6
1 Introduction
experiments. Overall, the status quo of manually deriving the design, validating
them using prototypes, and refining them until a working design is obtained results
in high costs (financially as well as in terms of time).
In order to support the designer in this design process, Computer-Aided
Design (CAD) methods can help. Dedicated methods allow to aid the design
process, e.g., by predicting the designed functionality or by performing tasks in an
automatic way. Hence, corresponding methods make microfluidics more accessible,
reduce the costs of the design process, and allow for a rapid time-to-market. This
eventually helps microfluidics to achieve a similar development as it has been
observed in microelectronics.
The potential that corresponding CAD methods indeed allow to automate many
tasks and, by this, change the design process has been shown for the digital
microfluidic platform based on electrowetting as well as for the microfluidic
platforms based on the large-scale integration using valves. Corresponding CAD
methods support designers in tasks like modeling [87, 103], simulation [103],
testing [63, 97, 112, 131], synthesis [45, 53, 54, 62, 64, 71, 73, 82, 87, 88, 111, 113,
121, 127, 129], sample preparation [62, 89, 95, 99], and physical design [86, 97].
However, for droplet microfluidic networks, as considered in this book, the
support is limited. Basically, only first simulation methods are available which
allow to test designs before they are fabricated. These simulation methods can be
applied on high abstractions (i.e., simulations on the 1D analysis model [93, 101])
as well as with a high level of considered physical details (i.e., simulations using
methods based on Computational Fluid Dynamics [35, 128]). Although simulation
methods bear a great potential, their accessibility is still limited and their setup is
complicated—providing potential for improvement.
This book aims to change this state of the art. To this end, it contributes advanced
methods (1) for simulation and design which support the design process of droplet
microfluidic networks in general and (2) for a dedicated droplet routing mechanism,
which, eventually, can be combined to a first integrated design process.
More precisely, the methods proposed for a general application in the design
process of droplet microfluidic networks are covered in Part II of this book and
address the following tasks:
• Simulating Droplet Microfluidic Networks: Simulations allow to test and validate
a design before it is fabricated and, by this, overcome the need for multiple
prototypes and physical experiments. Furthermore, simulations allow for design
explorations in order to, e.g., determine a robust design. Depending on the stage
of the design process, an appropriate abstraction level is required, i.e. early
stages require a model having a high abstraction and later stages require a model
considering more physical details.
In this book, a simulation framework is presented, 1 which works on a high
abstraction level and, hence, can be used early in the design process. This
1 The implementation of the simulator is available at http://iic.jku.at/eda/research/microfluidics
_simulation/.
1 Introduction
experiments. Overall, the status quo of manually deriving the design, validating
them using prototypes, and refining them until a working design is obtained results
in high costs (financially as well as in terms of time).
In order to support the designer in this design process, Computer-Aided
Design (CAD) methods can help. Dedicated methods allow to aid the design
process, e.g., by predicting the designed functionality or by performing tasks in an
automatic way. Hence, corresponding methods make microfluidics more accessible,
reduce the costs of the design process, and allow for a rapid time-to-market. This
eventually helps microfluidics to achieve a similar development as it has been
observed in microelectronics.
The potential that corresponding CAD methods indeed allow to automate many
tasks and, by this, change the design process has been shown for the digital
microfluidic platform based on electrowetting as well as for the microfluidic
platforms based on the large-scale integration using valves. Corresponding CAD
methods support designers in tasks like modeling [87, 103], simulation [103],
testing [63, 97, 112, 131], synthesis [45, 53, 54, 62, 64, 71, 73, 82, 87, 88, 111, 113,
121, 127, 129], sample preparation [62, 89, 95, 99], and physical design [86, 97].
However, for droplet microfluidic networks, as considered in this book, the
support is limited. Basically, only first simulation methods are available which
allow to test designs before they are fabricated. These simulation methods can be
applied on high abstractions (i.e., simulations on the 1D analysis model [93, 101])
as well as with a high level of considered physical details (i.e., simulations using
methods based on Computational Fluid Dynamics [35, 128]). Although simulation
methods bear a great potential, their accessibility is still limited and their setup is
complicated—providing potential for improvement.
This book aims to change this state of the art. To this end, it contributes advanced
methods (1) for simulation and design which support the design process of droplet
microfluidic networks in general and (2) for a dedicated droplet routing mechanism,
which, eventually, can be combined to a first integrated design process.
More precisely, the methods proposed for a general application in the design
process of droplet microfluidic networks are covered in Part II of this book and
address the following tasks:
• Simulating Droplet Microfluidic Networks: Simulations allow to test and validate
a design before it is fabricated and, by this, overcome the need for multiple
prototypes and physical experiments. Furthermore, simulations allow for design
explorations in order to, e.g., determine a robust design. Depending on the stage
of the design process, an appropriate abstraction level is required, i.e. early
stages require a model having a high abstraction and later stages require a model
considering more physical details.
In this book, a simulation framework is presented, 1 which works on a high
abstraction level and, hence, can be used early in the design process. This
1 The implementation of the simulator is available at http://iic.jku.at/eda/research/microfluidics
_simulation/.