Development and Evaluation of a Novel Method for Determining

Subscriber access provided by University of Florida | Smathers Libraries

Environmental and Carbon Dioxide Issues

Development and Evaluation of a Novel Method for Determining Absorbent Composition in Aqueous Ammonia-based CO and SO and SO Loaded Capture Process Solutions via FT-IR Spectroscopy 2

32-

42-

Lichun Li, Robert Bennett, William Owen Conway, Hai Yu, Sarah Clifford, Marcel Maeder, and Graeme Puxty Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.8b00762 • Publication Date (Web): 26 Jun 2018 Downloaded from http://pubs.acs.org on June 27, 2018

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 26 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

1

Development and Evaluation of a Novel Method for Determining

2

Absorbent Composition in Aqueous Ammonia-based CO2 and SO32- and

3

SO42- Loaded Capture Process Solutions via FT-IR Spectroscopy

4

Lichun Li*,a,b , Robert Bennetta, William Conwaya, Hai Yua, Sarah Cliffordb, Marcel Maederb,

5

and Graeme Puxtya

6

a

CSIRO Energy, 10 Murray Dwyer Circuit Mayfield West NSW 2304 Australia

7

b

Department of Chemistry, School of Environmental and Life Sciences, The University of

8

Newcastle, Callaghan, NSW 2308, Australia

9

* Corresponding author – [email protected]

10

1 ACS Paragon Plus Environment

Energy & Fuels

11

TOC Standard solutions

0.4

= 0.3 – 6.0 M = 0.0 – 3.5 M = 0.0 - 1.5 M = 0.0 - 1.5 M

6

FT-IR Calibration Spectra

0.3

PLSR

0.2

Model

PLSR model prediction (M)

[NH3] [CO2] [SO 32-] [SO 42-]

...

Absorbance

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 2 of 26

[NH3] [CO2] [SO32-] [SO42-]

5 4 3 2 1 0

0.1

0

1

2

3

4

5

6

Experimental Concentration(M) 0 1800

1600

1400

1200

1000

800

Wavenumber (cm-1)

12 13

Abstract

14

CO2 capture using aqueous ammonia is a potentially attractive option for emissions

15

reductions from energy production and industrial processes. From an operational perspective,

16

the capture absorbent must be monitored continuously to maintain the maximum efficiency of

17

the capture process. In practice the composition of the absorbent is typically evaluated offline

18

and retrospectively via wet chemistry methods, delaying any necessary variations to the

19

process conditions to maintain maximum efficiency. Online absorbent monitoring methods

20

incorporating spectroscopy via Raman or Fourier transform infra-red (FT-IR) are attractive

21

options due to their rapid response times and flexibility of the resulting output to be

22

incorporated directly into process control packages. The present study outlines an evaluation

23

of the FT-IR spectroscopic technique with analysis via Partial Least Squares regression

24

(PLSR) for a range of dilute to concentrated aqueous ammonia absorbents from ~ 0.3 – 6.0 M,

25

and over a range of CO2 loadings from ~ 0.0 – 0.6 moles CO2 / mole NH3. The water

26

concentration in the samples ranges from ~ 35.2 – 55.2 M. The effect of interfering SOx

27

species on the FT-IR method has been evaluated by incorporating dissolved SO32- and SO422 ACS Paragon Plus Environment

Page 3 of 26 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

28

components into the solutions from 0.0 – 1.5 M. Analysis results in accurate concentrations

29

for all analytes. The robustness of the analysis results has been evaluated and discussed.

30

Additionally, FT-IR spectroscopy with PLSR was compared with conventional titration

31

methods for a selected series of mixed NH3/CO2 standard solutions and a series of liquid

32

samples from a bench-scale CO2 absorption process. At low concentrations where total NH3

33

concentration is < 4.0 M and total CO2 concentration is < 1.5 M, both the combined PLSR

34

with FT-IR method, and the conventional potentiometric titration methods, were suitable for

35

the evaluation of the liquid compositions. While at concentrations out of the low

36

concentration range, the combined PLSR and FT-IR method was proven to be more robust

37

and accurate than the conventional potentiometric titration methods. However, given the

38

simplicity and rapid turnaround of FT-IR spectroscopy in combination with PLSR we

39

consider this to be a superior and flexible technique for monitoring of CO2 loaded aqueous

40

ammonia solutions.

41

Keywords: Infrared spectroscopy; partial least square regression; ammonia; CO2 capture;

42

Multivariate data analysis; chemistry, chemical engineering, equilibrium.

43

Introduction

44

Aqueous ammonia has been proposed for the chemical removal of CO2 from exhaust gas 1-4

45

streams emerging from fossil fuel-fired power stations and other industrial sources

46

Compared with the widely applied aqueous alkanolamine monoethanolamine (MEA), high

47

CO2 removal efficiency

.

5, 6

, low energy requirement for solvent regeneration 6, potential for


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 4 of 26

7, 8

48

simultaneous removal of multiple acid gases including CO2, SOx and NOx

49

production of value added products (NH4HCO3)

50

absorbents as a superior alternative for post combustion CO2 capture. The potential of

51

simultaneous removal of acid gases including CO2 and SOx enhances process efficiency

52

compared to separate removal steps resulting in significant reductions in capital and operating

53

costs 9, 10.

7

, and potential

position aqueous ammonia-based

54

From a practical perspective, monitoring of the aqueous ammonia absorbent composition

55

(total ammonia concentration ([NH3]tot), CO2 loading (α), water content ([H2O]) and other

56

dissolved salt concentrations) is a critical undertaking during the CO2 absorption process

57

operation as it conveys the operational driving force for CO2 absorption and quantifies the

58

potential efficiency for ongoing and stable CO2 removal. Traditionally, determination of total

59

ammonia concentration and total CO2 concentration is evaluated by wet-chemistry methods

60

including titrations and total organic carbon (TOC), and, correspondingly, SOx by total

61

inorganic sulfur (TIS). These techniques are slow, retrospective, and labor intensive. On the

62

other hand, attempts to determine the liquid phase composition using Raman and

63

Fourier-transform infrared (FT-IR) spectroscopies have been developed recently for a small

64

number of aqueous amine systems 11-14. The distinct advantage of these measurements is that

65

they are rapid and simple and have the potential to be incorporated into on-line process

66

control packages which can continuously optimize operating conditions to maximize

67

absorbent performance in real-time. The practical application of spectroscopic analysis for

68

determining the liquid phase composition of the acid gas reacted amine solutions can be 4 ACS Paragon Plus Environment

Page 5 of 26 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

69

divided into two different categories.

70

Firstly, the spectroscopic information has been used for the quantitative determination of

71

the concentrations of all chemical species in CO2 containing amine solutions (speciation). For

72

a typical primary/secondary/tertiary amine absorbent, numerous species are produced upon

73

reacting with CO2 including amine, protonated amine, carbamate species, bicarbonate,

74

carbonate and water. The determination of the complete speciation is based on the validity of

75

Beer-Lambert’s law that includes the following assumptions 1) the FT-IR spectra of the

76

mixture are simply a sum of the individual contributions of each of the independent species; 2)

77

the intensity of each pure species at a fixed wave number is considered to have a linear

78

relationship with the concentration of the species. Therefore, the knowledge of the molar

79

absorption spectra of all species are essential. A substantial library of reference measurements

80

of the spectra of each individual species with various concentrations are required to

81

determine the molar absorption. It is often difficult to isolate a number of the individual

82

species such as carbamate species due to its instability. The determination of the absorption

83

spectra of carbamate species often requires assumptions, for example, the carbamate is the

84

only dissolved CO2 “sink” upon reaction of the amine with CO2 at low CO2 loadings 11, 15, 16.

85

Nevertheless, this method has been applied to determine the chemical speciation in several

86

amine systems, including diethanolamine (DEA)

87

2-amino-2-methyl-1-propanol (AMP) 17.

11, 17

, monoethanolamine (MEA)

17

,

88

Secondly, the combination of spectroscopic measurements and multivariate calibration

89

approaches such as Partial Least-Square Regression (PLSR) has been applied to extract the 5 ACS Paragon Plus Environment

Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 6 of 26

90

chemical composition directly from the FT-IR spectra. Briefly, combination of the FT-IR

91

measurement technique with the PLSR algorithm enables the determination of total

92

concentrations of the dominant chemical species by calibrating a series of samples with

93

known compositions. PLSR has found a large number of applications in many fields of

94

chemical analysis while its mathematical background is also well known and documented

95

18-20

96

and concentrations alone, and does not require peak assignments or additional measurements

97

to determine the molar absorptivity of individual species. This positions PLSR as the ideal

98

method for the analysis of chemical composition in complicated chemical systems. Further,

99

PLSR is well suited to the analysis of solutions for which spectral overlap occurs between

100

. PLSR is significantly more robust than method 1 using the individual component spectra

different species.

101

Briefly, PLSR is a calibration based method which requires calibration samples of known

102

composition. These calibration samples are used to build a PLSR model, which is then

103

validated by a test series of separate samples of known composition. An important

104

consideration is that the calibration samples must cover the range of concentrations expected

105

to be found in samples to be analyzed. Extrapolation outside the range of calibration will

106

result in increased error in the predicted values. It should also be noted that PLSR methods

107

are only suitable for situations where a linear or weakly nonlinear relationship exists between

108

the predicted variables and the measured variables. The combination of FT-IR spectroscopy

109

and aqueous amine/ammonia/CO2/water systems adheres to such a relationship. While there

110

is complexity in terms of the chemical speciation that can form as CO2 is absorbed into the 6 ACS Paragon Plus Environment

Page 7 of 26 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

111

ammonia solutions, the relationship between all components remains linear allowing the use

112

of total concentrations as a variable.

113

Our group has recently developed a PLSR method for the analysis of FT-IR spectra in a

114

binary amine system incorporating MEA and 3-piperidinemethanol (3-PM) as the capture

115

absorbent

116

concentrations of CO2, SOx, and a CO2 capturing agent (β-alanine) during a PCC pilot plant

117

trial that enables prediction of species concentration from FT-IR spectra to within 0.05 mol/L

118

(95% confidence interval)

119

determination of liquid composition is extended to the aqueous ammonia-based CO2 loaded

120

solvents that incorporates additional SO32- and SO42- ions. There are two major novelties of

121

this work. The first is the use of a sample injection cell for the FT-IR spectroscopic

122

measurements to minimize the effect of evaporative losses of ammonia on the sample spectra.

123

Secondly, compared with traditional amine systems, the SO32- and SO42- species have been

124

included in the aqueous ammonia based solvents here for the first time. This significant step

125

allows the FT-IR and PLSR method to be expanded and applied to both absorber and

126

pre-treatment columns for the determination of liquid compositions. To investigate the

127

application of FT-IR with PLSR to the mixed NH3/CO2/SO32- /SO42-/H2O solutions, a series

128

of 67 sample solutions covering a wide range of ammonia concentrations from ~ 0.3 to 6.0 M,

129

CO2 loadings from ~ 0.0 to 0.6 moles CO2 per mole of NH3, SO32- concentrations from 0.0 to

130

1.5 M, SO42- concentrations from 0.0 to 1.5 M were prepared and equilibrated for the FT-IR

131

measurements. The water concentrations in these solutions range from ~35.2 - 55.2 M. PLSR

12

. A similar method has also been effectively applied for monitoring of the

21

. In this work, FT-IR spectroscopy with PLSR analysis for the


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 8 of 26

132

analyses

133

(www.jplusconsulting.com/products/reactlab-co2/). In addition, a series of 19 mixed

134

NH3/CO2 standard solutions were analyzed via potentiometric titrations to compare the

135

multivariate spectroscopy approach with the traditional wet chemistry analysis for total NH3

136

and CO2 loading.

137

Materials and Methods.

138 139

were

performed

using

software

ReactLab_CO2

Chemicals and Reagents. Ammonium bicarbonate, (NH4HCO3, >99%, Sigma Aldrich), ammonium sulfite

140

monohydrate

141

((NH4)2SO4, >99%, Sigma Aldrich), and methanol (>99%, Sigma Aldrich) were all used as

142

supplied without further purification. Analytical grade aqueous NH3 (28–30 wt %) was

143

purchased from Sigma Aldrich and the concentration of the stock NH3 solution was

144

determined by potentiometric titration of a diluted solution using a standardized HCl solution

145

(0.100 M, Sigma Aldrich). All samples were prepared using Milli Q water and volumetric

146

glassware. A summary of the liquid compositions of the 67 standard sample solutions is

147

shown in Table 1. The numerical details of the chemical composition of the samples are

148

indicated in Table S1 of the Supporting Information.

149

((NH4)2SO3.H2O,

>92%,

Sigma

Aldrich),

ammonium

sulfate

Table 1. Liquid composition of the 67 standard samples in three groups [NH3] (M)

α (mol CO2/mol NH3)

[SO32-] (M)

[SO42-] (M)

0.34 – 5.63

0.00 – 0.57

–

–

Group I (samples 1-29 )


Page 9 of 26 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

Group II

0.125 – 6.00

–

0.063 – 1.50

0.063 – 1.50

0.125 – 5.74

0.00 – 0.59

0.0 – 1.50

0.0 – 1.50

(samples 30-45) Group III (samples 46-67)

150

The 67 standard samples can be divided into three groups as follows: group I) mixed

151

NH3/CO2/H2O standard samples; group II) (NH4)2SO3/(NH4)2SO4/H2O standard solutions;

152

group III) mixed NH3/CO2/SO32-/SO42-/H2O standard solutions. For the group I mixed

153

NH3/CO2/H2O standard sample solutions, two original stock solutions were prepared. Firstly,

154

a stock solution of CO2 free NH3, with a maximum ammonia concentration of 5.631 M, was

155

prepared via dilution of the concentrated ammonia solution. Secondly, the stock solution of

156

5.631 M ammonia with an additional CO2 loading of 0.567 moles CO2/mole of NH3 was

157

prepared by mixing the concentrated ammonia solution with ammonium bicarbonate in Milli

158

Q water. Additional samples in group I were prepared from dilution of the two stock solutions

159

(concentrated CO2 loaded NH3 solution and CO2 free NH3 solutions) with each other, and

160

water, to achieve intermediate ammonia concentrations and CO2 loadings. For the group II

161

(NH4)2SO3/(NH4)2SO4/H2O standard solutions, two new stock solutions containing 1.5 M

162

(NH4)2SO3 and 1.5 M (NH4)2SO4/H2O were prepared and diluted in a similar procedure to

163

prepare

164

NH3/CO2/SO32-/SO42-/H2O standard solutions, all samples were prepared by mixing desired

165

amounts of concentrated ammonia solution, NH4HCO3, (NH4)2SO3 and (NH4)2SO4, with

166

Milli Q water. The known compositions of these standard sample solutions were used for the

167

calibration of the PLSR model. The concentration of H2O was calculated from the

intermediate

concentration

solutions.

For

the

group

III

mixed


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 10 of 26

168

concentrations of NH3, CO2, SO32- and SO42-, assuming that the addition of inorganic salts

169

and CO2 will not affect the density of the solvent (H2O) significantly. This has been proved

170

by experimental measurements that the density of 3 M (NH4)2SO4 solution is 1.1607 g/ml 22,

171

and the density of 6 M MEA solution with CO2 loading of 0.5 (moles CO2 / mole MEA) is

172

1.1170 g/ml 23.

173 174

FT-IR spectroscopy The experimental procedure for the measurement of the FT-IR spectra of aqueous 12

175

amine solutions has been described in detail in our previous work

176

were recorded on a Bruker Alpha FT-IR Spectrometer equipped with a Platinum ATR

177

accessory and diamond ATR crystal. Background spectra were recorded in an air atmosphere

178

at room temperature. Multivariate spectra of the samples were measured from 600.0 – 4000.0

179

cm-1 by injecting sample solutions into a covered cell with an ATR crystal window. The

180

purpose of employing the sample cover with injection port is to minimize the impact of

181

ammonia loss (via evaporation) during the measurement. A total of 16 scans with a resolution

182

of 4.0 cm-1 were recorded for each sample and averaged within the Bruker OPUS software to

183

produce a single spectrum for PLSR analysis. Total acquisition times for a single spectrum is

184

in the order of ~30.0 seconds. It should be noted that all samples were equilibrated at room

185

temperature for > 24.0 hours prior to collecting the FT-IR spectra to ensure complete

186

equilibration was achieved.

. Briefly, FT-IR spectra


Page 11 of 26 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

187

Energy & Fuels

Partial Least-Squares Regression (PLSR)

188

A robust PLSR model for the multicomponent NH3/CO2/SO32-/SO42-/H2O solutions

189

requires knowledge of all relevant concentrations in the calibration samples. FT-IR spectra

190

were acquired for a series of nm = 67 pre-prepared standard samples with known total

191

concentrations of NH3, CO2, SO32-, SO42- and H2O. These absorption spectra, measured at nl

192

wavenumbers from the FT-IR are recorded and stored as nm rows in a matrix Y. The known

193

concentrations

194

, , , , and , each vector having nm elements.

of

the

analytes

are

stored

in

individual

column

vectors

195

For each analyte, with known spectra matrix Y and concentration vector q, a matrix X

196

with orthogonal columns (scores) and a matrix P (loadings) as well as a vector b are

197

computed in such a way that the residual error matrix R and vector r given in equation (1) are

198

minimized.

Y= X × P+ R

and

q=X × b+r

(1)

199

The PLSR prediction of a property of a new unknown sample with spectrum ysample

200

requires the determination of its representation as a row vector xsample (calculated from ysample

201

and P) from which the predicted quality qsample can be calculated as qsample = xsample × b. The

202

details of the PLS algorithms can be found in several publications 24, 25.

203

The number of factors or columns in X for the calculation purpose to use in the PLSR 12

204

model was determined through an iterative “leave-one-out” cross validation

205

calibration data set with known predicted variables was employed to determine this number, 11 ACS Paragon Plus Environment

. The

Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

206

Page 12 of 26

which can be different for each analyte.

207

To measure the prediction performance of the PLSR model, the mean squared error

208

(MSE) between the experimental and model predicted values can be calculated using the

209

following equation.

MSE =

∑ ( − )

(2)

210

In the above equation, n is the total number of data points, and Known and PLSR

211

represent the known and model calculated concentration values of all the predicted analytes

212

including [NH3], [CO2], [SO32-], [SO42-] and [H2O]respectively.

213

Titrimetric determination of total ammonia concentration

214

Titration of total ammonia concentration in dilute aqueous ammonia solutions in the

215

presence and absence of CO2 was performed on an automated titration apparatus which has

216

been described in detail in previous work

217

presence and absence of CO2 were diluted to ~ 0.5 M prior to titration using volumetric

218

glassware. An aliquot (1.00 mL) of the diluted aqueous ammonia solution was then acidified

219

with HCl solution (10.00 mL, 0.10M) and back titrated with a standardized 0.10 M NaOH

220

solution. Note that the concentration of the NaOH solution was standardized with standard

221

0.25 M KHP (potassium hydrogen phthalate) solution. The acidified titration solutions were

222

initially purged with N2 gas (> 5.0 minutes) to remove any residual CO2 dissolved in the

223

liquid and present in the gas headspace of the vessel. The mV signal of the solution was

224

recorded throughout the titration and converted into pH during the analysis of the titration 12

26, 27

. Initially, aqueous ammonia solutions in the

ACS Paragon Plus Environment

Page 13 of 26 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

225 226

Energy & Fuels

data using Reactlab pH titration software (http://jplusconsulting.com/products/reactlab-ph/). Titrimetric determination of total CO2 concentration

227

A Mettler Toledo T50 Auto titrator was used for the determination of total CO2

228

concentration in the aqueous ammonia solutions. To do so, a 0.50 M NaOH solution was

229

sequentially added to a titration beaker containing a 40.0ml aliquot of methanol until the pH

230

of the methanol solutions was adjusted to 11.0. A 5.0 mL aliquot of CO2 loaded ammonia

231

solution was dosed into the methanol solution resulting in a decrease in pH of the methanol

232

solution (due to the presence of CO2 acting as an acid). Additional amounts of the 0.50 M

233

NaOH solution were dosed into the methanol/NH3/CO2 sample to return the pH of the

234

solution to 11.0. The total CO2 concentration in the solution can be calculated from the

235

second volume of NaOH dosed into the solution to raise the pH back to 11.0 in equation (3).

!CO $(%) =

236

' ( )*+, × )*+, .'*/012 ' ( 3*'4/5 *6656

(3)

Results and discussion

237

A total of 67 standard samples were prepared and analyzed using the FT-IR and PLSR

238

method. Figure 1 shows the composition of all standard samples graphically as well as their

239

distribution within the set of calibration samples. The full analytical details of the

240

compositions of the 67 standard samples can be found in Table S1 of the Supporting

241

Information. The data set consisting of the 67 standard samples was divided into two groups

242

for calibration and validation of the PLSR model. A set of 45 samples was selected to build

243

the PLSR model (calibration sample set, dots) while the remaining 22 samples were used to 13 ACS Paragon Plus Environment

Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

244

Page 14 of 26

validate the model (validation sample set, open circles).

245 246

Figure 1. Calibration matrix - blue dots (●) = group I calibration samples; red dots (●) =

247

group II calibration samples; black dots (●) group III calibration samples; blue circles (○) =

248

group I validation samples; red circles (○) = group II validation samples, black circles (○)

249

group III validation samples. NOTE - Some overlap between samples exists due to the plot of

250

the sum of the concentrations of [SO32-] + [SO42-] here (the ratios between [SO32-] and [SO42-]

251

may differ).

252

FT-IR spectra

253

Some examples of the FT-IR spectra of calibration samples containing different ammonia

254

concentrations in the presence and absence of CO2, and varying amounts of SO32-, SO42-, and

255

their combinations with CO2, are presented in Figures 2 (a), (b), (c) and (d). Note that, the

256

spectra presented here in Figure (2) only covers the wavenumber range of 800.0 – 1800.0

257

cm-1 for clarity given this is the region richest in peaks. The complete spectra (600.0 – 4000.0

258

cm-1) was used for the analyses. Broadly, from the spectra in Figure 2 (a) and (b) it can be 14 ACS Paragon Plus Environment

Page 15 of 26

259

seen that the different absorbent compositions result in unique but overlapping spectra which

260

lays the foundation for the PLSR model calibration. Secondly, addition of new species into

261

the ammonia solutions is correspondingly accompanied by significant spectral changes. To

262

demonstrate this, the addition of CO2 into fresh ammonia solutions is followed by peak

263

formation in the wavenumber range from 800.0 – 1600.0 cm-1 while the addition of SO32- into

264

ammonia solutions is followed by new unique spectral peaks forming in the wavenumber

265

range between 800.0 – 1000.0 and 1300.0 – 1500.0 cm-1. The addition of SO42- into ammonia

266

solutions results in significant change of the FT-IR spectra in the wavenumber range from

267

1000.0 – 1200.0 cm-1. However, one of the most significant advantages of using the PLSR

268

model is the ability of the model to act on a system in the presence of interfering signals. 0.30

0.30

(b) [NH3]=5.50 M

0.25

0.25

0.20

0.20

Absorbance

Absorbance

(a)

0.15

[NH3]=0.34 - 5.63 M

0.10

[CO2]=0.00 - 3.02 M

0.15

0.10

0.05

0.05

0.00

0.00 1800

1600

1400

1200

1000

800

1800

1600

Wavenumber (cm-1)

269

1400

1200

1000

800

1000

800

Wavenumber (cm-1)

0.40

0.30

(c)

(d) [NH3]=3.85 M, [CO2]=0.59 M

0.35 0.25

0.30

[NH3] = 3.0 M; [SO42-]= 1.5 M

0.25

[NH3] = 3.0 M; [SO32-]=0.75M ;[SO42-]=0.75 M [NH3] = 3.0 M; [SO3

0.20

2-]=

0.20 Absorbance

Absorbance

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

1.5 M

[SO32-] =0.19 M;[SO42-]=0.063 M 0.15

[SO42-]= 1.00 M [SO32-]= 0.50 M

0.15 0.10

0.10 0.05

[SO42-]=0.063 M [SO32-]=0.00 M; [SO42-]=0.00 M

0.05 [NH3] = 0.125; [SO3

0.00 1800

270 271

1600

2-]=0.063 M

1400 1200 Wavenumber (cm-1)

[NH3] = 0.125 M; [SO42-]= 0.063 M 1000

0.00

800

1800

1600

1400 1200 Wavenumber (cm-1)

Figure 2. FT-IR spectra (a) ammonia concentration varying from 0.34 to 5.63 without 15 ACS Paragon Plus Environment

Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 16 of 26

272

pre-loaded CO2; (b) ammonia concentration ~5.50 M and CO2 concentration varying from 0.00

273

to 3.02 M; (c) ammonia concentration varying from 0.125 to 3.0 M, SO32- and SO42-

274

concentration varying from 0.063 to 1.50 M; (d) ammonia concentration ~3.85 M, CO2

275

concentration ~ 0.59 M, SO32- and SO42-concentration varying from 0.00 to 0.50 M and 0.00 to

276

1.00 M.

277

PLSR model validation

278

A PLSR model has been applied for the determination of the liquid composition in the

279

complex multi-component system of the aqueous ammonia systems here. The predicted

280

variables employed for the PLSR calibration are as follows; total ammonia concentration

281

([NH3]), total CO2 concentration ([CO2]), SO32- concentration ([SO32-]), SO42- concentration

282

([SO42-]), and H2O concentration ([H2O]). Initially, the PLSR model was evaluated against

283

the measured FT-IR spectra of the 45 calibration samples. The developed PLSR model was

284

then applied to the 22 validation sample set to check the applicability of the model. PLSR

285

predicted concentrations, plotted against the known concentrations for NH3, CO2, SO32-,

286

SO42-, and H2O, for all 67 samples, are presented in Figure 3(a) - (d). Data corresponding to

287

the 45 calibration samples are presented using full dots while the data of the 22 validation

288

samples are presented as open circles.


Page 17 of 26

(b) CO2

6.00

3.50

5.00

3.00 2.50

4.00

[CO2]PLSR (M)

[NH3]PLSR (M)

(a) NH3

3.00 2.00

2.00 1.50 1.00

1.00

0.50 0.00

0.00 0.00

1.00

2.00

289

3.00 4.00 [NH3]Known (M)

5.00

0.00

6.00

0.50

(c) SO32-

1.00

1.50 2.00 [CO2]Known (M)

2.50

3.00

3.50

(d) SO42-

1.60

1.60

1.40

1.40

1.20

1.20 [SO42-]PLSR (M)

[SO32-]PLSR (M)

1.00 0.80 0.60

1.00 0.80 0.60

0.40

0.40

0.20

0.20

0.00

0.00 0.00

290

0.50

1.00 [SO32-]Known (M)

1.50

0.00

0.50

1.00 [SO42-]Known (M)

1.50

(e) H2O 60.00 55.00 [H2O]PLSR (M)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

50.00 45.00 40.00 35.00 30.00 30.00

291

35.00

40.00 45.00 50.00 [H2O]Known (M)

55.00

60.00

292

Figure 3. Parity plot of the model predicted total NH3 concentration (a), total CO2

293

concentration (b), SO32- concentration (c), SO42- concentration (d) and H2O concentration

294

versus the prepared concentration of the 45 calibration samples (dots) and 22 validation

295

samples (circles);


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 18 of 26

296

Figure 3 (a) - (e) demonstrate that the PLSR predicted variables including total NH3, CO2,

297

SO32- , SO42-and H2O concentrations are in excellent agreement with the known prepared

298

concentrations for both the calibration and validation sample sets. This observation strongly

299

indicates the successful application of the FT-IR spectroscopy with PLSR model calculation

300

method for the determination of chemical composition of the complex multi-component,

301

mixed NH3/CO2/SO32-/SO42-/H2O solutions. To further evaluate the predictability of the

302

model, the mean squared error (MSE) between the experimental and estimated values for all

303

variables, and for each predicted variable, were calculated and presented in Table 2.

304

Table 2. Mean squared error (MSE) for all predicted variables and for each predicted

305

individually from the PLSR model. MSE

MSE

Calibration data set

Validation data set

All Variables (M)

0.0076

0.0081

NH3 concentration (M)

0.0160

0.0270

CO2 concentration (M)

0.0012

0.0008

SO32- concentration (M)

0.0003

0.0007

SO42- concentration (M)

0.0001

0.0007

H2O concentration (M)

0.0210

0.0270

306

The MSE values for all variables in the calibration and validation data set are 0.0076 and

307

0.0081, again suggesting the excellent prediction capability of the PLSR analysis.

308

Specifically, the excellent agreement between the PLSR model predicted and experimental

309

data for the 22 validation sample data set is confirmation of the PLSR model and its robust 18 ACS Paragon Plus Environment

Page 19 of 26 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

310

prediction performance. Compared with our previous publication, the MSE values for all

311

variables in the calibration data set have improved from 0.124 to 0.0076 12. This significant

312

improvement in the performance of PLSR method is likely due to the reason that the current

313

study contains a larger calibration data set with 45 calibration samples while our previous

314

publication only contained 18 calibration samples.

315

Therefore, the current developed novel method combining FT-IR spectroscopy with

316

PLSR analysis for the evaluation of mixed NH3 solutions containing CO2, SO32-, SO42- and

317

H2O has been validated here covering a wide range of concentrations including ammonia

318

concentration (~ 0.3 to 6.0 M NH3), CO2 loading (~ 0.0 to 0.6 mol CO2/mol NH3), SO32-

319

concentration (~ 0.0 to 1.5 M), SO42- concentration (~ 0.0 to 1.5 M) and H2O concentration (~

320

35.2 - 55.2 M).

321

Comparison between titration and PLSR models

322

Comparison of the performance between the FT-IR spectroscopy/PLSR method and the

323

traditional titration method was conducted in this section. It should be noted that the

324

concentrations of SO32- and SO42- are known from the initial makeup of the solution while the

325

titrations here are more relevant for determination of the NH3 and CO2 concentrations given

326

each of these species is volatile under the conditions employed here. The total ammonia

327

concentration and CO2 loading determined via both methods are compared herein for a

328

sample set containing 19 mixed NH3/CO2 solutions from group I. The detailed chemical

329

composition of the 19 mixed NH3/CO2 solutions can be found in Table S1, Supporting


Energy & Fuels

330

Information. The composition of the 19 test solutions was selected such that it sits within the

331

calibration range of the PLSR model and covers a wide range of ammonia concentrations and

332

CO2 loadings. A parity plot of model predicted results from PLSR and titration results against

333

the known concentrations are shown in Figure 4 (a) and (b). 3.50

6.00

(b)

(a) 3.00

4.00 Titration PLSR model

3.00 2.00

2.50 2.00

Titration PLSR model

1.50 1.00

1.00

0.50 0.00

0.00 0.00

334

[CO2]Titration, PLSR (M)

5.00

[NH3]Titration, PLSR (M)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 20 of 26

1.00

2.00

3.00 4.00 [NH3]Known (M)

5.00

6.00

0.00

0.50

1.00

1.50 2.00 [CO2]Known (M)

2.50

3.00

3.50

335

Figure 4. (a) Parity plot of the model predicted and titration determined total ammonia

336

concentration against the prepared concentration of the 19 mixed NH3/CO2 samples; (b)

337

parity plot of the model predicted and titration determined total CO2 concentration against the

338

prepared concentration of the 19 mixed NH3/CO2 samples.

339

From Figure 4 (a) and (b), both methods can successfully determine the total ammonia

340

and CO2 concentrations, revealed from the excellent agreement between the PLSR model

341

predicted and titration results. It is worth noting that for high concentration conditions where

342

the ammonia concentration is > 4.0 M, and CO2 concentration is > 1.5 M, FT-IR

343

spectroscopy with PLSR model shows better predictability compared to the traditional

344

titration method. This is likely due to the higher experimental error caused by manual aspects

345

during the titration method which involves significant sample handling, transferring, dilution

346

and mixing procedures. 20 ACS Paragon Plus Environment

Page 21 of 26

347

Determination of liquid composition during CO2 absorption process

348

A bench-scale CO2 absorption experiment was performed by bubbling CO2 gas (450.0

349

mL.min-1) through a 1.0 L of a 1.0 M aqueous ammonia solution for a total of 60.0 minutes.

350

Liquid samples were taken at intervals; 0.0, 15.0, 30.0, 45.0 and 60.0 minutes. Collected

351

samples were left overnight for complete equilibration before analysis using the combined

352

PLSR and FT-IR method. To validate the method, samples were analysed in parallel via the

353

potentiometric titration method for the determination of the liquid compositions including

354

total ammonia and total CO2 concentrations, respectively. The resulting total NH3

355

concentrations and total CO2 concentrations determined from both PLSR and titration

356

methods are plotted against time in Figure 5. The numerical data can be found in Table S2 in

357

the supporting information section. 1.40 0.50 1.20

0.80

0.30 [NH₃]-FT-IR and PLSR

0.60

[NH₃]-Titration [CO₂]-FT-IR and PLSR

0.40

[CO2]tot (M)

0.40

1.00

[NH3]tot (M)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

0.20

[CO₂]-Titration 0.10

0.20 0.00

0.00 0

15

30

45

60

Time (minute)

358 359

Figure 5. Total NH3 and CO2 concentrations, respectively, from the bench-scale CO2

360

absorption samples. Squares – total NH3 concentration, circles – total CO2 concentration,

361

solid markers - results from FT-IR and PLSR method, hollow markers – results from titration

362

method.


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 22 of 26

363

From the data in Figure 5 both methods can successfully determine both the total NH3

364

and CO2 concentrations, respectively, with the values determined from the PLSR method

365

showing excellent agreement with the titration method within ~ 5.0%.

366

Conclusions

367

This work describes the development and evaluation of the combination of FT-IR

368

spectroscopy with PLSR analysis for the evaluation of mixed NH3 solutions containing

369

multiple components including CO2, SO32-, SO42- and H2O. The PLSR model has been

370

validated here using known calibration samples covering a wide range of concentrations

371

including ammonia concentrations (~ 0.3 to 6.0 M NH3), CO2 loadings (~ 0.0 to 0.6 mols

372

CO2/mol NH3), SO32- concentration (~ 0.0 to 1.5 M) and SO42- concentration (~ 0.0 to 1.5 M),

373

and H2O concentration (~ 35.2 - 55.2 M). Mean squared error (MSE) values for all analytes

374

improved significantly with a large calibration data set employed for developing the PLSR

375

model.

376

For some mixed NH3/CO2 standard sample solutions and a series of liquid samples

377

generated from a bench scale CO2 absorption process, the data pertaining to total ammonia

378

concentration and CO2 loading determined from the FT-IR spectroscopy with PLSR model

379

calculation method were compared with the data generated from traditional titration methods.

380

Results show that both methods can be used to determine total ammonia and CO2

381

concentrations in the mixed NH3/CO2 solutions. However, for aqueous ammonia

382

concentrations > 4.0 M and total CO2 concentrations above > 1.5 M, FT-IR spectroscopy with


Page 23 of 26 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

383

PLSR is the preferred method due to potential for interfering phenomena involving

384

evaporative losses when using traditional wet chemistry methods. More importantly, FT-IR

385

spectroscopy with PLSR is superior in terms of measurement and analysis time and overall

386

robustness. Uniquely, the method here has been demonstrated to be suitable to determine total

387

SOx content of the solutions (as sulfate and sulfite) together with the ammonia, CO2, and

388

water content from the same spectral data. The FT-IR and PLSR techniques developed here

389

are in the process of being employed at a power station for on-line analysis of pilot plant

390

samples.

391

Acknowledgement

392

The authors wish to acknowledge financial assistance provided through CSIRO Energy. The

393

views expressed herein are not necessarily the views of the Commonwealth, and the

394

Commonwealth does not accept responsibility for any information or advice contained herein.

395

This work was also funded by Department of Planning and Environment through the Coal

396

Innovation NSW Fund, which is administered by the Minister for Minister for Resources,

397

Minister for Energy and Utilities. Any views expressed herein do not necessarily reflect the

398

views of Coal Innovation NSW, the Department of Planning and Environment or the NSW

399

Government.

400

Supporting information

401 402

The Supporting Information is available free of charge on the ACS Publications website at DOI:


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 24 of 26

403

References

404

1.

405

Trialling Aqueous NH3 Based Post Combustion Capture in a Pilot plant at Munmorah Power Station: Solvent

406

Regeneration Energy. Chemeca 2012: Quality of life through chemical engineering: 23-26 September 2012,

407

Wellington, New Zealand 2012, 1097.

408

2.

409

Chilled Ammonia Process at AEP’s Mountaineer plant, Proceedings of MEGA Conference, Baltimore, Maryland,

410

USA, 2008; 2008.

411

3.

412

International Journal of Greenhouse Gas Control 2010, 4, (2), 131-136.

413

4.

414

absorption kinetics and ammonia loss. Greenhouse Gases: Science and Technology 2013, 3, (3), 231-245.

415

5.

416

gas emissions. Science of The Total Environment 1999, 228, (2–3), 121-133.

417

6.

418

CO2 capture by aqueous ammonia. Fuel Processing Technology 2005, 86, (14–15), 1533-1546.

419

7.

420

Greenhouse Gases: Science and Technology 2012, 2, (3), 200-208.

421

8.

422

and NOx. International Journal of Environmental Technology and Management 2004, 4, (1), 89-104.

423

9.

424

Process for Simultaneous Removal of SOx, NOx, and CO2: A Techno-Economic Analysis. Energy & Fuels 2017,

425

31, (4), 4165-4172.

426

10. Dong, R.; Lu, H.; Yu, Y.; Zhang, Z., A feasible process for simultaneous removal of CO2, SO2 and NOx in

427

the cement industry by NH3 scrubbing. Applied energy 2012, 97, 185-191.

Yu, H.; Li, L.; Morgan, S.; Allport, A.; Cottrell, A.; McGregor, J.; Wardhaugh, L.; Feron, P., Results from

Sherrick, B.; Hammond, M.; Spitznogle, G.; Muraskin, D.; Black, S.; Cage, M. In CCS with Alstom’s

Darde, V.; Thomsen, K.; van Well, W. J. M.; Stenby, E. H., Chilled ammonia process for CO2 capture.

Li, L.; Han, W.; Yu, H.; Tang, H., CO2 absorption by piperazine promoted aqueous ammonia solution:

Yeh, A. C.; Bai, H., Comparison of ammonia and monoethanolamine solvents to reduce CO2 greenhouse

Yeh, J. T.; Resnik, K. P.; Rygle, K.; Pennline, H. W., Semi-batch absorption and regeneration studies for

Yu, H.; Xiang, Q.; Fang, M.; Yang, Q.; Feron, P., Promoted CO2 absorption in aqueous ammonia.

Resnik, K. P.; Yeh, J. T.; Pennline, H. W., Aqua ammonia process for simultaneous removal of CO2, SO2

Hajari, A.; Atanga, M.; Hartvigsen, J. L.; Rownaghi, A. A.; Rezaei, F., Combined Flue Gas Cleanup


Page 25 of 26 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

428

11. Diab, F.; Provost, E.; Laloue, N.; Alix, P.; Souchon, V.; Delpoux, O.; Furst, W., Quantitative analysis of the

429

liquid phase by FT-IR spectroscopy in the system CO2/diethanolamine (DEA)/H2O. Fluid Phase Equilibria

430

2012, 325, 90-99.

431

12. Puxty, G.; Bennett, R.; Conway, W.; Maher, D., A comparison of Raman and IR spectroscopies for the

432

monitoring and evaluation of absorbent composition during CO2 absorption processes. International Journal of

433

Greenhouse Gas Control 2016, 49, 281-289.

434

13. Kachko, A.; van der Ham, L. V.; Bardow, A.; Vlugt, T. J. H.; Goetheer, E. L. V., Comparison of Raman,

435

NIR, and ATR FTIR spectroscopy as analytical tools for in-line monitoring of CO2 concentration in an amine

436

gas treating process. International Journal of Greenhouse Gas Control 2016, 47, 17-24.

437

14. Wong, M. K.; Bustam, M. A.; Shariff, A. M., Chemical speciation of CO2 absorption in aqueous

438

monoethanolamine investigated by in situ Raman spectroscopy. International Journal of Greenhouse Gas

439

Control 2015, 39, 139-147.

440

15. Rogers, W. J.; Bullin, J. A.; Davison, R. R.; Frazier, R. E.; Marsh, K. N., FTIR method for VLE

441

measurements of acid‐gas–alkanolamine systems. AIChE journal 1997, 43, (12), 3223-3231.

442

16. Motang, N. In situ FTIR measurements of the kinetics of the aqueous CO2-monoethanolamine reaction.

443

Stellenbosch: Stellenbosch University, 2015.

444

17. Richner, G.; Puxty, G., Assessing the Chemical Speciation during CO2 Absorption by Aqueous Amines

445

Using in Situ FTIR. Industrial & Engineering Chemistry Research 2012, 51, (44), 14317-14324.

446

18. Rossel, R. A. V., ParLeS: Software for chemometric analysis of spectroscopic data. Chemometrics and

447

Intelligent Laboratory Systems 2008, 90, (1), 72-83.

448

19. Wold, S.; Sjostrom, M.; Eriksson, L., PLS-regression: a basic tool of chemometrics. Chemometrics and

449


450

20. Li, B. B.; Morris, J.; Martin, E. B., Model selection for partial least squares regression. Chemometrics and

451


452

21. Geers, L. F. G.; van de Runstraat, A.; Joh, R.; Schneider, R.; Goetheer, E. L. V., Development of an Online

453

Monitoring Method of a CO2 Capture Process. Industrial & Engineering Chemistry Research 2011, 50, (15),


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 26 of 26

454

9175-9180.

455

22. Goldsack, D. E.; Franchetto, A. A., The viscosity of concentrated electrolyte solutions—III. A mixture law.

456

Electrochimica Acta 1977, 22, (11), 1287-1294.

457

23. Weiland, R. H.; Dingman, J. C.; Cronin, D. B.; Browning, G. J., Density and viscosity of some partially

458

carbonated aqueous alkanolamine solutions and their blends. Journal of Chemical & Engineering Data 1998, 43,

459

(3), 378-382.

460

24. Kramer, R., Chemometric techniques for quantitative analysis. CRC Press: 1998.

461

25. Wold, S.; Sjöström, M.; Eriksson, L., PLS-regression: a basic tool of chemometrics. Chemometrics and

462

intelligent laboratory systems 2001, 58, (2), 109-130.

463

26. Fernandes, D.; Conway, W.; Wang, X.; Burns, R.; Lawrance, G.; Maeder, M.; Puxty, G., Protonation

464

constants and thermodynamic properties of amines for post combustion capture of CO2. The Journal of

465

Chemical Thermodynamics 2012, 51, 97-102.

466

27. Li, L.; Clifford, S.; Puxty, G.; Maeder, M.; Burns, R.; Yu, H.; Conway, W., Kinetic and Equilibrium

467

Reactions of a New Heterocyclic Aqueous 4-Aminomethyltetrahydropyran (4-AMTHP) Absorbent for Post

468

Combustion Carbon Dioxide (CO2) Capture Processes. ACS Sustainable Chemistry & Engineering 2017, 5, (10),

469

9200-9206.

470


Development and Evaluation of a Novel Method for Determining

Recommend Documents