This letter nominates Dr. Fei Su for an Outstanding Ph.D. Dissertation Award for his work on design automation and test methods for digital microfluidic biochips. Digital microfluidic biochips use electrowetting-on-dielectric to manipulate discrete droplets of fluids, revolutionizing applications like DNA sequencing and clinical diagnostics. Dr. Su's dissertation focused on synthesis, testing, and reconfiguration techniques to address design challenges for these emerging lab-on-chip devices. The work exploits the reconfigurability of droplet-based "digital" microfluidics to automate labor-intensive tasks and allow remapping of bioassays in the case of chip defects.

1. Automated Design of Digital
Microfluidics Lab-on-Chip
Connecting Biochemistry to Information Technology
And Electronic Design Automation
Krishnendu Chakrabarty
Department of Electrical and Computer Engineering
Duke University
Durham, NC
1
Acknowledgments
• Students: Tianhao Zhang, Fei Su, William Hwang, Phil Paik, Tao Xu,
Vijay Srinivasan, Yang Zhao
• Post-docs, colleagues, and collaborators: Dr. Vamsee Pamula, Dr.
Michael Pollock, Prof. Richard Fair, Dr. Jun Zeng (HP Labs), Dr. S.
Krishnamoorthy (Baxter)
• Duke University’s Microfluidics Research Lab
(http://www.ee.duke.edu/research/microfluidics/)
• Advanced Liquid Logic (http://www.liquid-logic.com/): Start-up
company spun out off Duke University’s microfluidics research
project
2
1

2. Motivation for Lab-on-Chip
• Clinical diagnostics, e.g., healthcare for
premature infants, point-of-care diagnosis of
diseases
• “Bio-smoke alarm”: environmental monitoring
• Massive parallel DNA analysis, automated
drug discovery, protein crystallization
CLINICAL DIAGNOSTIC Lab-on-a-chip for
APPLICATION CLINICAL DIAGNOSTICS
Shrink
Microfluidic Lab-
on-a-Chip
20nl sample
Higher throughput, minimal human intervention,
smaller sample/reagent consumption, higher
sensitivity, increased productivity
Conventional Biochemical Analyzer
3
The Futility of Predicting Applications
Kroemer’s Lemma of New Technology:
The principal applications of any sufficiently new and
innovative technology have always been—and will
continue to be—applications created by that technology.
Herbert Kroemer, Department of Electrical and Computer
Engineering, University of California at Santa Barbara
Nobel Prize winner for Physics, 2000
4
2

3. Tubes to Chips: Integrated Circuits
• Driven by Information Processing needs
IBM Power 5 IC
(2004)
IBM 701 calculator (1952)
5
Tubes to Chips: BioChips
• Driven by biomolecular analysis needs
BioMark™ Dynamic Arrays
Fluidigm
Test tube analysis
6
3

4. Why Do We Care?
System Driver
Beyond
2009: “Medical”
Intel Research Day 2007: Biochip prototype
demonstrated for point-of-care diagnostics and
2007
lab testing
7
Press Releases and News Items
L
NA
UR
O
J
ET
RE
ST
L
AL
W
E
TH
8
4

5. Why is Biochemistry-on-a-Chip Difficult?
A
C
B
Mixing
A+B
Synthesis
A
A+B
B
Analysis
Reaction Separation
9
Why is Biochemistry-on-a-Chip
Difficult?
10
5

6. what’s a biochip?
By the way,
It’s a miniature disposable for an
HTS - High-Throughput Screening -
(bio)analytical instrument
what does it do?
Essentially the same operations you did in high school
chemistry class:
dispensing,
mixing,
detecting,
discarding,-
just a lot cheaper and a lot faster than you did
11
Why do chips have to be small?
High-Throughput is why. If you do 106 assays in 10μl format,
each time you do a reaction you’ll need 10 liters of reagents.
With the typical cost of biological reagents, even Big Pharma
can’t afford this.
why High-Throughput?
By the way,
• Because you need a lot of raw data for many applications
• Because, with the currently available technology, to produce
raw data that would keep a CPU busy for a few minutes
($0.1), you need a Ph.D. scientist and a couple of technicians
for a month ($10,000)
12
6

7. Talk Outline
• Motivation
• Technology Overview
– Microarrays
– Continuous-flow microfluidics: channel-based lab-on-chip
– “Digital” microfluidics: droplet-based lab-on-chip
• Overview of Fabrication Method
• Design Automation Methods
– Synthesis and module placement
– Droplet Routing
– Pin-Constrained Design
– Testing and Reconfiguration
• Conclusions
13
Microarrays
• DNA (or protein) microarray: piece of glass, plastic or silicon
substrate
• Pieces of DNA (or antibodies) are affixed on a microscopic array
• Affixed DNA (or antibodies) are known as probes Hybridized array
• Only implement hybridization reaction ♦
♦
A A
T
♦
G G G G
C C
DNA
G T C G T G C
C A
Sample
C T T C T A T
G A
T A T A
A T
T A A
Optical Scan
A C C G
T G
A C G
substrate
substrate
Unhybridized array
Laser
14
7

8. What are the main types of biochips?
Passive (array):
all liquid handling functions are performed by
the instrument. The disposable is simply a
patterned substrate.
Active (lab-on-chip, μ-TAS):
some active functions are performed by the
chip itself. These may include flow control,
pumping, separations where necessary, and
even detection.
15
Motivation for Microfluidics
Automation
Test tubes Integration
Miniaturization
Automation
Robotics Integration
Miniaturization
Automation
Microfluidics Integration
Miniaturization
16
8

9. Microfluidics
• Continuous-flow lab-on-chip: Permanently etched microchannels,
micropumps and microvalves
• Digital microfluidic lab-on-chip: Manipulation of liquids as discrete
droplets
Multiplexing
(Duke University)
Mixing: Static,
Diffusion Limited
Biosensors: Control
Optical: SPR, Fluorescence etc. electronics
Electrochemical: Amperometric,
(shown) are
Potentiometric etc.
suitable for
Printed circuit board handheld or
lab-on-a-chip – benchtop
inexpensive and applications
readily manufacturable
17
Electrowetting
• Novel microfluidic platform invented at Duke University
• Droplet actuation is achieved through an effect called
electrowetting
⎯ Electrical modulation of the solid-liquid interfacial tension
No Potential Applied Potential
A droplet on a hydrophobic The droplet’s surface energy
surface originally has a increases, which results in a
large contact angle. reduced contact angle. The
droplet now wets the surface.
18
9

10. What is Digital Microfluidics?
• Discretizing the bottom electrode into multiple electrodes, we can
achieve lateral droplet movement
Note: oil is typically used to fill between the Droplet Transport (Side View)
top and bottom plates to prevent evaporation.
19
What is Digital Microfluidics?
Transport
25 cm/s flow rates,
order of magnitude
higher than
continuous-flow
methods
For videos, go to www.ee.duke.edu/research/microfluidics
20
10

11. What is Digital Microfluidics?
Splitting/Merging
21
Demonstrations of Digital Microfluidics
Droplet Formation
Synchronization of many droplets
http://www.ee.duke.edu/research/microfluidics
22
11

12. What is Digital Microfluidics?
Droplet Formation
8 droplets in 3.6s
23
What is Digital Microfluidics?
Mixing
24
12

13. Advantages
• No bulky liquid pumps are required
– Electrowetting uses microwatts of power
– Can be easily battery powered
• Standard low-cost
fabrication methods can be
used
– Continuous-flow systems
use expensive
lithographic
techniques to create
channels
– Digital microfluidic chips
are possible using solely
PCB processes
Droplet Transport on PCB (Isometric View)
25
An Example
• Detection of lactate, glutamate and pyruvate has also been
demonstrated.
• Biochip used for multiplexed in-vitro diagnostics on human
physiological fluids
Fabricated microfluidic array used for multiplexed biomedical assays
26
13

14. Capabilities
• Digital microfluidic lab-on-chip
TRANSPORT DISPENSING MIXERS REACTORS DETECTION
TRANSPORT DISPENSING MIXERS REACTORS DETECTION
Basic microfluidic functions (transport, splitting,
merging, and mixing) have already been
demonstrated on a 2-D array
INTEGRATE
Highly reconfigurable system
Digital Microfluidic
Biochip
Protein crystallization chip
(under development)
27
Advantages of Digital Microfluidics
Digital Microfluidics Other Microfluidic Technologies
• Very accurate droplet volumes • Pump fluids through channels
– Droplet sizes in the 1 nanoliter to several
• Must adapt assays to channel-
microliter range; droplet dispensing volume
based format
variation ~1%
• Complex or multiplexed assays
• Programmable, software-driven electronic
become a plumber’s nightmare
control
• Off-chip pumps and valves mean
– No moving parts, tubes, pumps or valves
large, expensive equipment and
• More efficient use of samples and reagents low reliability
– No liquid is wasted priming channels
• Expensive, time consuming, up-
• Extremely energy efficient front investments required for most
– Nanowatts of power per single step of chip developments
actuation
• Designs are fixed in the
• Development cycles are short, and assays development process
can be implemented with software changes
• Compatible with live biologic and most other
materials •Droplets moved in
“virtual channels” defined
by electrodes
•Programmable
electrodes directly control Caliper Technologies’
discrete droplet LabChip
operations
28
14

15. Glass Chip Platform Development
Top Plate (Optional) (i.e. glass or plastic)
Gasket Layer (100 to 600 µm) (proprietary)
Hydrophobic Layer (50 nm) (i.e. Teflon dip coated)
Insulator Layer (1 to 25 µm) (i.e. parylene)
Patterned Metal on Substrate
(i.e. chrome on glass via lift-off
process)
Chip Assembly
Top plate is either glued or fixed in place
by pressure
Contacts are made either through the
top or bottom
Droplets are either dispensed by hand or
formed from on-chip reservoirs
29
PCB Chip Platform Development
Fabrication Process
Gasket Layer
Flash Plating
(Dry Soldermask)
(Copper)
Hydrophobic Layer
(Teflon AF)
Dielectric
(LPI Soldermask)
PCB
Top Metal Layer
(Copper)
Bottom Metal Layer
(Copper)
Via Hole Filling
(Non Conductive Epoxy)
• PCB Material – Mitsui BN300 – 64 mil
• Top Metal Layer (Electrodes) – Cu – 15µm
• Bottom Metal Layer (Contacts) – Cu – 15µm
• Dielectric – LPI Soldermask – 25 µm
• Via Hole Filling – Non-conductive Epoxy
• Hydrophobic Layer – Teflon AF – 0.05 to 1.0 µm
• Gasket (spacer) – Dry Film Soldermask (Vacrel 8140) – 4 mils (~95µm after processing)
30
15

16. Computer-Aided Design: Vision
• Automate labor-intensive tasks, reduce burden on chip users
– Map bioassays to a fabricated chip: schedule fluidic operations,
determine droplet flow pathways, configure fluidic modules
dynamically, etc.
– Monitor the chip for defects that require remapping of bioassays
• Role of computer-aided design (CAD) tools
– Reduce setup time associated with the use of these chips
– Allow automatic reconfiguration of a faulty chip and remap the
remaining steps of bioassay.
– Develop capabilities that mirror compiler and operating system support
provided to software programmers
– Obviate the need for tedious remapping of assays to the chip by hand
for each target application.
• Similar to an FPGA? Logic Interconnects
31
CAD = ?
cad n. An unprincipled, ungentlemanly person
CAD abbr. Computer-Aided Design
Better to be in CAD than to be a cad?
32
16

17. The Road Not Taken…
I shall be telling this with a sigh
Somewhere ages and ages hence:
Two roads diverged in a wood, and I-
I took the one less traveled by,
And that has made all the difference.
Robert Frost, The Road Not Taken
Agilent’s Protein Nanogen’s NanoChip™
LabChip Microelectronic Array
Cartridge
i-STAT Biodiagnostic
μ-system
33
Similar to Concurrency in a PC!
January 28, 2007
Prof. Radu Marculescu
Attn: Outstanding Ph.D. Dissertation Award
Carnegie Mellon University
Department of Electrical and Computer Engineering
5000 Forbes Avenue
Pittsburgh PA 15213-3890
Dear Prof. Marculescu:
I am very pleased to write this letter of nomination for Dr. Fei Su for the AC
Outstanding Ph.D. Dissertation Award in Electronic Design Automation.
received his Ph.D. degree from Duke University in May 2006 and his thesis wo
was carried out under my supervision.
Fei’s PhD dissertation is titled “Synthesis, Testing, and Reconfigurat
Techniques for Digital Microfluidic Biochips”. It is focused on design automati
and test methods for emerging lab-on-a-chip devices that rely on the principle
electrowetting-on-dielectric. By exploiting the reconfigurability inherent
droplet-based “digital” microfluidics, these devices are revolutionizing a w
range of applications, such as high-throughput sequencing, para
immunoassays, blood chemistry for clinical diagnostics, DNA sequencing, a
environmental toxicity monitoring.
Microsystems for biomedical and sensing applications are often referred to
lab-on-a-chip or biochips. These are typically centimeter-sized chips, with on-ch
components having micrometer feature lengths. These components are created
IC fabrication technology (surface or bulk micro-machining), and they are
diverse functionality. Just as bioscience is sometimes called “wet” science, t
application of biochips relies primarily on its ability to work with fluids throu
its on-chip components. Biochemical samples are placed on the biochip in
liquid form. A pre-programmed analysis is then carried out automatically and
parallel. Miniaturization enables minute sample volume, thus it speeds
chemical reactions and analytical detection; automation and parallelization ma
it possible to carry out a massive number of different tests simultaneously. The
characteristics, especially the delivery of results for a large number of tests with
a short amount of time, are especially relevant for clinical diagnosti
environmental monitoring, and bio-defense applications.
Digital microfluidics has heralded the second (and remarkably advanc
generation of biochips. It utilizes tiny droplets as on-chip chemical compou
carriers. An on-chip array of electrodes that are individually addressable throu
CMOS electronics can manipulate each droplet electrically. A set of programma
CMOS instructions can induce the merging of two droplets. Such merg
operations constitute the key operations in on-chip chemical reactions. Multi-s
34
The operating system manages complexity, allows multi-tasking!
17

18. Design Methodology
• VLSI design
Constraints:
VLSI chip Area <…
If constraints System Level
wanted Delay <…
are not met
Re-design System Level
Module Level
Module Level
…..
Gate Level
Gate Level
…..
Circuit Level
Circuit Level
….. …..
Top-down design method
Bottom-up design method
35
Biochip Design Methodology
• Bottom-up vs. top-down biochip design
Constraints
Biochip wanted
If constraints Biochip designed
are not met
Biochip wanted
Re-design all
sub-blocks ! Biochip designed
Anticipated to be needed Constraints Constraints
Module 1 Module m Module 1 Module m
…..
designed and verified … designed and verified designed designed
Constraints
Constraints
Anticipated to be needed
Component 1 Component n Component 1 Component n
…..
…..
designed and verified designed and verified designed designed
Top-down design method
Bottom-up design method
36
18

19. Biochip Design Automation
37
Design Automation: Biochip Synthesis
• Full-custom bottom-up design Top-down system-level design
S1: Plasma, S2: Serum,
S3: Urine, S4: Saliva
Assay1: Glucose assay,
Assay2: Lactate assay,
Assay3: Pyruvate assay,
Assay4: Glutamate assay
S1, S2, S3 and S4 are
assayed for Assay1,
Assay2, Assay3 and
Assay4.
Scheduling of operations
Binding to functional
resources
Physical design
38
19

20. Sequencing Graph Model
Sequencing graph model for
multiplexed bioassays
39
Mathematical Programming Model
Objective Constraints
Dependency constraints
• First define a binary
Stj ≥ Sti + d(vi) if there is a dependency
variable
⎧ 1 if operation vi starts at
X ij = ⎨ between vi and vj
⎩ 0 otherwisej.
time slot
Resource constraints
Starting time of operation vi : Reservoirs/dispensing ports
T
St i = ∑ j × X ij Nr reservoirs/dispensing ports assigned to
j =1 each type of fluid (Nr = 1)
∑ X ij ≤ 1, ∑ X ij ≤ 1
Completion time of operation: … : 1≤ j≤ T
i:vi∈I m + n
i:vi ∈I1
C = max {Sti + d(vi) : vi ∈D1, …, Dn}
Reconfigurable mixers and
Objective function: storage units
minimize C Nmixer(j) + 0.25 Nmemory(j) ≤ Na 1 ≤ j ≤ T
Optical detectors
Nd detectors are assigned to each
bioassay (Nd = 1)
j
j
∑ X ij ≤ 1, …v∑ ∑ X ij ≤ 1 1≤ j≤ T
∑ i: ∈D l = j − d ( vi )
i:vi ∈D1 l = j − d ( vi ) i n1
40
20

21. Physical Design: Module Placement
• Placement determines the locations of each module on the
microfluidic array in order to optimize some design metrics
• High dynamic reconfigurability: module placement 3-D
packing modified 2-D packing
Reduction from
3_D placement
to a modified
2-D placement
41
Unified Synthesis Methodology
42
21

22. Protein Assay: Dilution Steps
Sequencing graph model
• Maximum array area:
10x10
• Maximum number of
optical detectors: 4
• Reservoir number:
1 for sample;
2 for buffer;
2 for reagent;
1 for waste
• Maximum bioassay
time: 400 s
43
Synthesis Results
Bioassay
completion time
T: 363 seconds
Biochip array:
9x9 array
44
22

23. Synthesis Results (Cont.)
• Defect tolerance
Bioassay
completion time
T: 385 seconds
(6% increase)
45
Droplet Routing
• A key physical design problem for digital microfluidic
biochips
• Given the results from architectural-level synthesis and
module placement:
– Determine droplet pathways using the available cells in the
microfluidic array; these routes are used to transport droplets
between modules, or between modules and fluidic I/O ports
(i.e., boundary on-chip reservoirs)
• To find droplet routes with minimum lengths
– Analogous to the minimization of the total wirelength in VLSI
routing
• Need to satisfy critical constraints
– A set of fluidic constraints
– Timing constraints: (the delay for each droplet route does not
exceed some maximum value, e.g., 10% of a time-slot used in
scheduling)
46
23

24. Fluidic Constraints
Directly
• Assume two given droplets as Di adjacent
and Dj, and let Xi(t) and Yi(t) Diagonally
denote the location of Di at time t adjacent
How to select the admissible locations at time t +1?
Rule #1: |Xi(t+1) − Xj(t+1)| ≥ 2 or |Yi(t+1) − Yj(t+1)| ≥ 2, i.e., their new
locations are not adjacent to each other.
Rule #2: |Xi(t+1) − Xj(t)| ≥ 2 or |Yi(t+1) − Yj(t)| ≥ 2, i.e., the activated
cell for Di cannot be adjacent to Dj.
Rule #3: |Xi(t) − Xj(t+1)| ≥ 2 or |Yi(t) − Yj(t+1)| ≥ 2.
Static fluidic constraint Dynamic fluidic constraints
47
Experimental Verification
(a) Experimental verification of Rule #1: droplets begin on electrodes 1 and 4; (b) Electrodes 2
and 3 are activated, and 1 and 4 deactivated; (c) Merged droplet.
(a) Experimental verification of Rule #2: droplets begin on electrodes 2 and 4; (b)
Electrodes 1 and 3 are activated, and 2 and 4 deactivated.
48
24

25. Experimental Verification (Cont.)
(a) Experimental verification of Rule #3: droplets begin on electrodes 4 and 7; (b) Electrodes 3
and 6 are activated, and 4 and 7 deactivated; (c) Merged droplet.
• To demonstrate that adherence to Rule #1 is not sufficient to prevent
merging. Both Rule #2 and Rule #3 must also be satisfied during droplet
routing.
• These rules are not only used for rule checking, but they can also provide
guidelines to modify droplet motion (e.g., force some droplets to remain
stationary in a time-slot) to avoid constraint violation if necessary
49
Design of Pin-Constrained Biochips
Direct Addressing
• Each electrode connected to an independent pin
• For large arrays (e.g., > 100 x 100 electrodes)
– Too many control pins ⇒ high fabrication cost
– Wiring plan not available
PCB design: 250 um via hole, 500 um x 500 um electrode
Via Holes
Wires
Nevertheless, we need high-throughput and low cost:
DNA sequencing (106 base pairs), Protein crystallization (103 candidate conditions)
Disposable, marketability, $1 per chip
50
25

26. Pin-Constrained Biochip Design
• Cross-referencing
Orthogonally placed pins on top and bottom plates
Advantage
k = n x m pins n + m pins for an n x m microfluidic array
Disadvantage
Suffer from electrode interference
51
Electrode Interference
• Unintentional Electrode Actuation
Selected column and row pins may intersect at multiple electrodes
• Unintentional Droplet Manipulation
1
2
1
3
Unintentional
3
4
destination cells
5
6
7 destination cells
8
2
9
10
1 2 3 4 5 6 7 8 9 10
52
26

27. Efficient (Concurrent) Droplet
Manipulation
• Goal: Improve droplet manipulation concurrency on
cross-referencing-based biochips.
9 steps needed if
moving one droplet
at a time (too slow)
53
Efficient Droplet Manipulation
• Observation
– Droplet manipulations whose destination cells belongs to the same
column/row can be carried out without electrode interferences.
4 9
destination cells
54
27

28. Efficient Droplet Manipulation
• Methodology
– Group droplet manipulations according to their destination cells
– All manipulations in a group can be executed simultaneously
The goal is to find an optimal grouping plan which
results in the minimum number of groups.
55
Efficient Droplet Manipulation
• Problem formulation
Destination cells Nodes
Destination cells in one column/row a clique
Grouping Clique partitioning
Optimal grouping Minimal clique-partitioning (NP-Complete)
56
28

29. Broadcast Electrode-Addressing
• Observation
“Don’t-Cares” in Electrode-Actuation Sequences
Electrode control inputs: 3 values
“1” –- activated
“0” –- deactivated
“x” –- can be either “1” or “0”
Therefore, activation sequences
can be combined by interpreting “x” Floating electrode
Example: A droplet routed
Corresponding electrode activation
counterclockwise on a loop of electrodes
sequences
57
Solution Based on Clique Partitioning
• Idea
– Combining compatible sequences to reduce # of control pins
• Clique partitioning based method
Electrodes Nodes
Electrodes with compatible activation sequences a clique
Optimal combination Minimal clique-partitioning
58
29

30. Solution Based on Clique Partitioning
Reduced number
Bioassay synthesis
of control pins
results
Extract Combine
Scheduling & Clique partitioning
droplet routing plan Result
Calculate Generate
Map
Activation sequence
Undirected graph
for each electrode
59
Application to a Multiplexed Bioassay
A biochip target execution of a Sequencing graph model of the
multiplexed assay multiplexed assay
• A glucose assay and a lactate assay based on colorimetric enzymatic reactions
• 4 pairs of droplets – {S1, R1}, {S1, R2}, {S2, R1}, {S2, R2}, are mixed in the mixer in
the middle of the chip, the mixed droplets are routed to the detector for analysis
60
30

31. Results
132 s
73 s
73 s
Comparison of bioassay completion time using different addressing methods
Addressing Broadcast Array-partitioning- Cross-referencing-
methods addressing based method based method
# of control pins 25 35 30
61
Application to Multi-functional
Chip
• Multi-functional Chip
– biochips targeting the execution of a set of (multiple) predetermined
bioassays
• Application of Broadcast Addressing to Multi-functional Chips
Key idea: treat the union of the target bioassays as a single
bioassay
– Collect droplet routing and schedule information for each target
bioassay
– Calculate activation sequences for each bioassay
– Merge the activation sequences from the different assays and obtain a
collective activation sequence for each electrode
– Note that merging of activation sequences can be carried out in any
arbitrarily-chosen order
62
31

32. Addressing Results
Sequencing graph model of the
multiplexed assay
Sequencing graph model of protein
dilution
Sequencing graph model of
Polymerase Chain Reaction (PCR)
63
Addressing Results
Chip layout and broadcast-
addressing result for the
multi-functional chip for
1. Multiplexed assay
2. PCR assay
3. Protein dilution assay
Total number of control pins: 37
The addition of two assays to the biochip for the multiplexed assay
leads to only 13 extra control pins
64
32

33. Reconfigurability
• Common microfluidic operations
– Different modules with different performance levels (e.g., several
mixers for mixing)
– Reconfiguration by changing the control voltages of the
corresponding electrodes
65
Reconfiguration and Graceful Degradation
• Reconfigure the faulty module
– Avoid defects (faulty cells)
• Reconfiguration: bypass faulty cells
– No spare cells; use fault-free unused cells
• Defect tolerance in design procedure (increase in design complexity)
– Incorporate physical redundancy in the array
• Spare cells replace defective cells (local reconfiguration,
application-independent)
•
66
33

34. Testing of Digital Microfluidics Biochips
Stimuli: Test droplets; Response: Presence/absence of droplets
No.
Cause of Defect Fault Observable
defect type cells model error
Dielectric Droplet-electrode Droplet undergoes
Excessive 1
short (short between
actuation breakdown electrolysis; prevents
the droplet and the
voltage further
applied to electrode) transportation
electrode
Irreversible Electrode-stuck-on Unintentional droplet
Electrode 1
charge (electrode remains
actuation for operations or
concentration on
excessive constantly activated) stuck droplets
duration electrode
Excessive Misalignment of Pressure gradient (net
1 Droplet transportation
mechanical parallel plates static pressure in without activation voltage
force applied (electrodes and some direction)
to chip ground plane)
Non-uniform Fragmentation of droplets
Coating 1 Dielectric islands
(islands of Teflon and their motion is
failure dielectric layer
coating) prevented
67
More Defects in Digital Microfluidic Biochips
No. Fault
Cause of Defect Observable
defect type cells model error
Floating droplets
Abnormal Grounding 1 Failure of droplet
(droplet not
metal layer failure transportation
deposition anchored )
and etch Electrode open
Broken wire to 1 Failure to activate the
variation (actuation not
Control source electrode for droplet
during possible) transportation
fabrication
Electrode short
Metal connection 2 A droplet resides in the
(short between middle of the two shorted
between adjacent
electrodes, and its transport
electrodes electrodes)
cannot be achieved
Particle Particle connects 2 Electrode short
contamination or two adjacent
liquid residue electrodes
Protein Sample residue Resistive open at Droplet transportation is
1
absorption on electrode electrode impeded.
during bioassay surface Assay results are outside the
Contamination
range of possible outcomes
68
34

35. Electrical Detection Mechanism 10 K
Output
Periodic
• Minimally invasive 150 pF
square
• Easy to implement (alleviate 74C14
waveform
the need for external devices) Droplet
+5V
1N914
• Fault effect should be
unambiguous 5K
1N5231
5.1V
1N914
Electrically control and
track test stimuli droplets Gnd
Capacitive changes reflected in electrical signals (Fluidic
• If there is a droplet, domain to electrical domain)
output=1; otherwise,
output=0
• Fault-free : there is a
droplet between sink
electrodes
Faulty: there is no
droplet.
69
Defect-Oriented Experiment
• Understand the impact of certain defects on droplet flow, e.g., for
short-circuit between two electrodes
• Experimental Setup
– To evaluate the effect of an electrode short on microfluidic behavior
70
35

36. Conclusions
• Digital microfluidics offers a viable platform for lab-on-chip for clinical
diagnostics and biomolecular recognition
• Design automation challenges
– Automated synthesis: scheduling, resource binding, module placement; droplet
routing; testing and reconfiguration
• Bridge between different research communities: bioMEMS, microfluidics,
electronics CAD and chip design, biochemistry
• Growing interest in the electronics CAD community
– Special session on biochips at CODES+ISSS’2005 (appears in CFP now)
– Special issue on biochips in IEEE Transactions on CAD (Feb 2006), IEEE Design &
Test of Computers (Jan/Feb’07)
– Workshop on biochips at DATE’06
– Tutorials on digital microfluidic lab-on-chip at DATE’07, ISCAS’08, VDAT 2007;
embedded tutorial at VLSI Design 2005
– Other notable activities in digital microfluidics: University of California at Los
Angeles, University of Toronto, Drexel University, IMEC (Belgium), Freiburg
(Germany), Philips (Netherlands), Fraunhofer Institute (Berlin, Germany), and
many more….
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37. ISBN: 0849390095
2006 X, 406 p. Hardcover Publication Date: 10/5/2006, 248 p.
ISBN-10: 1-4020-5122-0, ISBN-13: 978-1-4020-5122-7
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