miniaturization in electronic technologyme.jhu.edu/thwang/notes/introduction-biomems.pdf · eniac:...
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![Page 1: Miniaturization in Electronic Technologyme.jhu.edu/thwang/notes/Introduction-BioMEMS.pdf · ENIAC: the "Electronic Numerical Integrator and Calculator“, 1943 ENIAC filled a 20 by](https://reader034.vdocument.in/reader034/viewer/2022042400/5f0e69cf7e708231d43f203e/html5/thumbnails/1.jpg)
BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University
ENIAC: the "Electronic Numerical Integrator and
Calculator“, 1943
ENIAC filled a 20 by 40 feet room, weighed 30 tons,
and used more than 18,000 vacuum tubes.
Miniaturization in Electronic Technology
A8 Chip, 2014
>109 transistor
iPhone 6
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University 2
Savings in time & cost
Less materials and samples
Short processing time
Disposable
Parallel processing
Integration/Automation
Why Being Small ?
• Laminar Flow
• High surface to volume ratio
High single-to-noise ratio in transuding signals
• Small thermal mass
• Strong fields such as electric fields
Gain from the unique
microscopic features
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University 3
Spacecraft Human Organ Tissue Cell DNA
>100 m 1 m 10-2 m 10-6 m 10-9 m
Micro/Nano Technology
Length Scale Matching
• Manipulation of
molecules and cells
• High resolution /
sensitivity
(Kim)
(Wang)
Why Being Small ?
e.g. to facilitate single-molecule diagnostics,
study of single-cell biology
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University 4
Classes of BioMEMS
(Bio-MicroElectroMechanicalSystem)
Microfluidics & Microfluidic Devices
Biosensors and Bioelectronics
Neural Interface Devices
Chromatography /Electrophoresis Devices
Microsurgical Tools
Bioreactors
Tissue Engineering Devices
Molecule /Cell Handling Devices
Implantable Devices, Drug Delivery Devices
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University 5
(Sandia)
Examples of MEMS Devices
Spider mite on gears
Micro-mirrors
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University 6
Projector
(Texas Instruments)
(Analog Device)
Air Bag Sensor
Bubble Inkjet
(HP)
Examples of Industrial MEMS Devices
Motion & Orientation sensor (Wii)
(Nintendo)
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University 7
Apple iPhone 6
6-axis Gyro/Accel (Invensense)
3-axis Accelerometer(Bosch)
3-axis Magnetometer (AKM)
3 microphones (Knowles)
Pressure Sensors (Bosch)
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University 8
MEMS Is Everywhere in Your Daily Life
Trillions of MEMS sensors coming soon !
Internet of Things (IoT)
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University 9
Capillary Electrophoresis
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University 10
Micromachined Capillary Electrophoresis (m-CE)
• High throughput
• Low volume
• Rapid analysis (Ra Mathies, PNAS 2006)
• Integrated with thermal
cycling and CE for
Sanger sequencing
• Off-chip optical detection
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University 11
Thermal Cycling for Polymerase Chain Reaction (PCR)
PCR is an expensive and time-consuming technique
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University 12
Continuous-flow Micro PCR
(A. Manz, Science 2002)
(M.A. Burns U Mich, Science)
• PCR reaction
• Gel electrophoresis
• Microfluidics
• On-line electrical detector
Integration of CE and m-PCR
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University 13
Microfluidic Digital PCR : Nanoliter-sized PCR arrays
(J.R. Leadbetter, Science 2006)
• 1176 chamber
• 6.25 nL each chamber
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University 14
Droplet Digital PCR: Picoliter-sized PCR arrays
(T. Rane, Lab Chip, 2015)
0 2 4 6 8 100
1000
2000
Ph
oto
n C
ou
nts
per
100
use
c
Calcein Channel
0 2 4 6 8 100
500
1000
Time (sec)
ROX channel
2.35 2.4 2.450
500
1000
1500
Ph
oto
n C
ou
nts
per
100
use
c
Calcein Channel
2.35 2.4 2.450
500
1000
Time (sec)
ROX channel
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University 15
Analysis of Single Cells
(R. Zare, Scinece 2006)
Single-Molecule
Detection
Preparation of a
single cell
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University 16
Laminar Flow-Based Assay
(P. Yager)
• Laminar flow – initiate reaction
• Diffusion-based analysis
T-Sensor
Separation
Rapid Mixing
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University 17
Flied Flow Fraction-DEP cell sorter
( U. Texas, Houston)
• Field flow fraction using
DEP force
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University
Free Solution Hydrodynamic Separation
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University 19
Nano Fluidics
100-nm-wide nanochannel array
Stretch of l DNA (48.6 kbp)fragment
DNA is driven by E-field
(R. Austin)
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University 20
Digital Microfluidics
• Pump-free and valve-free
• Each sample and reagent is
individually addressable
• Array-based analysis
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University
Integrated DNA Preparation and PCR Detection
Using Silica Superparamagnetic Particles (SSP) as a solid phase within droplets
Lysis/Binding buffer
Washing buffer 1
Cell lysis DNA purification
& concentration PCR reaction DNA amplification
(thermal cycling)
Centralized & manual tube based PCR
detection
Sample
In Answer
Out
Sample 1
Sample 2
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University
Surface topology assisted SSP and droplet
manipulation
a)
SS
P p
lug
Su
rfa
ce
ele
va
tio
n
a)
b)
Surface elevation
SSP plug
Drops in Air
Drops in Oil
(Y Zhang, Lab Chip 2011)
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University
0 5 10 15 20 25 30 350
400
800
1200
1600
Flu
ore
sce
nce
In
ten
sit
y (
AU
)
Cycle (n)
a) b)
40 50 60 70 80 90 1000.0
0.2
0.4
0.6
0.8
1.0
0.00
0.02
0.04
0.06
0.08
0.10 Fluorescence
-dF
/dT
No
rmalize
d F
luo
rescen
ce In
ten
sit
y
Temperature (Celsius)
Negative first derivative
On-Chip Real-Time PCR Detection
0 10 20 30 40900
1000
1100
1200
1300
1400
1500
Flu
ore
scen
ce I
nte
nsit
y (
AU
)
Cycle (n)
Detection of E coli 16S gene from cell culture
Marker Amplicon
100bp
150bp
200bp
250bp
300bp
Detection of Rsf-1 marker from whole blood
0 5 10 15 20 25 30 350
400
800
1200
1600
Flu
ore
sc
en
ce
In
ten
sit
y (
AU
)
Cycle (n)
a) b)
40 50 60 70 80 90 1000.0
0.2
0.4
0.6
0.8
1.0
0.00
0.02
0.04
0.06
0.08
0.10 Fluorescence
-dF
/dT
No
rmalized
Flu
ore
scen
ce In
ten
sit
y
Temperature (Celsius)
Negative first derivative
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University
Features
• Monodisperse droplets of
sizes ranging from nL-pL
• High speed droplet
generation of > kHz
Potential applications
• Low-cost & High throughput
screening
• Biochemical synthesis
• Digital PCR
• Single-cell analysis
24 24
Microfluidic Droplet Technology for High-Throughput Analysis
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University
Droplet Microfluidics for Monitoring of Kinetics
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University 26
DNA Microarrays
Affymetrix
• Fabricated with lithographic
technique
• cDNA array
• Gene expression profiling
• Relative fluorescence
measurement
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University 27
Neural Probe/ Neuro Implant
• Neuro-circuit interaction – neuro-recoding
• Prosthesis research
• Chemical delivery
• Issues with long term implant – bio compatibility
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University 28
Tissue Engineering / Cell Patterning • Patterning cells using microfluidics
• Control of microenvironments using microfluidics
• Single-cell (controlled small number of cells) patterning
• High-throughput search for right cell conditions for controlling cell growth,
differentiation, apoptosis)
( Whitesides)
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BioSensing & BioMEMS 530/580.672 Jeff Wang Johns Hopkins University 29
Corneal Microtissue Culture
( C. Puleo, Lab Chip. 2009)