36
3 Simulating Droplet Microfluidic Networks
system. The size of the equation system depends on the size of the microfluidic
network.
This equation system has to be re-solved when any of the events discussed above
is triggered by any droplet. More precisely, an event is triggered when
• a new droplet is injected,
• a droplet leaves the network,
• a droplet enters another edge,
• a droplet is trapped in the microfluidic network,
• a droplet is squeezed through any gap (which usually terminates the simulation),
and
• a droplet starts or stops clogging a channel.
Overall, these event-based re-calculations of the equation system make the
proposed advanced simulation framework efficient. This allows to simulate large
microfluidic networks within negligible computation times.
3.3.5 Evaluation
The simulation framework proposed in this section is publicly available at http://iic.
jku.at/eda/research/microfluidics_simulation/. The resulting tool addresses the main
shortcomings of the current state of the art, e.g., by being
• dedicated to droplet microfluidics (it does not require the translation to the
electrical domain or the utilization of non-domain-specific tools such as SPICE),
• applicable for practically relevant networks as the framework now supports
important physical phenomena,
• publicly available, and
• easily accessible and extendible.
By this, the resulting framework has the potential to establish simulation in the
design of droplet microfluidic networks. In the following, the evaluations are
summarized, which check the correct simulation of those physical phenomena.
A main characteristic of the proposed simulation framework (which is essential
to make the approach broadly applicable for practically relevant applications as
discussed in Sect. 3.3.2) is its direct support of several physical phenomena, which
have not been supported yet. To demonstrate the working principle of the proposed
simulator, small networks are simulated which require the corresponding features.
More precisely, networks composed of (1) a channel connected to a single trapping
well and (2) a channel to which a perpendicular channel is connected are used. For
both networks, similar specifications summarized in Table 3.1 are used.
The accordingly obtained simulation results are, respectively, provided in
Figs. 3.8 and 3.9 for selected time steps. The figures show the determined position
of a droplet at each particular time as well as the instantaneous volumetric flow
rates (provided in μ l/min) in each channel.
3 Simulating Droplet Microfluidic Networks
system. The size of the equation system depends on the size of the microfluidic
network.
This equation system has to be re-solved when any of the events discussed above
is triggered by any droplet. More precisely, an event is triggered when
• a new droplet is injected,
• a droplet leaves the network,
• a droplet enters another edge,
• a droplet is trapped in the microfluidic network,
• a droplet is squeezed through any gap (which usually terminates the simulation),
and
• a droplet starts or stops clogging a channel.
Overall, these event-based re-calculations of the equation system make the
proposed advanced simulation framework efficient. This allows to simulate large
microfluidic networks within negligible computation times.
3.3.5 Evaluation
The simulation framework proposed in this section is publicly available at http://iic.
jku.at/eda/research/microfluidics_simulation/. The resulting tool addresses the main
shortcomings of the current state of the art, e.g., by being
• dedicated to droplet microfluidics (it does not require the translation to the
electrical domain or the utilization of non-domain-specific tools such as SPICE),
• applicable for practically relevant networks as the framework now supports
important physical phenomena,
• publicly available, and
• easily accessible and extendible.
By this, the resulting framework has the potential to establish simulation in the
design of droplet microfluidic networks. In the following, the evaluations are
summarized, which check the correct simulation of those physical phenomena.
A main characteristic of the proposed simulation framework (which is essential
to make the approach broadly applicable for practically relevant applications as
discussed in Sect. 3.3.2) is its direct support of several physical phenomena, which
have not been supported yet. To demonstrate the working principle of the proposed
simulator, small networks are simulated which require the corresponding features.
More precisely, networks composed of (1) a channel connected to a single trapping
well and (2) a channel to which a perpendicular channel is connected are used. For
both networks, similar specifications summarized in Table 3.1 are used.
The accordingly obtained simulation results are, respectively, provided in
Figs. 3.8 and 3.9 for selected time steps. The figures show the determined position
of a droplet at each particular time as well as the instantaneous volumetric flow
rates (provided in μ l/min) in each channel.