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Proceedings ArticleDOI

Digital Microfluidic Biochips: A Vision for Functional Diversity and More than Moore

03 Jan 2010-pp 452-457
TL;DR: This embedded tutorial paper provides an overview of droplet-based “digital” microfluidic biochips and describes emerging computer-aided design (CAD)tools for the automated synthesis and optimization of bioch chips from bioassay protocols.
Abstract: Microfluidics-based biochips are revolutionizing high-throughput sequencing, parallel immunoassays, clinical diagnostics, and drug discovery. These devices enable the precise control of nanoliter volumes of biochemical samples and reagents. Compared to conventional laboratory procedures, which are cumbersome and expensive, miniaturized biochips offer the advantages of higher sensitivity, lower cost due to smaller sample and reagent volumes, system integration, and less likelihood of human error. This embedded tutorial paper provides an overview of droplet-based “digital” microfluidic biochips. It describes emerging computer-aided design (CAD)tools for the automated synthesis and optimization of biochips from bioassay protocols. Recent advances in fluidic-operation scheduling, module placement, droplet routing, pin-constrained chip design, and testing are presented.

Summary (3 min read)

Introduction

  • Continued growth in this emerging field depends on advances in chip/system integration.
  • Recent advances on fluidic-operation scheduling, module placement, droplet routing, testing, and dynamic reconfiguration are also presented.
  • Section II describes biochip technology platforms, including digital microfluidics.
  • Early biochips were based on the concept of a DNA microarray, which is a piece of glass, plastic or silicon substrate on which pieces of DNA, i.e., probes, have been affixed.

A. Continuous-Flow Microfluidics

  • Traditional (continuous-flow) microfluidic technologies are based on the continuous flow of liquid through microfabricated channels [5, 7-8].
  • Inherently difficult to integrate because the parameters that govern flow field (e.g. pressure, fluid resistance, electric field strength) vary along the flow-path, making the flow at any location dependent upon the properties of the entire system.
  • Moreover, unavoidable shear flow and diffusion in microchannels make it difficult to eliminate intersample contamination and dead volumes.
  • Furthermore, since structure and functionality are so tightly coupled, each system is only appropriate for a narrow class of applications.

B. Digital Microfluidics

  • A digital microfluidic biochip utilizes electrowetting on dielectric (EWOD) to manipulate and move microliter or nanoliter droplets containing biological samples on a twodimensional electrode array [2, 9-12].
  • A unit cell in the array includes a pair of electrodes that acts as two parallel plates.
  • By varying the patterns of control-voltage activation, fluid-handling operations such as droplet merging, splitting, mixing, and dispensing can be easily executed.
  • To address the need for low-cost, PCB technology has been employed for inexpensive fabrication.
  • The authors examine a progression of CAD problems related to biochip synthesis.

A. Scheduling and Module Placement

  • Recent years have seen growing interest in the automated design and synthesis of microfluidic biochips [13, 19, 21, 25- 29].
  • Algorithms are used for unified resource binding, operation scheduling, and module placement.
  • The design is improved through a series of genetic evolutions based on PRSA.
  • It generates an optimized schedule of bioassay operations, the binding of assay operations to resources, and a layout of the microfluidic biochip.
  • A microfluidic module containing a faulty unit cell can easily be relocated to another part of the microfluidic array by changing the control voltages applied to the corresponding electrodes.

A. Droplet-Trace-Based Array Partitioning

  • An array-partitioning-based pin-constrained design method of digital microfluidic biochips proposed in [22].
  • This method uses array partitioning and careful pin assignment to reduce the number of control pins.
  • The droplet trace, defined as the set of cells traversed by a single droplet, serves as the basis for generating the array partitions.
  • Sets of pins from an “overlapping” partition cannot be used in the overlapped region since the reuse of the pins may lead to droplet interference.
  • This method requires detailed information about the scheduling of assay operations, microfluidic module placement, and droplet routing pathways.

B. Cross-Referencing-Based Droplet Manipulation

  • An alternative design method based on a cross-reference driving scheme is presented in [26, 30].
  • This method allows control of an N×M grid array with only N+M control pins.
  • The key idea is to group the droplet movements according to their destination cells.
  • The manipulation of multiple droplets is ordered in time; droplets in the same group can be moved simultaneously without electrode interference, but the movements for the different groups must be sequential.
  • The problem of finding the minimum number of groups can be directly mapped to the problem of determining a minimal clique partition from graph theory.

C. Broadcast-Addressing Method

  • A broadcast-addressing based design technique for pinconstrained and multi-functional biochips has been developed in [27].
  • Each electrode activation sequence contains several don’t-care terms, which can be replaced by “1” or “0”.
  • If two sequences can be made identical by careful replacing these don’t-care terms with “0” or “1”, they are referred to as compatible sequences.
  • 455 Authorized licensed use limited to: DUKE UNIVERSITY.
  • The problem of finding an optimal partition that leads to the minimum number of groups can be easily mapped to the problem of determining a minimal clique partition from graph theory.

B. Structural Test Techniques

  • A unified test methodology for digital microfluidic biochips has recently been presented, whereby faults can be detected by controlling and tracking droplet motion electrically [14].
  • Even though most catastrophic faults lead to a complete cessation of droplet transportation, there exist differences between their corresponding erroneous behaviors.
  • To test for the electrode-open fault, it is sufficient to move a test droplet from any adjacent cell to the faulty cell.
  • More recently, a cost-effective testing methodology referred to as “parallel scan-like test” has been proposed [24].
  • The method is named thus because it manipulates multiple test droplets in parallel to traverse the target microfluidic array, just as test stimuli can be applied in parallel to the different scan chains in an integrated circuit.

C. Functional Testing Techniques

  • Functional testing involves test procedures to check whether groups of cells can be used to perform certain operations, e.g., droplet mixing and splitting.
  • For the test of a specific operation, the corresponding patterns of droplet movement are carried out on the target cluster of cells.
  • Functional test methods to detect the defects and malfunctions have recently been developed.
  • The authors have presented a survey of research on design automation and test techniques for digital microfluidic biochips.
  • Practical design techniques for achieving high throughout with a small number of control pins have been presented.

ACKNOWLEDGMENT

  • The author thanks colleagues at Duke University and Advanced Liquid Logic, Inc., who have contributed to this work.
  • They include Fei Su, Tao Xu, Yang Zhao, William Hwang, Phil Paik, Vamsee Pamula, and Richard Fair.

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Digital Microfluidic Biochips: A Vision for
Functional Diversity and More than Moore
Krishnendu Chakrabarty
Department of Electrical and Computer Engineering
Duke University. Durham, NC 27708, USA
Abstract—Microfluidics-based biochips are revolutionizing high-
throughput sequencing, parallel immunoassays, clinical
diagnostics, and drug discovery. These devices enable the precise
control of nanoliter volumes of biochemical samples and
reagents. Compared to conventional laboratory procedures,
which are cumbersome and expensive, miniaturized biochips
offer the advantages of higher sensitivity, lower cost due to
smaller sample and reagent volumes, system integration, and less
likelihood of human error. This embedded tutorial paper
provides an overview of droplet-based “digital” microfluidic
biochips. It describes emerging computer-aided design (CAD)
tools for the automated synthesis and optimization of biochips
from bioassay protocols. Recent advances in fluidic-operation
scheduling, module placement, droplet routing, pin-constrained
chip design, and testing are presented.
I. INTRODUCTION
Advances in digital microfluidics have led to the promise of
miniaturized biochips for applications such as immunoassays
for point-of-care medical diagnostics, DNA sequencing, and
the detection of airborne particulate matter [1-4]. These
devices enable the precise control of nanoliter droplets of
biochemical samples and reagents, and integrated circuit (IC)
technology can be used to transport and process “biochemical
payload” in the form of tiny droplets. Biochips facilitate the
convergence of electronics with the life sciences, and they
integrate on-chip various bioassay operations, such as sample
preparation, analysis, separation, and detection [2]. Compared
to conventional laboratory procedures, which are cumbersome
and expensive, miniaturized biochips offer the advantages of
higher sensitivity, lower cost due to smaller sample and
reagent volumes, system integration, and less likelihood of
human error. As a result, non-traditional biomedical
applications and markets are opening up fundamentally new
uses for ICs.
However, continued growth in this emerging field depends
on advances in chip/system integration. In particular, design
methods are needed to ensure that biochips are as versatile as
the macro-labs that they are intended to replace. The few
commercial biochips available today (e.g., from Agilent,
Fluidigm, Caliper, I-Stat, BioSite, etc.) are specific to an
application and they offer no flexibility to the user. Intel
recently announced the Health Guide PHS6000 product for
home patients, but the underlying technology does not exploit
the benefits of reconfigurable microfluidics.
This embedded tutorial paper is focused on droplet-based
“digital” microfluidic biochips. The digital microfluidics
platform offers the flexibility of dynamic reconfigurability and
software-based control of multifunctional biochips. Next the
paper describes emerging computer-aided design (CAD) tools
for the automated synthesis and optimization of biochips from
bioassay protocols. Recent advances on fluidic-operation
scheduling, module placement, droplet routing, testing, and
dynamic reconfiguration are also presented. These techniques
allow biochip users to concentrate on the development of
nanoscale bioassays, leaving chip optimization and
implementation details to design-automation tools.
It is expected that an automated design flow will transform
biochip research and use, in the same way as design
automation revolutionized IC design in the 80s and 90s. This
approach is especially aligned with the vision of functional
diversification and “More than Moore”, as articulated in the
ITRS 2007, which highlights “Medical” as being a “System
Driver” for the future [6]. Users will adapt more easily to
emerging technology if appropriate design methods/tools and
in-system automation methods are available.
The rest of this paper is organized as follows. Section II
describes biochip technology platforms, including digital
microfluidics. Section III presents synthesis techniques,
including solutions published in the literature for operation
scheduling, module placement, and droplet routing. Section IV
describes pin-constrained chip methods. Section V presents
advances in testing, including fault models and fault detection.
Finally, Section VI concludes the paper.
II. T
ECHNOLOGY PLATFORMS
Early biochips were based on the concept of a DNA
microarray, which is a piece of glass, plastic or silicon
substrate on which pieces of DNA, i.e., probes, have been
affixed. There are a number of commercial microarrays
available in the marketplace today, e.g., GeneChip
®
DNAarray
from Affymetrix, NanoChip
®
microarray from Nanogen, and
DNA microarray from Agilent. A drawback of these arrays is
that they are “passive chips”; they are neither reconfigurable
nor can they be used for sample preparation.
The basic idea of a microfluidic biochip is to integrate all
necessary functions for biochemical analysis using
microfluidics technology. These micro-total-analysis-systems
are more versatile than microarrays. Integrated functions
include assay operations, detection, and sample preparation.
A. Continuous-Flow Microfluidics
Traditional (continuous-flow) microfluidic technologies are
based on the continuous flow of liquid through micro-
fabricated channels [5, 7-8]. Continuous-flow systems are
2010 23rd International Conference on VLSI Design
1063-9667/10 $26.00 © 2010 IEEE
DOI 10.1109/VLSI.Design.2010.33
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inherently difficult to integrate because the parameters that
govern flow field (e.g. pressure, fluid resistance, electric field
strength) vary along the flow-path, making the flow at any
location dependent upon the properties of the entire system.
Moreover, unavoidable shear flow and diffusion in
microchannels make it difficult to eliminate intersample
contamination and dead volumes. Furthermore, since structure
and functionality are so tightly coupled, each system is only
appropriate for a narrow class of applications.
B. Digital Microfluidics
A digital microfluidic biochip utilizes electrowetting on
dielectric (EWOD) to manipulate and move microliter or
nanoliter droplets containing biological samples on a two-
dimensional electrode array [2, 9-12]. A unit cell in the array
includes a pair of electrodes that acts as two parallel plates.
The bottom plate contains a patterned array of individually
controlled electrodes, and the top plate is coated with a
continuous ground electrode. A droplet rests on a hydrophobic
surface over an electrode. It is moved by applying a control
voltage to an electrode adjacent to the droplet and, at the same
time, deactivating the electrode just under the droplet. Using
interfacial tension gradients, droplets can be moved to any
location on a two-dimensional array.
The division of a volume of fluid into discrete,
independently controllable “packets” or droplets, provides
several advantages over continuous-flow. The reduction of
microfluidics to a set of basic repeated operations (i.e., “move
one unit of fluid one distance unit”) enables a cell-based
design approach. By varying the patterns of control-voltage
activation, fluid-handling operations such as droplet merging,
splitting, mixing, and dispensing can be easily executed. The
platform offers dynamic reconfigurability, since fluidic
operations can be performed anywhere on the array. Droplet
routes and operation scheduling results are programmed into a
microcontroller that drives electrodes in the array.
To address the need for low-cost, PCB technology has been
employed for inexpensive fabrication. Using a copper layer for
the electrodes, solder mask as the insulator, and a Teflon AF
coating for hydrophobicity, the microfluidic array can be
fabricated using an existing PCB process.
III. S
YNTHESIS METHODS
In this section, we examine a progression of CAD problems
related to biochip synthesis.
A. Scheduling and Module Placement
Recent years have seen growing interest in the automated
design and synthesis of microfluidic biochips [13, 19, 21, 25-
29]. Optimization goals here include the minimization of assay
completion time, minimization of chip area, and higher defect
tolerance. The minimization of the assay completion time is
essential for environmental monitoring applications where
sensors can provide early warning. Real-time response is also
necessary for surgery and clinical diagnostics. Finally,
biological samples are sensitive to the environment and to
temperature variations, and it is difficult to maintain an
optimal clinical or laboratory environment on chip.
One of the first published methods for biochip synthesis
decoupled high-level synthesis from physical design [13].
Architectural-level synthesis for microfluidic biochips can be
viewed as the problem of scheduling assay functions and
binding them to a given number of resources so as to
maximize parallelism, thereby decreasing response time. A
behavioral model for a set of bioassays is first obtained from
their laboratory protocols. Architectural-level synthesis is then
used to generate a macroscopic structure of the biochip.
Geometry-level synthesis (physical design) addresses the
placement of resources and the routing of droplets to satisfy
objectives such as area or throughput. It creates the final
layout of the biochip, consisting of the placement of
microfluidic modules such as mixers and storage units, the
routes that droplets take between different modules, and other
geometrical details [21].
Input:
Output:
Sequencing graph
of bioassay
Digital microfluidic
module library
Mixing components
Area
2x2-array mixer
2x3-array mixer
2x4-array mixer
1x4-array mixer
Detectors
LED+Photodiode
4 cells
6 cells
8 cells
4 cells
1 cell
Design
specifications
Maximum array area
A
max: 20x20 array
Maximum number of
optical detectors: 4
Maximum bioassay
completion time T
max:
50 seconds
Resource binding
Schedule
O1
O2
O3
O4
0
1
2
3
4
5
6
7
Placement
O1
Mix
Mix
Mix
Store
Store
O2
O3
O4
O5
O6
Detection
ResourceOperation
2x3-array mixer
2x4-array mixer
1x4-array mixer
Storage unit (1 cell)
LED+Photodiode
O1
O2
O3
O4
O5
O6
Storage unit (1 cell)
O1
O2
O3
O4
O5
O6
Biochip design results:
Array area: 8x8 array Bioassay completion time: 25 seconds
Unified Synthesis of Digital Microfluidic Biochip
Time
10 s
6 s
3 s
5s
30 s
Number of reservoirs: 3
Fig. 1. An example illustrating system-level synthesis [16].
A key problem in the geometry-level synthesis of biochips
is the placement of microfluidic modules such as different
types of mixers and storage units. Since digital microfluidics-
based biochips enable dynamic reconfiguration of the
microfluidic array during run-time, they allow the placement
of different modules on the same location during different
time intervals. A simulated annealing-based heuristic approach
has been developed to solve the NP-complete problem in a
computationally efficient manner [21].
Architectural synthesis is based on rough estimates for
placement costs such as the area of the microfluidic modules.
These estimates provide lower bounds on the exact biochip
area, since the overheads due to spare cells and cells used for
droplet transportation are not known a priori. However, it
cannot be accurately predicted if the biochip design meets
system specifications, e.g., maximum allowable array area and
upper limits on assay completion times, until both high-level
synthesis and physical design are carried out. [16] proposed a
unified system-level synthesis method for microfluidic
biochips based on parallel recombinative simulated annealing
(PRSA), which offers a link between these two steps.
The design flow is illustrated in Fig. 1. First, the different
bioassay operations (e.g. mixing and dilution), and their
mutual dependences are represented using a sequencing graph.
Next, a combination of simulated annealing and genetic
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algorithms are used for unified resource binding, operation
scheduling, and module placement. A chromosome is used to
represent each candidate solution, i.e., a design point. In each
chromosome, operations are randomly bound to resources.
Based on the binding results, list scheduling is used to
determine the start times of operations, i.e., each operation
starts with a random latency after its scheduled time. Finally, a
module placement is derived based on the resource binding
and the schedule of fluidic operations. A weighted sum of
area- and time-cost is used to evaluate the quality of the
design. The design is improved through a series of genetic
evolutions based on PRSA. It generates an optimized schedule
of bioassay operations, the binding of assay operations to
resources, and a layout of the microfluidic biochip.
Efficient reconfiguration techniques have been developed to
bypass faulty unit cells in the microfluidic array. A
microfluidic module containing a faulty unit cell can easily be
relocated to another part of the microfluidic array by changing
the control voltages applied to the corresponding electrodes.
Defect tolerance can also be achieved by including redundant
elements in the system; these elements can be used to replace
faulty elements through reconfiguration techniques [17].
Another method is based on graceful degradation, in which all
elements in the system are treated in a uniform manner, and no
element is designated as a spare [18].
The top-down synthesis flow described above unifies
architecture level design with physical-level module
placement. However, it suffers from two drawbacks. For
operation scheduling, it is assumed that the time cost for
droplet routing is negligible, which implies that droplet
routing has no influence on the operation completion time.
While generating physical layouts, the synthesis tool in [16]
provides only the layouts of the modules and it leaves droplet
routing pathways unspecified. The assumption of negligible
droplet transportation times is valid for small microfluidic
arrays. However, for large arrays and for biochemical
protocols that require several concurrent fluidic operations on-
chip, the droplet transportation time is significant and routing
complexity is non-trivial. This problem is addressed in the
next subsection.
B. Droplet Routing
A key problem in biochip physical design is droplet routing
between modules, and between modules and I/O ports (i.e.,
on-chip reservoirs). The dynamic reconfigurability inherent in
digital microfluidics allows different droplet routes to share
cells on the microfluidic array during different time intervals.
In this sense, the routes in microfluidic biochips can be viewed
as virtual routes, which make droplet routing different from
the classical wire VLSI routing problem.
The first method for droplet routing in biochips was
published in [19]. The main objective in routing is to find
droplet routes with minimum lengths, where route length is
measured by the number of cells in the path from the starting
point to the destination.
During droplet routing, a minimum spacing between
droplets must be maintained to prevent accidental mixing,
except for the case when droplet merging is desired (e.g., in 3-
pin nets). Fluidic constraint rules in [19] need to be satisfied in
order to avoid undesirable mixing. The microfluidic modules
placed on the array are viewed as obstacles in droplet routing.
In order to avoid conflicts between droplet routes and assay
operations, a segregation region is added to wrap around the
functional region of microfluidic modules. Another constraint
in droplet routing is given by an upper limit on droplet
transportation time. The delay for each droplet route should
not exceed some maximum, e.g., 10% of a time-slot used in
scheduling, in order that the droplet-routing time can be
ignored for scheduling assay operations [16].
Since a digital microfluidic array can be reconfigured
dynamically at run-time, a series of 2-D placement
configurations of modules in different time spans are obtained
in the module placement phase [48]. Therefore, the droplet
routing is decomposed into a series of sub-problems. A
complete droplet-routing solution is obtained by solving these
sub-problems sequentially.
Based on this problem formulation, a two-stage routing
method has been proposed in [21]. In the first stage, M
alternative routes for each net are generated. In the second
stage, a single route from the M alternatives for each net is
selected independent of the routing order of nets. This method
also exploits the features of dynamic reconfigurability and
independent controllability of electrodes to modify droplet
pathways to override potential violation of fluidic constraints.
Droplet routing should be considered in the synthesis flow
for digital microfluidics, in order to generate a routable
synthesized design for the availability of routing paths. [25]
proposed a method to incorporate droplet-routability in the
PRSA-based synthesis flow. This method estimates the
droplet-routability using two metrics. It adopts the average
module distance (over all interdependent modules) as the first
design metric to guarantee the routability of modules in the
synthesized biochip. It also adopts the maximum module
distance as the second design metric to approximate the
maximum length of droplet manipulation. Since synthesis
results with high routability values are more likely to lead to
simple and efficient droplet pathways, this method
incorporates the above two metrics into the fitness function by
a factor that can be fine-tuned according to different design
specifications to control the PRSA-based procedure. For each
chromosome considered in the PRSA-based synthesis flow,
this method calculates both the average and maximum module
distance. Candidate designs with low routability are discarded
during evolution. Thus, the synthesis procedure guarantees
that the routing complexity is reduced for the synthesized
biochip, while meeting constraints on array size and bioassay
processing time.
We ran the defect-tolerant routing-aware and defect-
oblivious routing-aware algorithms under a set of
combinations of weights in the fitness function for a protein
assay example. We carried out random defect injection into
each design and obtain its failure rate. We mapped each design
G to a 3D point (T
G
, A
G
, F
G
), where T
G
, A
G
, F
G
are completion
time, chip area, and failure rate of the design, respectively. A
point (T
G
, A
G
, F
G
) is referred to as a feasibility boundary point
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if there are no other points (T
m
, A
m
, F
m
) such that T
m
< T
G
, A
m
< A
G
, and F
m
< F
G
. A feasibility frontier surface is obtained
by connecting all the feasibility boundary points, as shown in
Fig. 2. The feasible design region corresponds to the space
above the feasible surface. Any design specification can be
met whose corresponding is point located in this region;
otherwise, no feasible design exists for this specification. As
shown in Fig. 2, defect-tolerant routing-aware synthesis leads
to a lower-feasibility frontier surface and a larger feasible
design space as compared to the defect-oblivious method.
IV. P
IN-CONSTRAINED CHIP DESIGN
Electrode addressing is an important problem in biochip
design. It refers to the manner in which electrodes are
connected to and controlled by input pins. Early design-
automation techniques relied on the availability of a direct-
addressing scheme. For large arrays, direct-addressing
schemes lead to a large number of control pins, and the
associated interconnect routing problem significantly adds to
the product cost. In this section, we describe a number of pin-
constrained biochip design methods.
A. Droplet-Trace-Based Array Partitioning
An array-partitioning-based pin-constrained design method
of digital microfluidic biochips proposed in [22]. This method
uses array partitioning and careful pin assignment to reduce
the number of control pins. The key idea is to “virtually”
partition the array into regions. The partitioning criterion here
is to ensure at most one droplet is included in each partition.
The droplet trace, defined as the set of cells traversed by a
single droplet, serves as the basis for generating the array
partitions. The droplet trace can be easily extracted from the
droplet routing information and the placement of the modules
to which it is routed. If droplets traces intersect on the array,
the partitions derived by this method overlap in some regions.
Sets of pins from an “overlapping” partition cannot be used in
the overlapped region since the reuse of the pins may lead to
droplet interference. The solution to this problem is to make
the overlapping region a new partition, referred to as the
overlapping partition, and use direct addressing (one-to-one
mapping) for it. An efficient algorithm for mapping control
pins to the electrodes in a partition has also been developed.
The above approach can be integrated into the droplet-trace-
based array partitioning method to generate droplet-
interference-free layouts with a minimum number of pins.
However, this method requires detailed information about the
scheduling of assay operations, microfluidic module
placement, and droplet routing pathways. Thus, the array
design in such cases is specific to a target biofluidic
application.
B. Cross-Referencing-Based Droplet Manipulation
An alternative design method based on a cross-reference
driving scheme is presented in [26, 30]. This method allows
control of an N×M grid array with only N+M control pins. The
electrode rows are patterned on both the top and bottom plates,
and placed orthogonally. However, due to electrode
interference, this design cannot handle the simultaneous
movement of more than two droplets. For the concurrent
manipulation of multiple droplets on a cross-referencing-based
biochip, multiple row and column pins must be selected to
activate the destination cells, i.e., cells to which the droplets
are supposed to move. However, the selected row and column
pins may also result in the activation of cells other than the
intended droplet destinations.
A solution based on destination-cell categorization has been
proposed to tackle the above problem. The key idea is to group
the droplet movements according to their destination cells. A
group consists of droplets whose destination cells share the
same column or row. In this way, the manipulation of multiple
droplets is ordered in time; droplets in the same group can be
moved simultaneously without electrode interference, but the
movements for the different groups must be sequential. The
problem of finding the minimum number of groups can be
directly mapped to the problem of determining a minimal
clique partition from graph theory. A linear-time heuristic
algorithm based on row-scanning and column-scanning has
been used to derive the clique partitions.
C. Broadcast-Addressing Method
A broadcast-addressing based design technique for pin-
constrained and multi-functional biochips has been developed
in [27]. To execute a specific bioassay, routing and scheduling
information must be stored in the form of electrode activation
sequences, where each bit representing the status of the
electrode at a specific time-step. The status can be either “1”
(activate), “0” (deactivate) or F” (floating). The “floating”
status is represented using the symbol “x” and refer to it as
“don’t-care”. Each electrode activation sequence contains
several don’t-care terms, which can be replaced by “1” or “0”.
If two sequences can be made identical by careful replacing
these don’t-care terms with “0” or “1”, they are referred to as
compatible sequences. Compatible sequences can be generated
from a single signal source.
Defect-oblivious
routin
g
-aware
Defect-tolerant
routing-aware
Fig. 2. Feasibility frontier surface and feasible design region for defect-
tolerant and defect-oblivious routing-aware synthesis methods.
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The number of control pins can be reduced by connecting
together electrodes with mutually-compatible activation
sequences, and addressing them using a single control pin.
Therefore, the resulting electrode-access method is referred to
as a broadcast addressing. The first step here is to partition the
electrodes into groups. For all the electrodes in any group, the
corresponding activation sequences must be pairwise-
compatible. The problem of finding an optimal partition that
leads to the minimum number of groups can be easily mapped
to the problem of determining a minimal clique partition from
graph theory. The minimum number of groups yields the
minimum number of control pins.
V. T
ESTING
In this section, we describe recent advances in the testing of
digital microfluidic biochips and fault localization techniques.
A. Fault Modeling
Faults in digital microfluidic systems can be classified as
being either catastrophic or parametric. Catastrophic faults
lead to a complete malfunction of the system, while parametric
faults cause degradation in the system performance. Table I
lists some common failure sources, defects and the
corresponding fault models for catastrophic faults in digital
microfluidic lab-on-chip.
B. Structural Test Techniques
A unified test methodology for digital microfluidic biochips
has recently been presented, whereby faults can be detected by
controlling and tracking droplet motion electrically [14]. Test
stimuli droplets containing a conductive fluid (e.g., KCL
solution) are dispensed from the droplet source. These droplets
are guided through the unit cells following the test plan towards
the droplet sink, which is connected to a capacitive detection
circuit. Most catastrophic faults result in a complete cessation
of droplet transportation. Therefore, we can determine the
fault-free or faulty status of the system by simply observing the
arrival of test stimuli droplets at selected ports. An efficient test
plan ensures that testing does not conflict with the normal
bioassay, and it guides test stimuli droplets to cover all the unit
cells available for testing. The microfluidic array can be
modeled as an undirected graph, and the pathway for the test
droplet can be determined by solving the Hamiltonian path
problem.
Even though most catastrophic faults lead to a complete
cessation of droplet transportation, there exist differences
between their corresponding erroneous behaviors. For
instance, to test for the electrode-open fault, it is sufficient to
move a test droplet from any adjacent cell to the faulty cell.
The droplet will always be stuck during its motion due to the
failure in charging the control electrode. On the other hand, if
we move a test droplet across the faulty cells affected by an
electrode-short fault, the test droplet may or may not be stuck
depending on its flow direction. In [15], a solution based on
Euler paths in graphs is described for detecting electrode
shorts.
Despite its effectiveness for detecting electrode shorts,
testing based on an Euler path suffers from long test
application time. More recently, a cost-effective testing
methodology referred to as “parallel scan-like test” has been
proposed [24]. The method is named thus because it
manipulates multiple test droplets in parallel to traverse the
target microfluidic array, just as test stimuli can be applied in
parallel to the different scan chains in an integrated circuit.
A drawback of the above “structural” test methods is that
they focus only on physical defects, and they overlook module
functionality. A defect-free microfluidic array can also
malfunction in many ways. For example, a defect-free
reservoir may result in large volume variations when droplets
are dispensed from it. A splitter composed of three defect-free
electrodes may split a big droplet into two droplets with
significantly unbalanced volumes. These phenomena, referred
TABLE I
EXAMPLES OF FAULT MODELS FOR DIGITAL MICROFLUIDIC BIOCHIP [23]
Cause of defect Defect type Number
of cells
Fault model Observable error
Excessive actuation voltage
applied to an electrode
Dielectric breakdown 1 Droplet-electrode short (a
short between the droplet
and the electrode)
Droplet undergoes electrolysis, which
prevents its further transportation
Electrode actuation for
excessive duration
Irreversible charge
concentration on an electrode
1 Electrode-stuck-on (the
electrode remains constantly
activated)
Unintentional droplet operations or
stuck droplets
Excessive mechanical force
applied to the chip
Misalignment of parallel plates
(electrodes and ground plane)
1 Pressure gradient (net static
pressure in some direction)
Droplet transportation without
activation voltage
Coating failure Non-uniform dielectric layer 1 Dielectric islands (islands of
Teflon coating)
Fragmentation of droplets and their
motion is prevented
Abnormal metal layer
deposition and etch variation
during fabrication
Grounding Failure 1 Floating droplets (droplet are
not anchored )
Failure of droplet transportation
Broken wire to control source 1 Electrode open (electrode
actuation is not possible)
Failure to activate the electrode for
droplet transportation
Metal connection between two
adjacent electrodes
2
Electrode short (short
between electrodes)
A droplet resides in the middle of the
two shorted electrodes, and its
transport along one or more directions
cannot be achieved
Particle contamination or
liquid residue
A particle that connect two
adjacent electrodes
2 Electrode short
Protein adsorption during
bioassay
Sample residue on electrode
surface
1 Resistive open at electrode Droplet transportation is impeded.
Contamination Assay results are outside the range of
possible outcomes
456
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Citations
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Proceedings ArticleDOI
25 Mar 2012
TL;DR: This work provides a comprehensive integration throughout fluidic-operation scheduling, chip layout generation, control pin assignment, and wiring solution to achieve higher design performance and feasibility in digital microfluidic biochips.
Abstract: Recently, digital microfluidic biochips (DMFBs) have revolutionized many biochemical laboratory procedures and received much attention due to many advantages such as high throughput, automatic control, and low cost. To meet the challenges of increasing design complexity, computer-aided-design (CAD) tools have been involved to build DMFBs efficiently. Current CAD tools generally conduct a two-stage based design flow of fluidic-level synthesis followed by chip-level design to optimize fluidic behaviors and chip architecture separately. Nevertheless, existing fluidic-chip design gap will become even wider with a rapid escalation in the number of assay operations incorporated into a single DMFB. As more and more large-scale assay protocols are delivered in current emerging marketplace, this problem may potentially restrict the effectiveness and feasibility of the entire DMFB realization and thus needs to be solved quickly. In this paper, we propose the first fluidic-chip co-design methodology for DMFBs to effectively bridge the fluidic-chip design gap. Our work provides a comprehensive integration throughout fluidic-operation scheduling, chip layout generation, control pin assignment, and wiring solution to achieve higher design performance and feasibility. Experimental results show the effectiveness, robustness, and scalability of our co-design methodology on a set of real-life assay applications.

20 citations

Proceedings ArticleDOI
19 Dec 2011
TL;DR: The proposed method is based on ant colony optimization $(ACO)$ technique that optimizes the number of electrode usage and routing completion time simultaneously simultaneously, and experimental results show improvement in most of the cases.
Abstract: Digital micro fluidic biochip $(DMFB)$ has gained much importance in recent times, which supports various on chip biological sample analysis. The analysis is performed on a two dimensional micro array. Significant researches are going on for high performance droplet routing in DMFB using computer aided design ($CAD$) techniques. This paper proposes a bio inspired multi objective optimization technique for multiple droplet routing in single source-single destination net (two pin net) and also for dual source - single destination net (three pin net). Our proposed method is based on ant colony optimization $(ACO)$ technique that optimizes the number of electrode usage and routing completion time simultaneously. We run our algorithm on in-vitro, and some other existing benchmarks, and experimental results show improvement in most of the cases.

14 citations

Journal ArticleDOI
TL;DR: This paper presents a comprehensive survey on design automation for biochip, highlighting some recent works on bioassay analysis, resource binding, and scheduling in geometry level, and some possible future research directions.

9 citations

Proceedings ArticleDOI
19 Jun 2014
TL;DR: In this paper, symmetric bi-partitioning of a digital micro-fluidic array under test and the timing constraints of the test droplets within neighboring clusters to avoid droplet manipulation and enable effective traversal of testdroplets.
Abstract: Digital Micro-fluidic biochips promises havoc changes in the fields of clinical diagnostics, drug discovery, forensic testing and biological research as a whole. These miniaturized lab-on-chip devices needs to go through structural and functional testing for its commercial and scientific viability. Bi-partitioning a digital microfluidic array into two symmetric clusters not only reduces the overall testing time but also adds on some criticality as it uses multiple test droplets simultaneously. This paper focuses on symmetric bi-partitioning of a digital micro-fluidic array under test and the timing constraints of the test droplets within neighboring clusters to avoid droplet manipulation and enable effective traversal of test droplets.

5 citations


Cites background from "Digital Microfluidic Biochips: A Vi..."

  • ...Runtime reconfiguration of biochip cells [7] enabled them to function as storages as well as operational cells during different time periods....

    [...]

  • ...But, when a faulty cell is affected by electrode short fault, the droplet might not get stuck while flowing in a particular direction and can get stuck traversing oppositely [7]....

    [...]

Journal ArticleDOI
TL;DR: A novel test droplet routing method based on adaptive weighted particle swarm optimization (PSO) model aims to identify defective electrodes and simultaneously performs residue removal and reveals operational supremacy in terms of overall computational time and operational accuracy over some existing best known models.

5 citations

References
More filters
Journal ArticleDOI
TL;DR: In this paper, the authors report the completion of four fundamental fluidic operations considered essential to build digital microfluidic circuits, which can be used for lab-on-a-chip or micro total analysis system (/spl mu/TAS): 1) creating, 2) transporting, 3) cutting, and 4) merging liquid droplets, all by electrowetting.
Abstract: Reports the completion of four fundamental fluidic operations considered essential to build digital microfluidic circuits, which can be used for lab-on-a-chip or micro total analysis system (/spl mu/TAS): 1) creating, 2) transporting, 3) cutting, and 4) merging liquid droplets, all by electrowetting, i.e., controlling the wetting property of the surface through electric potential. The surface used in this report is, more specifically, an electrode covered with dielectrics, hence, called electrowetting-on-dielectric (EWOD). All the fluidic movement is confined between two plates, which we call parallel-plate channel, rather than through closed channels or on open surfaces. While transporting and merging droplets are easily verified, we discover that there exists a design criterion for a given set of materials beyond which the droplet simply cannot be cut by EWOD mechanism. The condition for successful cutting is theoretically analyzed by examining the channel gap, the droplet size and the degree of contact angle change by electrowetting on dielectric (EWOD). A series of experiments is run and verifies the criterion.

1,522 citations

Journal ArticleDOI
TL;DR: In this article, a microactuator for rapid manipulation of discrete microdroplets is presented, which is accomplished by direct electrical control of the surface tension through two sets of opposing planar electrodes fabricated on glass.
Abstract: A microactuator for rapid manipulation of discrete microdroplets is presented. Microactuation is accomplished by direct electrical control of the surface tension through two sets of opposing planar electrodes fabricated on glass. A prototype device consisting of a linear array of seven electrodes at 1.5 mm pitch was fabricated and tested. Droplets (0.7–1.0 μl) of 100 mM KCl solution were successfully transferred between adjacent electrodes at voltages of 40–80 V. Repeatable transport of droplets at electrode switching rates of up to 20 Hz and average velocities of 30 mm/s have been demonstrated. This speed represents a nearly 100-fold increase over previously demonstrated electrical methods for the transport of droplets on solid surfaces.

1,471 citations

Journal ArticleDOI
TL;DR: This work presents an alternative paradigm--a fully integrated and reconfigurable droplet-based "digital" microfluidic lab-on-a-chip for clinical diagnostics on human physiological fluids, and demonstrates reliable and repeatable high-speed transport of microdroplets.
Abstract: Clinical diagnostics is one of the most promising applications for microfluidic lab-on-a-chip systems, especially in a point-of-care setting. Conventional microfluidic devices are usually based on continuous-flow in microchannels, and offer little flexibility in terms of reconfigurability and scalability. Handling of real physiological samples has also been a major challenge in these devices. We present an alternative paradigm—a fully integrated and reconfigurable droplet-based “digital” microfluidic lab-on-a-chip for clinical diagnostics on human physiological fluids. The microdroplets, which act as solution-phase reaction chambers, are manipulated using the electrowetting effect. Reliable and repeatable high-speed transport of microdroplets of human whole blood, serum, plasma, urine, saliva, sweat and tear, is demonstrated to establish the basic compatibility of these physiological fluids with the electrowetting platform. We further performed a colorimetric enzymatic glucose assay on serum, plasma, urine, and saliva, to show the feasibility of performing bioassays on real samples in our system. The concentrations obtained compare well with those obtained using a reference method, except for urine, where there is a significant difference due to interference by uric acid. A lab-on-a-chip architecture, integrating previously developed digital microfluidic components, is proposed for integrated and automated analysis of multiple analytes on a monolithic device. The lab-on-a-chip integrates sample injection, on-chip reservoirs, droplet formation structures, fluidic pathways, mixing areas and optical detection sites, on the same substrate. The pipelined operation of two glucose assays is shown on a prototype digital microfluidic lab-on-chip, as a proof-of-concept.

1,124 citations

Journal ArticleDOI
01 Dec 2006-Science
TL;DR: A gene encoding a key enzyme involved in the mutualistic symbiosis occurring between termites and their gut microbiota was used as an experimental hook to discover the previously unknown ribosomal RNA–based species identity of several symbionts.
Abstract: Gene inventory and metagenomic techniques have allowed rapid exploration of bacterial diversity and the potential physiologies present within microbial communities. However, it remains nontrivial to discover the identities of environmental bacteria carrying two or more genes of interest. We have used microfluidic digital polymerase chain reaction (PCR) to amplify and analyze multiple, different genes obtained from single bacterial cells harvested from nature. A gene encoding a key enzyme involved in the mutualistic symbiosis occurring between termites and their gut microbiota was used as an experimental hook to discover the previously unknown ribosomal RNA–based species identity of several symbionts. The ability to systematically identify bacteria carrying a particular gene and to link any two or more genes of interest to single species residing in complex ecosystems opens up new opportunities for research on the environment.

730 citations

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25 Jun 2003
TL;DR: Developments that have emerged from the increasing interaction between the MEMS and microfluidics worlds, including how to integrate electrical or electrochemical function into chips for purposes as diverse as heating, temperature sensing, electrochemical detection, and pumping are explored.
Abstract: The use of planar fluidic devices for performing small-volume chemistry was first proposed by analytical chemists, who coined the term "miniaturized total chemical analysis systems" (/spl mu/TAS) for this concept. More recently, the /spl mu/TAS field has begun to encompass other areas of chemistry and biology. To reflect this expanded scope, the broader terms "microfluidics" and "lab-on-a-chip" are now often used in addition to /spl mu/TAS. Most microfluidics researchers rely on micromachining technologies at least to some extent to produce microflow systems based on interconnected micrometer-dimensioned channels. As members of the microelectromechanical systems (MEMS) community know, however, one can do more with these techniques. It is possible to impart higher levels of functionality by making features in different materials and at different levels within a microfluidic device. Increasingly, researchers have considered how to integrate electrical or electrochemical function into chips for purposes as diverse as heating, temperature sensing, electrochemical detection, and pumping. MEMS processes applied to new materials have also resulted in new approaches for fabrication of microchannels. This review paper explores these and other developments that have emerged from the increasing interaction between the MEMS and microfluidics worlds.

491 citations

Frequently Asked Questions (17)
Q1. What are the contributions in "Digital microfluidic biochips: a vision for functional diversity and more than moore" ?

This embedded tutorial paper provides an overview of droplet-based “ digital ” microfluidic biochips. 

Architectural-level synthesis for microfluidic biochips can be viewed as the problem of scheduling assay functions and binding them to a given number of resources so as to maximize parallelism, thereby decreasing response time. 

A digital microfluidic biochip utilizes electrowetting on dielectric (EWOD) to manipulate and move microliter or nanoliter droplets containing biological samples on a twodimensional electrode array [2, 9-12]. 

In order to avoid conflicts between droplet routes and assay operations, a segregation region is added to wrap around the functional region of microfluidic modules. 

A key problem in biochip physical design is droplet routing between modules, and between modules and I/O ports (i.e., on-chip reservoirs). 

The microfluidic array can be modeled as an undirected graph, and the pathway for the test droplet can be determined by solving the Hamiltonian path problem. 

Using a copper layer for the electrodes, solder mask as the insulator, and a Teflon AF coating for hydrophobicity, the microfluidic array can be fabricated using an existing PCB process. 

The dynamic reconfigurability inherent in digital microfluidics allows different droplet routes to share cells on the microfluidic array during different time intervals. 

The droplet trace, defined as the set of cells traversed by a single droplet, serves as the basis for generating the array partitions. 

A key problem in the geometry-level synthesis of biochips is the placement of microfluidic modules such as different types of mixers and storage units. 

During droplet routing, a minimum spacing between droplets must be maintained to prevent accidental mixing, except for the case when droplet merging is desired (e.g., in 3-pin nets). 

for large arrays and for biochemical protocols that require several concurrent fluidic operations onchip, the droplet transportation time is significant and routing complexity is non-trivial. 

A microfluidic module containing a faulty unit cell can easily be relocated to another part of the microfluidic array by changing the control voltages applied to the corresponding electrodes. 

For instance, to test for the electrode-open fault, it is sufficient to move a test droplet from any adjacent cell to the faulty cell. 

The authors ran the defect-tolerant routing-aware and defectoblivious routing-aware algorithms under a set of combinations of weights in the fitness function for a protein assay example. 

The authors mapped each design G to a 3D point (TG, AG, FG), where TG, AG, FG are completion time, chip area, and failure rate of the design, respectively. 

The delay for each droplet route should not exceed some maximum, e.g., 10% of a time-slot used in scheduling, in order that the droplet-routing time can be ignored for scheduling assay operations [16].