• Composed a memorandum on aeration and agitation rates on yeast cultures in a small scale bioreactor. • Plotted graphs to see how oxygen concentration in system depleted in time with presence of the bacteria.

1. Technical Memorandum
pg 1
Date: 10/5/15
To: Brian Thompson
Dr. Nielsen, Professor, CHE 451
From: Alfonso Figueroa, Team 1
Lab Section B
Subject: Aeration Rates and Agitation Rates Impact In a Bioreactor
Summary
Bioreactors are used for the fermentation of different materials to acquire desired goods
including foods, antibiotics, and alcohols. This experimentation will go over the aeration and
agitation rates of a bioreactor in the presence and absence of bacteria culture. The volumetric
mass transfer coefficient, 𝑘 𝐿 𝑎, will be determined through the slope of the linearized equation of
the buildup of oxygen in the liquid phase. The slopes gained for 𝑘 𝐿 𝑎 in static condition (no
bacteria present) in the reactor increase in value as agitation rate and aeration rate increase. The
same theory holds true in dynamic condition (bacteria present) where the 𝑘 𝐿 𝑎 slopes increase in
value as the agitation rate and aeration rate increase. Errors are present in a ± 5% range where
possible misreadings from the probe could have occurred.
Introduction
Fermentation has been performed for hundreds years all over the world to numerous
delectables. These foods include yogurt, tempeh, beer, bread and much more. The science behind
fermentation is that yeast and bacteria break down large molecules down to smaller sized
components. This results in waste products being cultivated from the cultures. Some of the waste
that is accumulated emerge as alcohols; these comprise of ethyl alcohol, butyl alcohol, acetone,
and additional molecules.
Eventually in the 1900s, bioreactors were conceived for the up-scale manufacturing of
culture bacteria and yeast. Bioreactors used to mainly be used in the synthesis of alcohols which
could be used to yield rubber for use in World War I. Another robust role the Bioreactor took
part in is the production of medicinal antibiotics. This started during World War II where the
major antibiotic produced at the time was penicillin since fermentation was ideal in
manufacturing the drug. The Bioreactor machines are a fine specimen of genius Chemical
Engineering design being applied to a new process.1
There are an abundant amount of parameters that are involved in the production of the
cells following pH, pressure, temperature, oxygen concentration, and more. The most important
of the different parameters is oxygen concentration, or more commonly known as, aerobic
bioprocess, which will be the main focus of this paper. In the aerobic bioprocess, the oxygen
transfer rate (OTR) describes oxygen transferring from the gas phase in the bubble into the liquid
phase. The equation is as follows:

2. Technical Memorandum
pg 2
(1)
𝑂𝑇𝑅 = 𝑘 𝐿 𝑎(𝐶∗
− 𝐶 𝐿)
Where 𝐶 𝐿 is the dissolved oxygen concentration in the bulk liquid, 𝐶∗
is the oxygen
saturation concentration in equilibrium between bulk liquid and bulk gas phase, 𝑘 𝐿 is the liquid
mass transfer coefficient, and 𝑎 is the gas-liquid interfacial area per unit of liquid volume. Since
defining 𝑘 𝐿 and 𝑎 disjointedly is extremely hard, both variables in combination, called the
volumetric mass transfer coefficient, can have a value determined for the transport of a gas to a
liquid. The jointed variables 𝑘 𝐿 𝑎 is important in determining aeration efficiency in the
bioreactor. A way to determine 𝑘 𝐿 𝑎 is by using the mass balance of dissolved oxygen in the
liquid phase.
(2)
𝑑𝐶
𝑑𝑡
= 𝑂𝑇𝑅 − 𝑂𝑈𝑅
Where
𝑑𝐶
𝑑𝑡
is the buildup of oxygen in the liquid phase and OUR is the oxygen uptake rate
by the cells. The formula for OUR is as follows:
(3)
𝑂𝑈𝑅 = 𝑞 𝑂2
𝐶 𝑋
Where 𝑞 𝑂2
is the oxygen uptake rate of the cells and 𝐶 𝑋 is the biological mass
concentration. The first part of this two part lab experiment will involve oxygen being inserted in
a bioreactor with no yeast cultures. Aeration and agitation rates are to be determined to see how
they affect the volumetric mass transfer coefficient. Since no bacteria will be present in the
bioreactor, equation (2) mass balance reduces as follows:
(4)
𝑑𝐶 𝐿
𝑑𝑡
= 𝑂𝑇𝑅 = 𝑘 𝐿 𝑎(𝐶∗
− 𝐶 𝐿)
Based on equation (4), the hypothesis for experiment one is that with an increase of
oxygen flow rate and agitation, the bubbles will burst up quicker. This will then make 𝑎 smaller
in value and thus increase the slope and decrease the time necessary to reach equilibrium. To
graph equation (4), the equation will be derived on both sides and then linearized. Also, the
dissolved oxygen (DO) will represent the ratio between 𝐶∗
and 𝐶 𝐿 as so,
𝐶 𝐿
𝐶∗, where 𝐶∗
can be
determined from Henry’s Law. The slope of the line is represented by 𝑡 =
1
𝑘 𝐿 𝑎
.
(5)
ln(1 − 𝐷𝑂) = −𝑘 𝐿 𝑎 ∗ 𝑡

3. Technical Memorandum
pg 3
For the second half of the experiment, oxygen will dissolve in a bioreactor containing a
culture of yeast. Aeration and agitation rates are going to be determined once again on the
volumetric mass transfer coefficient. All of equation (2) will be used and the theory for this trial
is that an increase in the aeration and agitation rates will transport the oxygen to the culture
faster, thus reaching equilibrium rapidly as well. The cell growth rate will also be inspected with
comparison of OUR where the equation is as follows:
(6)
𝑑𝐶 𝑋
𝑑𝑡
= µ𝐶 𝑋
Where µ is the specific cell growth rate, the slope comes out as −
1
µ
, representing oxygen
being consumed by the bacteria. The hypothesis is that with the rise in yeast growth rate, this
will decline the slope and therefore increase time of oxygen consumption. 2,3
Methodology
The schematic of the apparatus used for this laboratory is a small scale sized replica of a
bioreactor used in huge manufacturing plants. On the top of the bioreactor, there is a motor that
connects to the stirrer inside of the glass vessel [1]. There is a double jacket that surrounds the
bowl for heating and cooling purposes [2]. There is a rotameter that controls the inlet flow rate of
either air or Nitrogen gas into the reactor [3]. There is an opening on top of the container for any
exhaust gases to escape from [4]. An instrumental probe is used for calibrating and measuring
oxygen concentration in the tank [5]. A computer screen that is connected to the probe is used to
output oxygen concentrations in numerical values and display graphs [6].
Figure 1: Small scale bioreactor design4

4. Technical Memorandum
pg 4
For the first experiment of this lab, fill the bioreactor with only distilled water close to the
top of the vessel. The next step is to determine the specified oxygen flow rate and the agitation
RPMs for the upcoming trial runs. Now turn on Nitrogen gas to deoxygenate the system, leaving
0% concentration of oxygen in the water. Pick 3-5 oxygen flow rates, 3-5 agitation RPMs and a
grouping of 3 flows with 3 agitations. With the specified trials determined, record the DOC with
reverence to time, and then plot line graphs to then determine how 𝑘 𝐿 𝑎 is affected.
For the second experiment, fill the bioreactor with water and also yeast cultures to the
brim of the bowl. As the bacteria consume the oxygen at a steady state, record the DOC with
respect to time and the optical density (OD). Using a spectrophotometer at 600 nm, the OD can
then determine the cell growth in the system. Once enough oxygen has been consumed, pick 3-5
oxygen flow rates, 3-5 agitation RPMs and a grouping of 3 flows with 3 agitations. After trials
are set, record the DOC and OD with condolences to time, and then plot the line graphs to see
how 𝑘 𝐿 𝑎 is affected.
Results & Discussions
For the first experiment, some graphs gathered from trial runs are observed for any trends
and errors that could have caused data to go haywire.
Figure 2: Oxygen concentration vs. time at 100 rpm
In figure 2, the lines show an ever increasing slope until each one reaches 100%
concentration of oxygen for 100 rpm agitation. The lowest flow rate, 2 scfh, takes around 24
minutes to reach a 100% oxygen level. The next flow rate, 3 scfh, takes around 16 minutes until
oxygen completely saturates the water system. The highest and last flowrate, 4 scfh, takes about
13 minutes to reach a 100% concentration of oxygen in the solution.
Based off the 100% oxygen completion rate for each line, a trend is observed. The higher
the flow rates, the faster to completion the oxygen will fully saturate the system. The opposite
holds true as well, the lower the flow rate, the slower it takes for oxygen to reach a 100%
concentration in the water. The error bars throughout the graph are in a ± 5% range where the
0
20
40
60
80
100
120
0 5 10 15 20 25 30
OxygenConcectration(%)
time (min)
100 rpm 2 scfh
100 rpm 3 scfh
100 rpm 4 scfh

5. Technical Memorandum
pg 5
error increases more as the slope increases. Reasons for errors happening can be because of
inaccurate reading from the probe, unsteady rpm rates, and/or faulty readings from the computer.
Figure 3: Linearized equation (5) vs time at 100 rpm
Using the linearized equation (5), the slope values can be determined as follows in figure
3. At a flow rate of 2 scfh, the slope ended up coming out at a value of -0.2414. The next flow
rate, 3 scfh, the slope results in a numerical value of -0.3304. The last and final flow rate, 4 scfh,
the slope number comes out at a value of -0.4208. These values can be used to determine the
volumetric mass transfer coefficient, 𝑘 𝐿 𝑎.
Figure 4: Oxygen concentration vs. time at 200 rpm
-12
-10
-8
-6
-4
-2
0
0 5 10 15 20 25 30
ln(c*-cL)
time (min)
100 rpm 2 scfh
100 rpm 3 scfh
100 rpm 4 scfh
0
20
40
60
80
100
120
0 2 4 6 8 10
OxygenConcentration(%)
time (min)
200 rpm 3 scfh
200 rpm 4 scfh

6. Technical Memorandum
pg 6
In figure 4, it is shown that similar trends are occurring just like in figure 2. Only two
flow rates would be done though because of limited time in lab. The lowest flow rate, 3 scfh,
shows a 100% oxygen concentration in the system at around 9 minutes. The highest and last flow
rate, 4 scfh, shows a complete saturation of oxygen in the water at around 7 minutes.
Comparing figures 2 and 4, the fastest completion time of the system to reach a 100%
concentration of oxygen happens in figure 4. The reason for this has to nonetheless be the
agitation rate itself. What ends up being seen is that the higher the agitation rate, the faster the
oxygen reaches completion in the system. The lower the agitation rate, the slower it takes for the
oxygen to reach 100% oxygen concentration in the water. Errors that could occur are the same as
for figure 2 where there could be an inaccurate reading from the probe, unsteady rpm rates,
and/or faulty reading from the computer.
Figure 5: Linearized equation (5) vs time at 200 rpm
Just like figure 3, the linearized equation (5) is used to determine the slopes for the flow
rates at an rpm of 200 in figure 5. The lowest flow rate, 3 scfh, gives off a slope of -0.0657. The
final and highest flow rate, 4 scfh, outputs a slope of -0.6932. The graphs for an agitation of 300
rpm will not be displayed due to the fact that the graphs would just further prove the theories
confirmed from the other figures.
-14
-12
-10
-8
-6
-4
-2
0
0 2 4 6 8 10
ln(c*-cL)
time (min)
200 rpm 3 scfh
200 rpm 4 scfh

7. Technical Memorandum
pg 7
Figure 6: Volumetric mass transfer coeff vs. aeration rate at various rpms
In figure 6, the volumetric mass transfer coefficient, 𝑘 𝐿 𝑎 , is shown in terms of agitation
rate and aeration rate. The lowest agitation rate, 100 rpm, starts at a 𝑘 𝐿 𝑎 of 0.2 at 2 scfh, and then
increases steadily to a value of 0.4 at 4 scfh. The next agitation rate, 200 rpm, starts at a 𝑘 𝐿 𝑎 of
0.6 at 3 scfh, and then inclines to a value of 0.7 at 4 scfh. The highest agitation rate, 300 rpm,
starts at a 𝑘 𝐿 𝑎 of 1.1 at 3 scfh, and then increases to 1.2 at 5 scfh.
After the following trends have been investigated in full detail, a trend ends up appearing
from figure 6. The volumetric mass transfer coefficient increases in value as the agitation rate
and the aeration rate increase. The agitation rate though tends to increase 𝑘 𝐿 𝑎 much more than
the aeration rate. The error bars came out in a ± 5% range where error appeared to increase as the
slopes inclined ever higher. The errors are the same yet again as for figures 2 and 4, where there
could be an inaccurate reading from the probe, unsteady rpm rates, and/or faulty reading from
the computer.
Now transitioning to the second experiment of the lab, a few graphs will be observed for
any trends and errors that could have appeared.
Figure 7: Oxygen concentration vs. time in presence of yeast 1 and 2
0
0.2
0.4
0.6
0.8
1
1.2
1.4
0 1 2 3 4 5 6
volumetricmasstransfercoeff(kLa)
Aeration O2 rate (scfh)
100 rpm
200 rpm
300 rpm
0
20
40
60
80
100
120
0 20 40 60 80
OxygenConcentration(%)
time (min)
yeast 1: 200 rpm 4
scfh

8. Technical Memorandum
pg 8
In figure 7, the slopes start to decline to a certain point and then exponentially increase
until it starts to level off horizontally. At the lowest rate of 200 rpm and 4 scfh, the starting point
of 100% oxygen concentration occurs at the 5 minute mark where it declines ever so steadily to
the 40 minute mark. The line then starts to increase exponentially until it starts to level off
horizontally at the 60 minute mark. At the highest flow rate of 300 rpm and 5 scfh, the 100%
oxygen concentration happens at the 0 minute mark where it decreases constantly down to the 35
minute mark. It then increases exponentially to the 40 minute mark where it then levels off
horizontally at the 100% point for the rest of the time duration.
The reason for the following trends being observed is because of the varying flow rates.
When the yeast 1 culture consumes all of the oxygen, the lower flow rate and agitation rate takes
longer to resupply the system with oxygen. When the yeast 2 culture consumes all of the oxygen,
the higher flow rate and agitation rate takes a shorter amount of time to refill the water with
100% concentration of oxygen. These trends are similar to the figure 2 and 4 trends where higher
agitation rates and aeration rates supply the system with oxygen at a much faster rate. Errors that
could have occurred can be from a misreading from the probe, uneven amount of cells put into
the reactor for both runs, and/or misinterpreted data from the computer.
Figure 8: Volumetric mass transfer coeff vs. aeration rate in presence of yeast
Due to limited time in lab and low cell cultures to deal with, only two points could be
gained, but an analysis on figure 8 can still be done. At the lowest agitation rate and aeration rate
of 200 rpm and 4 scfh, the volumetric mass transfer coefficient, 𝑘 𝐿 𝑎, outputs a value of 0.2. At
the highest agitation rate and aeration rate of 300 rpm and 5 scfh, the volumetric mass transfer
coefficient, 𝑘 𝐿 𝑎, displays a number of 0.4. What can be observed yet again is that a higher 𝑘 𝐿 𝑎
numeral can be gained from higher agitation rates and aeration rates. The opposite holds true
where a lower value of 𝑘 𝐿 𝑎 can be gained from a lower agitation rate and aeration rate. Errors
that could have occurred are the same as for figure 7 where there could be a misreading from the
probe, uneven amount of cells was put into the reactor for both runs, and/or misinterpreted data
from the computer.
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0 1 2 3 4 5 6
volumetricmasstransfercoeff
(kLa)
Aeration O2 rate (scfh)
200 rpm
300 rpm

9. Technical Memorandum
pg 9
Conclusion and Recommendation
After the two experiments were fully completed and the data was analyzed to its fullest
potential, important theories came about. The higher the agitation rate and aeration rate, the
faster the system can reach 100% oxygen concentration with or without bacteria present. The
higher the agitation rate and aeration rate, the bigger the volumetric mass transfer coefficient,
𝑘 𝐿 𝑎, is in value without the presence or with the presence of cell culture. A recommendation to
consider for future trial runs of this experiment is to provide more detail on how to use the
computer interface for graphing convenience.

10. Technical Memorandum
pg 10
References
[1] Rice University. http://www.bioc.rice.edu/bios576/nih_bioreactor/NDL_Bioreactor%2
0Page.htm (accessed October 2, 2015)
[2] sadrabiotech. http://sadrabiotech.com/catalog/scale%20up%20bioreactor1.pdf
(accessed October 3, 2015)
[3] asu. https://myasucourses.asu.edu/bbcswebdav/pid-11466185-dt-content-rid-
60822354_1/courses/2015Fall-T-CHE451-76086-84043-70672-70673/CHE451%20-
%20B%20-%20Bioreactor%281%29.pdf (October 3, 2015)
[4] biomedcentral. http://www.biomedcentral.com/1753-6561/5/S8/P48/figure/F1
(accessed October 3, 2015)
[5] University of Minnesota. http://d.umn.edu/~rdavis/courses/che4601/notes/Bio
reactorDesignForChEs.pdf (accessed October 4, 2015)