We first primed the pumps to ensure that fluid was able to reach the insert and then performed three consecutive runs on separate well plates of the same format.

The plates filled with DI water were then aspirated one well at a time using micropipettes and the fluid dispensed by the system was measured in a weighing boat placed atop a standard laboratory balance which had a least count 0.01 grams.

The weights were converted into volumetric data based on the assumption that water has a density of 1 g/ml and the volumes were recorded into a spreadsheet.

The volumes were normalized and converted into percentages based on the theoretical amount of water that should have been dispensed by the system.

The percentage distribution data points were inputted into R Studio to generate heatmaps using the heatmaply function.

The maximum percentage graphs were then created by calculating the percent change from the maximum and minimum values.

The error bars were made by calculating the percent changes from the median to the maximum and minimum.

Finally, the bell-curve distribution, which shows the frequency of occurrence and the volume in milliliters, was made by populating the data points in Excel then finding the mean, standard deviation, and the 99.7% maximum and minimum values in the curve. Iterative values for the curve were then computed by finding the interval count and interval values to achieve the bell-shaped data points. With the data points, the bell-curve distribution was created.