COnference Paper

1. 1[MM-03]
Proceeding the Regional Conference on Chemical Engineering 2014
Yogyakarta, December 2-3, 2014
ISBN: 978-602-71398-0-0
Regression Modelling of Thermal Degradation Kinetics, of
Concentrated, Aqueous Piperazine in Carbon Dioxide Capture
Shaukat A. Mazari, Brahim Si Ali*
Department of Chemical Engineering, Faculty of Engineering, University of Malaya, 50603, Kuala
Lumpur, Malaysia.
*E-mail address: brahim@um.edu.my
Abstract. Carbon dioxide (CO2) emissions are a rising concern for the climate change and
global warming. Postcombustion CO2 capture using amine-base solvents seems to be a viable
technology. Concentrated, aqueous Piperazine (PZ) is an advanced solvent that has promising
characteristics to capture CO2. Experimental, thermal degradation kinetics data of
concentrated, aqueous PZ, loaded with CO2 was regressed using MATLAB®
. Data is fitted to
first and second order rate laws, by linear and nonlinear regression methods. Six different types
of expressions were used to describe the trend of thermal degradation of CO2 loaded aqueous
PZ. The findings revealed that the thermal degradation data followed both first order and
second order kinetics. Current model exhibited that rate constants (k1 and k2) can be predicted
by making use of six different expressions (1-6). Expression 3 and 5 are the most appropriate
expressions for predicting the thermal degradation kinetics for the first order and second order
rate laws. Coefficient of determination (R2
) for both models are higher than 0.99.
Key words: CO2 capture, degradation kinetics, piperazine, regression, thermal degradation,
1. Introduction
The report of international energy agency (IEA) [1], exhibited that production of electricity
and heat from fossil fuel-fired power plants accounted for 41% of the global carbon dioxide
(CO2) emissions in 2010. The highest rate of CO2 emissions, i.e. 71.5% has been noticed in
electricity and heat sector for one decade, from 1990 to 2010, that is no doubt an alarming
sign to activate mitigation of these emissions [1]. Amine-based absorption/stripping process
is a viable approach for capturing CO2 from coal-fired power plant flue gases [2]. Solvent
selection is considered as a primary step to this technology because it has a major role in the
performance of CO2 capture and economics [3, 4]. However, the viability of a solvent
depends on several parameters, namely; CO2 capture capacity, volatility, absorption rate,
degradation resistance and environmental impact. One of an essential parameter for solvent
selection criteria is the thermal degradation, as the stripper temperature goes above 100 °C,
which causes a rise in steam requirements and ultimately lowers CO2 capture capacity [5, 6].
Piperazine is a newly established solvent that has higher capacity of CO2 capture, high CO2
absorption rate and lower thermal and oxidative degradation [5, 7-11]. Thermal degradation
rate of PZ is minimum compared to the conventional amines. However, the abundant thermal
degradation products of 8 m PZ are N-formyl PZ (FPZ), ammonium (NH4
+
), and N-(2-
aminoethyl)PZ (AEP) which accounts for a total of 57% of nitrogen and 45% of carbon loss
[9]. Thermal degradation PZ also produces nitrosamines, which are potentially carcinogens
compounds [12]. Nitrosation of PZ occurs either through oxidation of PZ or due to the
presence of nitrogen gas contents (NOx) [13, 14]. Further, research revealed that N-(nitroso)-

2. 2[MM-03]
Proceeding the Regional Conference on Chemical Engineering 2014
Yogyakarta, December 2-3, 2014
ISBN: 978-602-71398-0-0
piperazine (MNPZ) formed in absorber can be decomposed in stripper at 150°C with a
significant rate [15].
PZ thermal degradation follows secondary nucleophilic (SN2) reaction mechanism, which
supports the hypothesis of second order rate law and rate constant (k2), to be used for the
analysis of PZ loss [11].
Regression analysis is one the of basic tools used to analyze the chemical kinetics data [16].
Order of reaction, coefficient of rate constants and initial rate of reaction can be determined
by using linear and nonlinear methods of regression [17, 18]. Literature studies [9-11]
indicate, that the linear and exponential regression has been carried out for the data of current
system, concentrated aqueous PZ. However, the results obtained through the regression are
with lower R2
values, especially at 135°C. This suggests a detailed regression analysis of the
experimental data of the system is required. Six different expressions are produced from first
and second order rate laws. A comprehensive regression is conducted for all the expressions.
Detailed analysis of rate constants (k1 and k2) is discussed with respect to each model
(expression).
2. Methodology
Early PZ studies showed that PZ loss kinetics follow first order kinetics and rate constant (k1)
[10]. Recent studies revealed that PZ thermal degradation is believed to follow SN2 reaction
mechanism, which advocates a second order rate law and rate constant (k2) to analyze PZ loss
[11]. Thus, first order rate law and second order rate law expressions were rearranged in 6
different forms of linear and nonlinear expressions to get a better fit to the experimental data.
Integrated equations (at boundary conditions, t=0, and t=t) of the first order and order rate
laws are reported as in equation (1) and equation (2);
Experimental data for thermal degradation of aqueous, concentrated PZ was taken from
previous studies [9-11]. However, the subject data is for thermal degradation of 8 m PZ with
0.3 mole CO2 per mole alkalinity. Details of the materials and methods may be viewed from
the sources. In this study, MATLAB®
R2012b is used. Regression analysis is conducted,
using the function curve fitting tool. Data for dependent and independent variables (X) and
(Y) are prepared as per Table 1. Expressions 1 to 4 employed polynomial first order and
expression 5 used second order polynomial whilst exponential function is used for expression
6.
CPZ (1)
(2)

3. 3[MM-03]
Proceeding the Regional Conference on Chemical Engineering 2014
Yogyakarta, December 2-3, 2014
ISBN: 978-602-71398-0-0
Table 1Linear and Nonlinear forms of first and second order rate equations
Expression Type Equation Curve fitting (Y Vs X)
Expression 1,
First Order
Linear lnCPZ Vs t
Expression 2,
Second Order
Linear 1/CPZ Vs t
Expression 3,
Second Order
Linear 1/CPZ.t Vs 1/t
Expression 4,
Second Order
Linear CPZ/CPZ0 Vs CPZ.t
Expression 5,
Second Order
Quadratic t/CPZ0 Vs t
Expression 6,
First Order
Exponential CPZ CPZ Vs t
3. Results and discussions
In this study, experimental data of concentrated, aqueous PZ are analyzed by using six
different expressions for the first and second order kinetics. Expressions for the first and
second order models for linearized and non-linearized forms with conditions are presented in
Table 1. Expression 1 and 2 are representing first order rate equation; however, expressions 2
to 5 represent a second order rate equation. First four expressions are in the linearized form
while fifth and sixth are in quadratic and exponential forms respectively. Expressions; 1, 2, 4
and 6 exhibited more or less similar results to those published in the literature previously.
However, two equations; expression 3 and 5 presented highly reliable results with R2
values
higher than 0.99.
3.1 First order kinetics
Expressions 1 and 6 in Table 1, are representing the first order rate laws. Expression 1 is in
the linear form and expression 6 is in exponential form. The results obtained through these
two expressions have identical R2
values. The highest R2
, noticed for the first order
expressions 1 and 6 is at 150 °C, which is 0.96 and lowest R2
is observed at 135 °C.
However, overall k1 values are similar to those reported in literature, so the first order
reaction expressions are not of much interest in the case of this study. First order rate
constants, k1 of these two expressions and that from the literature are presented in Table 2.

4. 4[MM-03]
Proceeding the Regional Conference on Chemical Engineering 2014
Yogyakarta, December 2-3, 2014
ISBN: 978-602-71398-0-0
Table 2 First order rate models results for thermal degradation of 8 m PZ with 0.3 mole CO2
per mole alkalinity initially at 135 °C to 175 °C.
Temperature (°C) k1( s-1
) R2
k1( s-1
) R2
Expression 1, First order kinetics Literature results Model results
175 1.32*10-7
0.98 1.20*10-7
0.89
165 3.14*10-8
0.95 3.94*10-8
0.88
150 6.12*10-9
0.96 8.63*10-9
0.96
135 9.69*10-10
0.57 9.70*10-10
0.56
Expression 6, First order kinetics Literature results Model results
175 1.32*10-7
0.98 1.20*10-7
0.89
165 3.14*10-8
0.95 3.94*10-8
0.88
150 6.12*10-9
0.96 8.63*10-9
0.96
135 9.69*10-10
0.57 9.70*10-10
0.56
It is observed from Table 2 and 3 that the coefficients of determination, R2
are changing at
each temperature in virtually every equation. Change in R2
values at each temperature
advocates that the independent(X) and dependent(Y) variables data points are not uniform.
This reveals that there is a significant impact of temperature on the data fitting of
concentrated, aqueous PZ.
3.2 Second order kinetics
Second order kinetics is reported in expressions 2 to 5. Expressions 2 to 4 are in the first
order polynomial form while the expression 5 is in the quadratic form. Detailed k2 values for
each expression is shown in Table 3.

5. 5[MM-03]
Proceeding the Regional Conference on Chemical Engineering 2014
Yogyakarta, December 2-3, 2014
ISBN: 978-602-71398-0-0
Table 3 Results of k2 of second order models of thermal degradation of 8 m PZ with 0.3
mole CO2 per mole alkalinity initially at temperatures, 135 °C to 175 °C.
Temperature (°C) k2( kg/mmol.s) R2
k2( kg/mmol.s) R2
Expression 2, First order kinetics Literature results Model results
175 4.94*10-11
0.99 5.62*10-11
0.91
165 1.28*10-11
0.94 1.22*10-11
0.87
150 1.49*10-12
0.95 2.05*10-12
0.96
135 2.39*10-13
0.58 2.40*10-13
0.53
Expression 3, First order kinetics Literature results Model results
175 4.94*10-11
0.99 6.09*10-11
0.99
165 1.28*10-11
0.94 7.95*10-12
0.99
150 1.49*10-12
0.95 1.97*10-12
1.00
135 2.39*10-13
0.58 1.64*10-13
0.99
Expression 4, First order kinetics Literature results Model results
175 4.94*10-11
0.99 5.08*10-11
0.84
165 1.28*10-11
0.93 1.17*10-11
0.75
150 1.49*10-12
0.95 2.05*10-12
0.95
135 2.39*10-13
0.58 2.37*10-13
0.50
Expression 5, First order kinetics Literature results Model results
175 4.94*10-11
0.99 5.24*10-11
0.99
165 1.28*10-11
0.94 1.77*10-11
0.99
150 1.49*10-12
0.95 1.83*10-12
0.99
135 2.39*10-13
0.58 5.06*10-13
0.99
It is observed from Table 3, that the expressions, 2 and 4 R2
values are not consistent at each
temperature. This shows that either time or concentration data is in a highly haphazard
condition or expressions are not good representatives of the data. Generally, the most
appropriate fitting is found at 150 °C and the poorest at 135 °C except expression 3 in linear
models and expression 5 as quadratic. The expressions 2 and 4 presented poorest R2
values
while expression 3 and 5 showed higher R2
values. The expression 3 has R2
values nearly
equal to 1, which put forward the expression as a more suitable option, for predicting the
second order kinetic data by linear method. Similarly, on the basis of R2
values, the

6. 6[MM-03]
Proceeding the Regional Conference on Chemical Engineering 2014
Yogyakarta, December 2-3, 2014
ISBN: 978-602-71398-0-0
expression 5 also can be considered as a workable equation for predicting second order
kinetics data, as R2
values for this expression are also higher than 0.99.
Second order rate law fits data with more flexibility than the first order rate law due to its
versatility in alternate expressions formation, as provided in Table 1. Modeled expressions 2
to 4 describe the linear behavior of the second order kinetics whose results are more or less
similar in expressions, 2 and 4 with small changes. Consistency of the model for expression 3
can be tested by its R2
values, which demonstrates that expression 2 and 4 failed to provide
more reliable fit for the thermal degradation data in comparison to expression 3.
Linear method has nothing to do with process, either it is linear or not but it rather assumes
that the experimental data provided is linear [19]. In this method, dependent variable (Y) is
predicted on the basis of intercept and slope for given values of independent variable (X) for
the equation. To get the best fit, it is suggested to linearize the Y data with respect to X data,
as accomplished in expression 3.
3.3 Comparison between literature and models result
S.A Freeman et al, [9] used Null hypothesis (H0) for slopes of three different data sets
(including data of this work) of the same system and found the results using linear regression
for the first order rate constant, k1. In literature [10], exponential regression for the same
work exhibited slightly higher values of k1 under the same experimental data, however, there
is no appreciable variation in the results that may be discussed in details. Values of k1 in
previous literature [9-11] by the same author showed consistency nearly with same R2
values.
This study is in agreement with the linear and exponential regression of first order rate law
with literature. Model results of expressions 1 and 6 are compared in Figure1 for better better
understanding.

7. 7[MM-03]
Proceeding the Regional Conference on Chemical Engineering 2014
Yogyakarta, December 2-3, 2014
ISBN: 978-602-71398-0-0
Figure 1 Comparison of results obtained through expression 1 and 6 to those observed in the
literature.
It can be observed from Figure 1, that at 135 °C and 175 °C model results for expressions, 1
and 6 are slightly lower to those published in the literature. Somewhat higher results for
expression 1 and 6 were noticed at 150 °C and 165 °C.
Second order rate law, results of thermal degradation kinetics data are best fitted by the
models of this study than literature. R2
values of expressions 2 and 4 are nearly equivalent to
those reported in the literature. Higher coefficient of determination values has been noticed
for two expressions of second order kinetics, namely: expression 3 and 5. Results of k2 for
expression 2 and 4 are nearly equal to those reported in the literature, but for expressions 3
and 5 k2 values are different to those published in the literature. Expression 3 and 5 presented
somewhat similar k2 values to those of literature and expression 2 and 4 at 150 °C and 175 °C
only. However, deviation in k2 values is observed at 135 °C and 165 °C. A comparison of
results of k2 of the models is compared with the results of literature in Fig 2.

8. 8[MM-03]
Proceeding the Regional Conference on Chemical Engineering 2014
Yogyakarta, December 2-3, 2014
ISBN: 978-602-71398-0-0
Figure 2 Comparison of results of literature for k2 and second order models of the study.
4. Conclusions
 Thermal degradation data o PZ is found to follow both first order and second order
kinetics.
 Conventional equations failed to present better results for second order kinetics,
especially at 135 °C.
 The results of first order rate models, expressions 1 and 6 and second order models,
expressions 2 and 4 are in agreement with the results of literature.
 Expression 3, in the linear form and expression 5, in quadratic form provides the
most feasible fits with R2
values higher than 0.99.
5. Nomenclature
CPZ = concentration of piperazine at time, t
CPZ0 = concentration of piperazine at time, 0
CO2 = carbon dioxide
Exp = exponent
H0 = null hypothesis
k1 = coefficient of first order rate constant
k2 = coefficient of second order rate constant
Mmoles/kg= millimoles per kilogram

9. 9[MM-03]
Proceeding the Regional Conference on Chemical Engineering 2014
Yogyakarta, December 2-3, 2014
ISBN: 978-602-71398-0-0
MNPZ = 1-nitrosopiperazine
PZ = piperazine
R2
= coefficient of determination
SN2 = nucleophilic substitution reaction
SSR = sum of squares of residuals
6. References
[1] IEA, CO2 emissions from fuel combustion highlights, International Energy Agency
(2012) Edition (2012) 124. (http://www.iea.org/co2highlights/co2highlights.pdf)
[2] A.B. Rao, E.S. Rubin, A Technical, Economic, and Environmental Assessment of Amine-
Based CO2 Capture Technology for Power Plant Greenhouse Gas Control, Environmental
Science & Technology 36 (2002) 4467-4475. (Journal)
[3] G.T. Rochelle, Amine scrubbing for CO2 capture, Science 325 (2009) 1652-1654. Journal
[4] G. Rochelle, E. Chen, S. Freeman, D. Van Wagener, Q. Xu, A. Voice, Aqueous
piperazine as the new standard for CO2 capture technology, Chemical Engineering Journal
171 (2011) 725-733. (Journal)
[5] J.D. Davis, Thermal degradation of aqueous amines used for carbon dioxide capture,
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leaves). (Dissertation)
[6] J. Davis, G. Rochelle, Thermal degradation of monoethanolamine at stripper conditions,
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[7] A.J. Sexton, Amine oxidation in CO2 capture processes, University of Texas, Austin,
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[9] S.A. Freeman, Thermal degradation and oxidation of aqueous piperazine for carbon
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[10] S.A.D. Freeman, Jason, Rochelle, Gary T., Degradation of aqueous piperazine in carbon
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10. 10[MM-03]
Proceeding the Regional Conference on Chemical Engineering 2014
Yogyakarta, December 2-3, 2014
ISBN: 978-602-71398-0-0
[11] S.A. Freeman, G.T. Rochelle, Thermal Degradation of Aqueous Piperazine for CO2
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Acknowledgment
This research is supported by High Impact Research Chancellery Grant
UM.C/625/1/HIR/123 from University of Malaya.