Ethyl Acetate Hydrolysis Followed by Ionic Conductivity
Timothy N. Pillow*
University of Oregon, Department of Chemistry, Eugene, 97403.
Abstract
In this experiment we were able to measure the kinetics of a hydrolysis reaction of Ethyl Acetate measured by
conductivity. Since the reaction is temperature dependent, whereby increased temperatures should correspond to
higher rate constants, enthalpy, entropy and activation energy were also determined from the biomolecular rate
constant K2. It was found that K2 = 0.17267 ± 0.00106 at 35C °, K2 = 0.11401 ± 0.676 at 25C ° and K2 = 0.44565 ±
0.00118 at 50C °. Results agree with transition state theory, which predicts that the rate constant should increase
with temperature.
1
Introduction
Conductivity is a measure of a solution’s ability to conduct electricity, and has many useful applications
within industry including water treatment, ability to monitor ion build up, leak detection in surface condensers,
clean in place (CIP) procedures within pharmaceutical companies, interface detection and desalination
detection. For a solution to conduct electricity, it must have charged ions. Conductivity is not specific, meaning
that it cannot detect individual ions, just the total concentration of all ions. Conductivity is measured in Siemans
S, named after Ernst Werner von Siemens and is equal to Ω-1. In this experiment we measure the conductivity
over time of an Ethyl Acetate Hydrolysis reaction. The theory is based on the fact that since each ion has a
different equivalent conductance, as the composition of the reaction changes, so will the conductivity. This
allows us to monitor when the reaction finishes. Our reaction follows this irreversible reaction:
𝐶𝐻3 𝐶𝑂𝑂𝐶𝐻2 𝐶𝐻3 + 𝑂𝐻 − → 𝐶𝐻3 𝐶𝑂𝑂− + 𝐶𝐻3 𝐶𝐻2 𝑂𝐻
‡
Fig 1. Showing the hydroxide catalyzed ester hydrolysis. K is an equilibrium
constant (reversible reaction) and K’ is a rate constant (irreversible)
2
Mechanism of Base Hydrolysis
The hydroxide acts as a nucleophile and attacks electrophilic C=O bond of
the ester. As the oxygen reforms its double bond onto the now tetrahedral
intermediate, this causes the alkoxide group to leave, which leads to the
structure of a carboxylic acid. Lastly, the negatively charged alkoxide is very
unstable and deprotonates the carboxylic acid. The last step in the reaction
has a very fast equilibrium constant since protonation is energetically
favorable for the alkoxide, and the negatively charge left on the carboxylic
acid is stabilized by resonance.
Data was analyzed using a least squares linear fit 𝐺0 − 𝐺(𝑡)/𝑡 as a function
of G(t) in order to determine the equilibrium constant K2. G0 is the
conductivity at time zero. After solving for K2 we were able to solve for G∞
which is the conductivity at reaction completion, see equation (1) below.
Fig 2. Mechanism of base
hydrolysis, showing the
favorable deprotonation in
the last step.
𝐺0 − 𝐺(𝑡)
= 𝑘2 𝑎𝐺∞ − 𝑘2 𝑎𝐺(𝑡)
𝑡
(1)
Equation (1) resembles the equation of a line (y=mx+b) whereby K2 can also be calculated by m/a =
slope/0.01 where m is slope and ‘a’ is the molar concentration. G0 and G∞ can also be calculated as follows:
G0 =
G∞ =
1
𝑎∆ − + 𝑎∆𝑁𝑎+
1000𝑘 𝑂𝐻
1
− + 𝑎∆𝑁𝑎+
𝑎∆
1000𝑘 𝐶𝐻3 𝐶𝑂𝑂
(2)
(3)
3
Lastly, we were able to plot conductivity G(t) against time and model it using the
equation (4) below in order to calculate conductivity at any time t:
𝐺(𝑡) =
𝑘2 𝑎𝑡𝐺∞ + 𝐺0
(1 + 𝑘2 𝑎𝑡)
(4)
Mechanism of Acid Hydrolysis
The first step in the reaction is really a pre-requisite for the hydrolysis reaction to
occur. Since the double bonded oxygen is stable, it is a poor nucleophile. Only
by protonation in the first step do we “activate” the hydrolysis by making the
ester carbonyl more electrophilic.
From here onwards, the water molecule acts as nucleophile, and the reaction
proceeds in the same way that base catalyzed hydrolysis did. The water molecule
causes a tetrahedral intermediate to form. The water molecule attached to
compound is then deprotonated by another water molecule and the oxygen of the
alkoxide deprotonates a water molecule / or hydronium ion. The positively
charged alkoxide thus becomes a good leaving group, and leaves when the
hydroxide substituent forms a double bond. The positively charged hydroxide
group is subsequently deprotonated which completes the acid hydrolysis of the
ester. It’s important to note that unlike the base hydrolysis mechanism; only the
acid hydrolysis has a reversible last step (allowing the entire reaction to become
irreversible). The last step is reversible because the formation of a hydronium
ion is very acidic and can easily re-protonate the hydroxyl group, kick starting
the reverse reaction.
Fig 3. Acid hydrolysis
mechanism.
4
Experimental
Test tubes containing solution were placed in a hot plate. The hot plate was connected to a VWR 1165
refrigerated constant temp circulator. Probes were inserted into the test tubes which were connected to a Fisher
Scientific accumet excel XL30 conductivity meter. Conductivity v time was collected at 3 different
temperatures: 25C ° ,35C ° and 50C °. After temperature was set, we waited 5mins for the glass test tubes to
warm before adding 10ml NaOH and 10ml ethyl acetate. Stir bars were subsequently added and set to a low stir
setting. Data was collected at a 3-second sampling rate. Conductivity was initially recorded in µS/cm and
ms/cm as conductivity increased. On analysis of data, all data was converter to S/cm in Microsoft Excel.
Further analysis was done in Igor Pro.
Results
Our results show a large difference between rate constants calculated using the model in equation 1 for the
linear fit, and the constant calculated by applying equation 4. Using equation (1) to find the rate constant
implies that the slope should be negative. On analysis of figures 4,6,8 we tried to fit the least squares fit to the
data that also resembled a negative slope, however no matter which data points the fit was applied to, large
deviations from literature values were still observed. Table 1 illustrates the large difference in calculated values
using 2 different models.
Temperature
25C °
35C °
50C °
K2 (determined from
K2 (determined from
linear fit)
non-linear fit)
G∞ (Siemans)
G0 (Siemans)
0.00098437
8.9267 ± 3.68e-005
0.11401 ± 0.676
0.002429
0.0014532 0.002973
0.068282 ±3.68e-005
0.17267 ± 0.00106
0.0013181 0.003028
0.68332 ±2.84e-005
0.44565 ± 0.00118
Table 1. Showing the linear fit estimation of K2 vs the non-linear fit. For the non-linear fit, independent
variables other than ‘a’ which were known (0.01M) were allowed to float.
5
Fig 4. Linear fit at 25C °
Fig 5. Non-linear fit at 25C °
Fig 4. Linear fit at 25C °
Fig 6. Linear fit at 35C °
Fig 8. Linear fit at 50C °
Fig 7. Non-linear fit at 35C °
Fig 9. Non-linear fit at 50C °
6
Calculation of ΔH:
ΔH = R ln (
𝑘2𝐿 𝑇𝐻 1
1
)( − )
𝑘2𝐻 𝑇𝐿 𝑇𝐻 𝑇𝐿
ΔH(25-35°C) = 29187.1 J/mole
ΔH(25-50°C) = 41100.2 J/mole
ΔH(35-50°C) = 49708.1 J/mole
Avg: 39998.5 J/mole
Calculation of Activation Energy Ea:
From transition state theory we know that Ea = ΔH + RT
Ea (25°C) = 42477.3 J/mole
Ea (35°C) = 42560.5 J/mole
Ea (50°C) = 42685.2 J/mole
Calculation of Gibbs Free Energy ΔG:
ΔG= -RT ln(k)
ΔG(25°C) = 5382.68 J/mole
ΔG(35°C) = 4499.76 J/mole
ΔG(50°C) = 2171.42 J/mole
Avg: 4017 J/mole
Calculation of Entropy ΔS:
𝑒
∆𝐺
=
𝑅𝑇
−
∆𝑆
𝑅
𝑒 𝑒
∆𝐻
𝑅𝑇
−
ΔS = 120.683 J/mole K
7
Error Analysis:
(𝐾2 𝑎𝑡G∞ + G0 )𝑎𝑡
𝜕𝐺(𝑡)
𝑎 + G∞
=
+
(−1 + 𝐾2 𝑎𝑡)2
𝜕𝐾2
1 + 𝐾2 𝑎𝑡
Using a=0.01M , t=600secs (10mins), G∞=0.000917, G0 =0.002429
Error(50°C) = 0.0134
Error(35°C) =22.577
Error (25°C) =0.2998
Discussion
The large difference in rate constant calculations is surprising. It appears that the linear fit model is generally a
poor predicator of the rate constant. On observation of the graphs in Fig 4,6, and 8 the shapes of the graphs vary
considerably. One explanation for this is simply poor data. Another is that since the equation 𝐺0 − 𝐺(𝑡)/𝑡
(y-axis) and Conductivity (X-axis) are both in terms of time, then it means that any errors within the data are
going to be magnified. In Fig 4 as time decreases, it appears that the error increases almost exponentially, until
at a conductivity of around 2S/cm the conductivity as a function of time is shown by a vertical line. Another
source of error is possible at the very start of data collection. When the solutions were mixed the conductivity
readings were recorded, but achieving an instantaneous homogenous mixture is not achievable with the current
equipment. This means that data readings at the onset of the experiment are likely to be least accurate. To
compensate for this we fitted our model in Fig 5,7 and 9 by ignoring the first few points, in hopes of achieving a
more accurate and precise fit.
Although the rate constants increased with increased temperature as expected, the residual traces fitted indicate
significant error is possible within Fig 5 and 7. Fig. 9 at 50 degrees show a promising residual and indicates that
our data in Fig 9 should contain the least amount of error, which is surprising since 50 degrees is near
temperature limit of the reaction before results are harder to analyze.
8
Corresponding Author
Timothy Pillow: [email protected]
Author Contributions
ACKNOWLEDGMENT
Kareth Curliss : Joint data collector
John L. Hardwick, University of Oregon
REFERENCES
(1) http://www2.emersonprocess.com/siteadmincenter/PM%20Rosemount%20Analytical%20Documents/Li
q_ADS_43-018.pdf (Uses of conductivity within industry)
(2) http://www.chem.ucalgary.ca/courses/350/Carey5th/Ch20/ch20-3-3-1.html (mechanism diagrams)
(3) http://willard.uoregon.edu/CH418/Lect2014//EtOAc.pdf (Fig 1).
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