Preface
Microfluidics deals with the manipulation of small amounts of fluids (in
the order of few micro- to pico-liters) and finds a broad application in
(bio-)chemistry, biology, pharmacology, and food industries. Most prominently
known as Lab-on-a-Chip (LoC), corresponding devices minimize, integrate,
automate, and parallelize typical lab operations such as mixing, heating, incubation,
etc. on a single device.
In order to implement a microfluidic device, droplet microfluidic networks
provide a well-established and highly potential platform because droplets are
especially suited to encapsulate biological samples like cells, proteins, or DNA. In
this platform, the droplets are injected in a continuous, immiscible phase and flow
through closed microchannels to modules executing operations on the droplets—
eventually realizing a (bio-)chemical experiment.
However, when designing a droplet microfluidic network implementing the
required operations, a huge number of physical parameters need to be considered
(e.g., the dimensions of the channels, flow rates, the applied phases, etc.), which all
depend on and affect each other. This results in a complex task, where, thus far, the
designer often has very few methods to derive a design or even to simply validate
whether it works as intended. In fact, in order to test and validate a design, currently,
several prototypes are produced on which physical experiments are conducted to test
the functionality. In case these prototypes do not show the intended functionality,
the entire design process has to be reiterated again. This “trial-and-error” approach
yields a long design time and high costs.
In order to change this current state of the art and to support the designer, this
book presents automatic methods for the design of droplet microfluidic networks.
To this end, this book contributes simulation and design methods which support the
design process of droplet microfluidics in general as well as design methods for a
dedicated droplet routing mechanism, namely, passive droplet routing.
The presented methods allow for (1) simulating a microfluidic design on a high
abstraction level, which facilitates an early validation of whether a design indeed
works as intended, (2) automatically dimensioning a microfluidic design so that constraints like flow conditions are satisfied, and (3) automatically generating meander
v
Microfluidics deals with the manipulation of small amounts of fluids (in
the order of few micro- to pico-liters) and finds a broad application in
(bio-)chemistry, biology, pharmacology, and food industries. Most prominently
known as Lab-on-a-Chip (LoC), corresponding devices minimize, integrate,
automate, and parallelize typical lab operations such as mixing, heating, incubation,
etc. on a single device.
In order to implement a microfluidic device, droplet microfluidic networks
provide a well-established and highly potential platform because droplets are
especially suited to encapsulate biological samples like cells, proteins, or DNA. In
this platform, the droplets are injected in a continuous, immiscible phase and flow
through closed microchannels to modules executing operations on the droplets—
eventually realizing a (bio-)chemical experiment.
However, when designing a droplet microfluidic network implementing the
required operations, a huge number of physical parameters need to be considered
(e.g., the dimensions of the channels, flow rates, the applied phases, etc.), which all
depend on and affect each other. This results in a complex task, where, thus far, the
designer often has very few methods to derive a design or even to simply validate
whether it works as intended. In fact, in order to test and validate a design, currently,
several prototypes are produced on which physical experiments are conducted to test
the functionality. In case these prototypes do not show the intended functionality,
the entire design process has to be reiterated again. This “trial-and-error” approach
yields a long design time and high costs.
In order to change this current state of the art and to support the designer, this
book presents automatic methods for the design of droplet microfluidic networks.
To this end, this book contributes simulation and design methods which support the
design process of droplet microfluidics in general as well as design methods for a
dedicated droplet routing mechanism, namely, passive droplet routing.
The presented methods allow for (1) simulating a microfluidic design on a high
abstraction level, which facilitates an early validation of whether a design indeed
works as intended, (2) automatically dimensioning a microfluidic design so that constraints like flow conditions are satisfied, and (3) automatically generating meander
v