M. Rezaei, Avik Basu, and A.S. Basu, "Trace: An Earlobe Mounted Sensor for Accurate, Continuous Measurement of Heart Rate Dynamics," IEEE Sensors, October 2019, Montreal, Canada.
  7. A. Fatima and A.S. Basu, "Label Free Quantitation of Immunoglobulin G using the Stagnant Cap Hydrodynamic Retardation Effect Detector (SHRED)," IEEE Sensors, October 2019, Montreal, Canada.
  8. A. Fatima and A.S. Basu, "Measuring Analyte Desorption using a Surfactant Hydrodynamic Retardation Effect Detector," IEEE Sensors, October 2019, Montreal, Canada.
  9. Jonathan Hull, Ashwini Bhat, Tian Yu, Anthony Henderson, and A.S. Basu, "A Novel Computer Vision System for Integrated Biomolecule and Cell Assays", IEEE Sensors, October 2019, Montreal, Canada.
  10. A.S. Basu, "Keynote Presentation: Novel Computer Vision System for Integrated Biomolecule and Cell Assays", Labroots Laboratory Testing and Automation, May 2019. Youtube
  11. Jonathan Hull, Ashwini Bhat, Tian Yu, Anthony Henderson, and A.S. Basu, "A Novel Computer Vision System for Integrated Biomolecule and Cell Assays", Society of Laboratory Automation and Screening (SLAS), January 2020.
  12. M. Rezaei and A.S. Basu, "Comparison of Two Low-Power Signal Processing Algorithms for Optical Heart Rate Monitoring," IEEE Sensors, October 2018, Delhi India.
  13. G.K. Kurup and A.S. Basu, "Label-Free Quantification of DNA in Droplets," Micro Total Analysis Systems (MicroTAS), October 2017, Savannah GA.
  14. R. Kebriaei and A.S. Basu, "Droplet Frequency Sensor (DFS): A Biomolecular Detector Based on Surfactant Retardation," Micro Total Analysis Systems (MicroTAS), October 2017, Savannah GA.
  15. P. Weerappuli and A.S. Basu, "A Compact and Highly Scalable Storage Unit Designed for Integration within a Microfluidic Random Access Memory (dRAM) Platform," Micro Total Analysis Systems (MicroTAS), October 2017, Savannah GA.
  16. A. Vedhanayagam and A.S. Basu, "Droplet Tracking at >600 Frames per Second Using GPU-Accelerated Image Processing," Micro Total Analysis Systems (MicroTAS), October 2017, Savannah GA.
  17. A. Vedhanayagam and A.S. Basu, "Near Video-Rate Droplet Tracking with Computationally-Efficient Image Processing Software," Micro Total Analysis Systems (MicroTAS), October 2017, Savannah GA.
  18. R. Kebriaei and A.S. Basu, “Droplet Frequency Sensor: A New Modality for Sensitive, Label-free, Inline Biochemical Detection,” The 19th Intl. Conference on Solid-State Sensors, Actuators and Microsystems (Transducers), June 2017, Kaohsiung Taiwan.
  19. P. Weerappuli and A.S. Basu, “Scalable 256-bit Droplet Random Access Memory (DRAM) Platform for Capture and Release of Single Microdroplets,” Micro Total Analysis Systems (MicroTAS), October 2016, Dublin Ireland.
  20. M.S. Utomo and A.S. Basu, “Electrophoretic Fractionation and Detection of Proteins Using Droplets,” Micro Total Analysis Systems (MicroTAS), October 2016, Dublin Ireland.
  21. G.K. Kurup and A.S. Basu, "Label-Free Detection of Proteins by Drop Shape Analysis," Micro Total Analysis Systems (MicroTAS), October 2014, San Antonio TX.
  22. R. Kebriaei and A.S. Basu, "Label-Free Inline HPLC Detector using a Drop Generator," Micro Total Analysis Systems (MicroTAS), October 2014, San Antonio TX.
  23. G.K. Kurup and A.S. Basu, "Microfractionation of Gases Separated by Gas Chromatography," Micro Total Analysis Systems (MicroTAS), October 2014, San Antonio TX.
  24. G.K. Kurup and A.S. Basu, "Viscophoresis: Migration and Sorting of Droplets in a Viscosity Gradient," Micro Total Analysis Systems (MicroTAS), October 2014, San Antonio TX.
  25. R.M. Javid, S. Noman, A. Akram, A.S. Basu, and J. Ram, “Automated Ballast Water Treatment Verification,” Society for Laboratory Automation and Screening (SLAS), January 2014, San Diego CA.
  26. R. Kebriaei and A.S. Basu, “Inline Label-Free Protein Detection Using Interfacial Tension,” Society for Laboratory Automation and Screening (SLAS), January 2014, San Diego CA.
  27. G.K. Kurup and A.S. Basu, "Deterministic Protein Extraction from Droplets Using Interfacial Drag and Tensiophoresis," Micro Total Analysis Systems (MicroTAS), October 2013, Freiburg Germany.
  28. Razieh Kebraei and A.S. Basu, "Autosizing Closed Loop Droplet Generator Using Morphometric Image Feedback,” Micro Total Analysis Systems (MicroTAS), October 2013, Freiburg Germany.
  29. G.K. Kurup and A.S. Basu, "Size Based Droplet Sorting with Wide Tuning Range Using Tensiophoresis," Micro Total Analysis Systems (MicroTAS), October 2013, Freiburg Germany.
  30. K.M. Dadesh and A.S. Basu, “40 MHz Frequency Multiplexed Electronic System for Multicolor Droplet Flow Cytometry,” Micro Total Analysis Systems (MicroTAS), October 2013, Freiburg Germany.
  31. Ashrafuzzaman Bulbul, A.S. Basu, and Hanseup Kim, “Characterization of Microbubbles of Multiple Gases in Microfluidic Channels,” Micro Total Analysis Systems (MicroTAS), October 2013, Freiburg Germany.
  32. G.K. Kurup and A.S. Basu, "Passive, Label- Free Droplet Sorting based on Chemical Composition using Tensiophoresis," Micro Total Analysis Systems (MicroTAS), October 2012, Okinawa Japan.
  33. G.K. Kurup and A.S. Basu, "Field-Free Particle Segregation and Extraction for Bead-Based Assays in Plugs," Micro Total Analysis Systems (MicroTAS), October 2012, Okinawa Japan.
  34. G.K. Kurup and A.S. Basu, "Indirect Particle Manipulation using a Scanning Optofluidic Tweezer," Micro Total Analysis Systems (MicroTAS), October 2012, Okinawa Japan.
  35. A.S. Basu, "Droplet Tracking Velocimetry: Automated Measurement of Droplet Motion and Shape Using Digital Image Processing," Micro Total Analysis Systems (MicroTAS), October 2012, Okinawa Japan.
  36. D. Chandrasekar, B. Arnetz, P. Levy, and A.S. Basu, “Plug-and-Play, Single-Chip Photoplethysmography,” IEEE Engineering in Medicine and Biology, August 2012, San Diego, CA.
  37. G.K. Kurup and A.S. Basu, "Tensiophoresis: Migration and Sorting of Droplets in an Interfacial Tension Gradient," Micro Total Analysis Systems (MicroTAS), October 2011, Seattle WA.
  38. G.K. Kurup and A.S. Basu, "Optofluidic Tweezers: Manipulation of Oil Droplets with 105 Greater Force than Optical Tweezers," Micro Total Analysis Systems (MicroTAS), October 2011, Seattle WA.
  39. K.M. Dadesh and A.S. Basu, "Multicolor LIF detection in a Single Optical Window Using Phase-Sensitive Multiplexing," Micro Total Analysis Systems (MicroTAS), October 2011, Seattle WA.
  40. P. Sehgal, A. Doshi, and A.S. Basu, "Microfractionation of CE-Separated Compounds into Droplets," Micro Total Analysis Systems (MicroTAS), October 2011, Seattle WA.
  41. S. Hamed, B. Shay, and A.S. Basu, "Capillary Fractionation of HPLC Substrates by a Microfluidic Droplet Generator for High Throughput Analysis," IEEE Engineering in Medicine and Biology (EMBC), September 2011, Boston MA.
  42. T. Mertiri, M. Chen, A. Hundich, T. Holland, and A.S. Basu, "Optical Microplates for Photonic High Throughput Screening of Algal Photosynthesis and Biofuel Production," IEEE Engineering in Medicine and Biology (EMBC), September 2011, Boston MA.
  43. K. Dadesh, and A.S. Basu, "High Speed Low-Noise Multiplexed Three Color Absorbance Photometry," IEEE Engineering in Medicine and Biology (EMBC), September 2011, Boston MA.
  44. G.K. Kurup and A.S. Basu, "Shape Dependent Laplace Vortices in Deformed Liquid-Liquid Slug Flow," IEEE Engineering in Medicine and Biology (EMBC), September 2011, Boston MA.
  45. G.K. Kurup and A.S. Basu, "Rolling, Aligning, and Trapping Droplets on a Laser Beam using Marangoni Optofluidic Tweezers," Proc. Intl. Conference on Sensors, Actuators, and Microsystems (Transducers), June 2011, Beijing China.
  46. G.K. Kurup and A.S. Basu, "Hydrodynamic Particle Concentration in a Microfluidic Plug," Proc. Micro Total Analysis Systems (MicroTAS), Oct. 2010, Groningen, The Netherlands.
  47. G.K. Kurup and A.S. Basu, "Multispectral Photometry with a Single Light Detector Using Frequency Division Multiplexing," Proc. Micro Total Analysis Systems (MicroTAS), Oct. 2010, Groningen, The Netherlands.
  48. A. Doshi, V. Trivedi, P. Sehgal, and A.S. Basu, "Digital Chromatography and the Formation of Heterogeneous droplet Libraries using Microfractionation in Droplets (µFD)," Proc. Micro Total Analysis Systems (MicroTAS), Nov. 2009, Jeju, Korea. [pdf]
  49. V. Trivedi, E.S. Ereifej, A. Doshi, P. Sehgal, P.J. VandeVord, and A.S. Basu, "Microfluidic Encapsulation of Cells in Alginate Capsules for High Throughput Screening," Proc. IEEE Engineering in Medicine and Biology Conference (EMBC), Sept. 2009, Minneapolis, MN. [doi, pdf]
  50. K. Visvanathan, F. Shariff, S.Y. Yee, and A.S. Basu, "Propulsion and Steering of a Floating Mini-Robot Based on Marangoni Flow Actuation," Proc. Intl. Conference on Sensors, Actuators, and Microsystems (Transducers), June 2009, Denver, Colorado. [doi, pdf]
  51. A.S. Basu and Y.B. Gianchandani, "A 128-Bit Digitallly Programmable Microfluidic Platform for Non-Contact Droplet Actuation Using Marangoni Flows," Proc. Intl. Conference on Sensors, Actuators, and Microsystems (Transducers), June 2007, Lyon, France. [doi, pdf]
  52. A.S. Basu, Seow Yuen Yee, and Y.B. Gianchandani, "Virtual Components for Droplet Control Using Marangoni Flows: Size-Selective Filters, Traps, Channels, and Pumps," Proc. IEEE International Conference on Micro Electro Mechanical Systems (MEMS), Jan. 2007, Kobe, Japan. [doi, pdf]
  53. S. Mutlu, A.S. Basu, and Y.B. Gianchandani, "Maskless Electrochemical Patterning of Gold Films for BioSensors Using Micromachined Polyimide Probes," Proc. IEEE Conference on Sensors, Nov. 2005, Irvine, CA, pp. 1173-1177. [doi, pdf]
  54. A.S. Basu, and Y.B. Gianchandani, "Microthermal Techniques for Mixing, Concentration, and Harvesting DNA and Other Microdroplet Suspensions," Proc. International Conference on Miniaturized Systems for Chemistry and Life Sciences (MicroTAS), Oct. 2005, Boston, MA, pp. 131-135. [pdf]
  55. A.S. Basu, and Y.B. Gianchandani, "Trapping and Manipulation of Particles and Droplets Using Micro-Toroidal Convection Currents," Proc. Intl. Conference on Solid State Sensors, Actuators, and Microsystems (Transducers), June 2005, Seoul, Korea, pp. 85-88. [doi, pdf]
  56. A.S. Basu, and Y.B. Gianchandani, "High Speed Microfluidic Doublet Flow in Open Pools Driven by Non-Contact Micromachined Thermal Sources," Proc. IEEE International Conference on Micro Electro Mechanical Systems (MEMS), Jan. 2005, Miami Beach, FL, pp 666-669. [doi, pdf]
  57. A.S. Basu, S. McNamara, and Y.B. Gianchandani, "Maskless Lithography by Patterned Heating of Photoresist Using Ultracompliant Thermal Probe Arrays," Proc. Electron, Ion, Photon Beam Technology and Nanofabrication (EIPBN), May 2004, San Diego, CA, pp. 109- 111. [pdf]
  58. S. McNamara, A.S. Basu, and Y.B. Gianchandani, "Ultracompliant, Passively Decoupled Thermal Probe Arrays: Large Area Mapping of Non-Planar Surfaces Without Force Feedback," Proc. IEEE International Conference. on Micro Electro Mechanical Systems (MEMS), Jan. 2004, Maastricht, The Netherlands, pp. 825-828. [doi, pdf]
  1. A.S. Basu, "Microthermal Devices for Fluidic Actuation by Modulation of Surface Tension," Ph.D. Dissertation, University of Michigan, August 2008. [pdf]
  1. B.W. Bramlett, A.S. Basu, “Microfluidic Information-Encoding Polymer Data Storage,” US Patent application, Intel Corporation, January 2017. Status: pending. URL.
  2. A.S. Basu, B.W. Bramlett, N.L. Dabby, L.O. Hernandez, “Wearable Assay System and Method of Use,” US Patent application, Intel Corporation, Filed Dec 8, 2016. Status: pending.
  3. D. Snyder, A.S. Basu, and R.G. Cooks, “Systems and Methods for Separating Ions at About or Above Atmospheric Pressure,” US Patent application 62/288,082, Purdue Research Foundation, filed January 2017. Status: pending. URL.
  4. A.S. Basu and G. Kamalaksakurup, “Optofluidic Tweezers,” US Patent US8944084, Wayne State University, Feb 3, 2015. Status: granted. URL. Wayne State University Tech Transfer, Case 11-1048
  5. A.S. Basu, “Sensor and Method for Continuous Health Monitoring,” US Patent application WO2013148753, Wayne State University, March 28th, 2012. Status: granted March 2019. URL.
  6. A.S. Basu, “Device and method for optimizing photobiological processes,” US Patent application number WO2013033080, Wayne State University, August 29, 2011. Status: pending. URL. Wayne State University Tech Transfer, Case 11-1061.
  7. A. Gaitas and A.S. Basu, “Lab on a Pipette,” US Patent number US8394625, Picocal Inc., March 12, 2013. Status: granted. URL.
  8. B. Mitra, A. Gaitas, A.S. Basu, and W. Zhu, "Scanning Probe Assisted localized CNT growth," US Patent US8192809, Picocal Inc., June 5, 2012. Status: granted. URL.
  9. Y. B. Gianchandani, and A.S. Basu, "Marangoni Convection Driven by Micro-Scale Thermal Sources, and its Application to Single Molecule Detection," U.S. Patent 7358051, University of Michigan, April 15, 2008. Status: granted. URL.
  10. Y.B. Gianchandani, S.P. McNamara, J. Lee, and A.S. Basu, "Micromachined Thermal Probe Apparatus, System for Thermal Scanning a Sample in Contact Mode, and Cantilevered Reference Probe for Use Therein," U.S. Patent 7073938, University of Michigan, July 11, 2006. Status: granted. URL.
  11. M.S. McCorquodale, S. Pernia, and A.S. Basu, "Frequency calibration for a monolithic clock generator and timing/frequency reference," U.S. Patent 7248124, Mobius Microsystems, July 24, 2007. Status: granted. URL .
  12. M.S. McCorquodale, S. Pernia, and A.S. Basu, "Monolithic clock generator and timing/frequency reference," U.S. Patent 7227423, Mobius Microsystems, Jun 5, 2007. Status: granted. URL.

Courses

ECE 7995: BioMEMS and Bioinstrumentation

BioMEMS and BioInstrumentation is an interdisciplinary graduate level course is open to students in engineering, chemistry, physics, and life sciences. It will cover the fundamentals of biomedical micro and nanosystems, with a focus on lab-on-a-chip technologies. Students will learn about the miniaturization of analytical systems used in biology, chemistry, and medicine. Topics of interest to engineering and physics students include: micro and nanofabrication techniques, the physics of microfluidic flow and other microscale phenomena, and computational modeling techniques. Students in life science and chemistry will learn emerging analytical techniques, molecular/particle/cell separations on chip, single cell assays, and detection methods.

Lecture Recordings

ECE 4570: Fundamentals of Solid State Devices

ECE 4570 is a senior level undergraduate course covering aspects of electrical properties of semiconductors, the physical electronics of P-N junction, bipolar, field effect transistors, and device fabrication technology essential to understanding semiconductor active devices and integrated circuits. Introduction to the behavior of semiconductor and electronics devices. Students also take part in a semiconductor fabrication lab, where they learn about the microfabrication processes used to manufacture and test semiconductor devices including resistors, diodes, and MOSFETs.

Lecture Recordings

ECE 4800 Electromagnetic Fields and Waves

Fundamentals of electromagnetic engineering, static electric and magnetic fields using vector analysis and fields of steady currents, Maxwell's equations and boundary value problems. Basic principles of plane waves, transmission lines and radiation.

ECE 9997 Doctoral Seminar

Weekly research seminar for graduate students in Electrical and Computer Engineering. This year's seminar schedule can be found here.

Nanotechnology Programs at the Detroit Science Center

Nanotechology is quickly becoming a pervasive and fundamental component of science and technology. The microfluidics laboratory is collaborating with the Detroit Science Center, the city's premiere source for K-12 science education, to develop modules for educating and inspiring future scientists and engineers in the micro and nanoscale worlds.

Wayne State University Summer Research Academy (SURA)

Sponsored by the National Science Foundation's Michigan Louis Stoke Alliance Minority Participation (MI-LSAMP) program, SURA is an effort designed by Wayne State's MI-LSAMP Work Group to provide summer research opportunities primarily to first and second year undergraduate students at Wayne State and other partner institutions, including Michigan State University, University of Michigan-Ann Arbor, and Western Michigan University. MI-LSAMP aims to significantly increase the number of minority students earning baccalaureate degrees each year in Science, Technology, Engineering and Mathematical (STEM) fields and prepare them for entry into graduate programs.

Current and Past Lab Members

Graduate Students

Undergraduates

High-School Students

Amar S. Basu

Associate Professor, Electrical and Computer Engineering
Joint appointment in Biomedical Engineering
Graduate Program Director, Department of Electrical and Computer Engineering

Wayne State University
3133 Engineering Building
5050 Anthony Wayne Drive
Detroit, MI 48202

Phone: 313-577-3990
Fax: 313-577-1101
Email: amar DOT basu AT wayne DOT edu

Curriculum Vitae

Research Interests

Microfluidics, bioMEMS, and integrated microsystems for applications in biotechnology and nanotechnology. Specific interests include:

Education

Honors

Professional Service