Beyond the data collected for the specific experiments detailed in our proof of concept section, the main results include the protocols established and levels of integration in this system.

Aquatic Environment:

○ The aquatic environment filters water and simulates key characteristics of a chosen aquatic environment. Currently this step includes the simulation of a desired pH and water turbulence, via a rotating magnetic system. The proof of concept test for the aquatic environment tested the pH simulation, but this feature can be extended to include other sensors such as salinity, ORP, and temperature. These key characteristics are important for testing biosensor efficiency in different environments.
○ In order to operate the peristaltic pumps, sensors, and fan from the raspberry pi, the code to actuate these components was integrated into the python environment.
○ Additionally, the multi-stage filtration system has two distinct filtering steps to remove large debris and smaller fibers that can clog a microfluidic chip.

Microfluidic Device 1:

Figure 1: Droplet Generation with Variation in Pump Parameters

○ The first step for operating the droplet generation microfluidic device is sampling from the aquatic environment and priming the fluid through the tubing to reach the microfluidic device. This table describes the pressures, flow rates, and time required to accurately generate droplets.
○ The microfluidic device can consistently mix the biosensor and water sample and create droplets of the same size, as shown in our proof of concept page.


○ The incubator was modularly constructed with a heat block that holds 1.5 mL and 2.0 mL test tubes. Due to the modular nature of the incubator, the current heat block can be replaced with one that holds 0.5 mL or 15 mL test tubes depending on the output volume from the droplet generation microfluidic device.
○ A closed-loop protocol controls the power supplied to the thermoelectric chip based on the temperature sensed inside the incubator. This code is actuated by an arduino that is controlled by a raspberry pi. This infrastructure combining the analog abilities of the arduino and the computing power of the raspberry pi is a key feature of the system.
○ Lastly, the incubator heats up quickly (< 30 minutes) and maintains the temperature during the entire incubation period.

Microfluidic Device 2:

○ A key goal of the second microfluidic device is to reinject the droplets and control their speed and rate. This is achieved by spacing out the droplets with oil to ensure the droplets move through the sensing region and a rate the sensor can sample.
○ The second goal for this microfluidic chip is to integrate to the CIDAR Lab’s established fluorescence sensing equipment. We show that this flourescence sensing can be incorporated into the system.

Touchscreen/User Interface:

○ A touchscreen interface was incorporated into the system for users to easily interact with the device. Specifically, the touchscreen has sliders to set variable levels for the device and protocol saving features to enhance the user experience.
○ The touchscreen connects to the raspberry pi which controls and actuates various protocols at the touch of a button.


○ The modular housing setup can hold the different components in a variety of layouts to optimize the space for specific experiments.
○ Because the system is composed of both liquid and electronic components, we divided the product into two halves - one solely for liquid inputs and the other for electronics and microfluidics.


○ The AM1’s automation is incorporated into each stage of the device. A raspberry pi controls all the overall scheduling of the individual protocols.
○ The user’s settings are used in an automated protocol that controls the aquatic environment. The user sets specific parameters and the closed loop simulates the desired environment by controlling the sensors submerged in the water and the peristaltic pumps that dispense liquid until the target liquid parameter levels are reached.
○ For the first microfluidic device, the sampling, priming, and droplet generation have all been characterized and occur automatically at that stage of the automated protocol.
○ The incubator is controlled by a closed-loop arduino code that sets the power level of the heating chip based on the sensed temperature.
○ Lastly, automated fluorescence sensing has also been incorporated into the protocol as a proof of concept for sensing the output from a biosensor.

Consideration for Replication of Project:

○ The timings and pressures in the microfluidic automation protocol are specific to the microfluidic devices, tubing lengths, test tubes, and biosensor used in these demos. To use the automation protocol without any adjustments, the exact setup described in the proof of concept and results pages will be needed.
○ The fluorescence output of the droplets with IPTG-inducible GFP bacteria was measured with CIDAR Lab’s existing fluorescence sensing setup.

Future Plans:

○ At this stage of the aquatic environment, the pH and turbulence features have been tested, but we’re interested in expanding this to other sensors including salinity, ORP, and temperature. Currently, certain protocols within the automation have been tested thoroughly, but further testing using different components is necessary for robust automation.
○ Additionally, we want to test other biosensor protocols. Once such protocol might require two separate incubation steps allowing for single cell encapsulation in droplets, growing up these cells through droplet incubation, piconinjecting the aquatic sample, incubating again, and reinjecting into the fluorescence chip.
○ Finally, we would like to incorporate different biosensors with other types of outputs. To accomplish this goal, the integration of fast-sampling electronic sensors in the sensing microfluidic device is required.