Microemulsification-Based Method: Analysis of Monoethylene Glycol

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Microemulsification-Based Method: Analysis of Monoethylene Glycol in Samples Related to Natural Gas Processing Jaqueline G. da Cunha,† Leandro Y. Shiroma,† Gabriela F. Giordano,† Bruno C. Couto,‡ Rogério M. Carvalho,‡ Angelo L. Gobbi,† Lauro T. Kubota,§,∥ and Renato S. Lima*,† †

Laboratório de Microfabricaçaõ , Centro Nacional de Pesquisa em Energia e Materiais, Campinas, São Paulo 13083-970, Brasil Centro de Pesquisas e Desenvolvimento Leopoldo Américo Miguez de Mello, Petrobras, Rio de Janeiro, RJ, Brasil § Instituto de Química, Universidade Estadual de Campinas, Campinas, São Paulo 13083-970, Brasil ∥ Instituto Nacional de Ciência e Tecnologia em Bioanalítica, Campinas, São Paulo 13083-970, Brasil ‡

Downloaded by UNIV OF ARIZONA on September 4, 2015 | http://pubs.acs.org Publication Date (Web): September 4, 2015 | doi: 10.1021/acs.energyfuels.5b01166

S Supporting Information *

ABSTRACT: The determination of monoethylene glycol (MEG) in samples related to natural gas processing by using the microemulsification-based method (MEC) is portrayed herein. MEC was recently proposed by these authors like a powerful way for the development of point-of-use technologies. It relies on effect of the analyte on formation of microemulsions (MEs), changing the minimum volume fraction of amphiphile needed to get ME. This fraction is the analytical signal in MEC, and its detection depends on a binary chemical information: the cloudy-to-transparent conversion that occurs with microemulsification. Hence, this signal can be precisely detected with naked eyes ensuring not only screening analyses as the most of colorimetrybased rapid testing methods, but also precise determinations. The investigations reported herein are essential for a deeper understanding of the approach. These studies relate to tests of ionic strength-function robustness, considerations about the analytical signal profile, and analyses of MEG in complex samples of regeneration after the use of this dialcohol in pipes of liquefied natural gas processing. The dispersions were composed of water, oleic acid, and ethanol such as hydrophilic (W), hydrophobic (O), and amphiphilic phases, respectively. Analytes were added in the W phase to attain the analytical curves by first preparing W−O mixtures (1:1 v/v) and, then, adding ethanol amphiphile until cloudy-to-transparent transition. For application, the samples were directly used as the W phase. The media were prepared in bottles with the aid of micropipette, whereas the analytical signal was detected in solution by naked eyes. Robustness was expressed as a function of absolute errors calculated for concentrations of analyte (volume fraction of MEG to water, % v/v). Such errors were because changes in ionic strength of W phase by adding the salts: 10.0 and 500.0 mmol L−1 NaCl and 10.0 mmol L−1 Na2SO4, CaCl2, and FeCl3. Conductivities of the W phase ranged from 0.1 to 32.1 mS cm−1. MEC was somewhat robust with absolute errors of 0.18 to 6.47% (v/v). Furthermore, our hypotheses on MEC signal profile were in accordance with experimental results indicating an inverse relationship between the signal and the surface activity phenomenon. Concerning the application, the samples presented color, particulate, high conductivity, and diverse compounds. Despite these drawbacks, MEC outstandingly provided accurate measurements (compared to data of iodometry titration) after simple dilution of the samples in water.

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INTRODUCTION Natural gas is currently a relevant alternative energy matrix on oil because of the progressive raise in oil price and environmental concerns.1 Approximately 25% of world’s primary energy production relates to natural gas. Studies reported in literature show that the global demand for this energy source is expected to grow at rates on the order of 3% per year until 2030.2 Monoethylene glycol (MEG) is used in the processing of natural gas by Petrobras (Brazilian multinational energy corporation) to avoid the clogging of pipes because the formation of hydrates. This dialcohol realizes hydrogen bonds with molecules of water raising the media freezing point. Conversely, MEG is regenerated from the system of gas exploration as it generates piping corrosion, catalyst poisoning, reduction in quality of the final product, and environmental contamination. Therefore, it is important to monitor the concentrations of MEG for evaluating the effectiveness of this regeneration. The method used by Petrobras for determining © XXXX American Chemical Society

monoethylene glycol in regeneration samples relies on iodometry classic titration. The routine of this approach is time-consuming and laborious. In addition, there is an extensive use of chemicals. Samples of regeneration which arise from processing of liquefied natural gas are basically composed of MEG and water with diverse interferents such as metals, anions, and carboxylic acids. In this communication, we address the determination of MEG in complex regeneration samples related to processing of liquefied natural gas (RLNG) by using a method recently proposed by these authors: the microemulsification-based method, called the MEC.3 MEC relies on the effect of analyte contents on the entropy of unstable dispersions (emulsions or Winsor systems) by modifying the surface activity phenomenon which reduces the interfacial tension. It affects the formation of Received: May 26, 2015 Revised: August 31, 2015

A

DOI: 10.1021/acs.energyfuels.5b01166 Energy Fuels XXXX, XXX, XXX−XXX

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Energy & Fuels

measurement of the analytical response in MEC, ΦME, is possible with naked eyes. It enables not only screening analyses (positive/negative data) like the most of colorimetry rapid tests,5 but also precise quantitative assays.3 In colorimetry, the results are affected by subjective uncertainties that arise from personal and surrounding conditions in recording the signals with naked eyes.6 MEC bypasses the use of instrumental detection for precisely quantifying analytes in complex samples with a satisfactory analytical performance as shown in our previous publication.3 This feature surpasses one of the major downsides in the field of point-of-use platforms: the deployment of rapid testing technologies that ensure precise determinations with satisfactory analytical figures of merit.7−12 Our approach meets other important requirements for the development of point-of-use platforms. MEC provides simple, fast, cheap, and portable analyses. Besides, small volumes of sample (approximately 20 μL for total dispersion) are enough to ensure the visual detection of ΦME.3 In our first reporting, MEC was applied for analysis of water in ethanol fuel and MEG in RLNG. The obtained data were precise, accurate, and robust regarding deviations in dispersion preparing and shifts in temperature.3 Further studies on the robustness of the method are portrayed herein. Such a parameter was tested as a function of deviations in ionic strength for the analysis of MEG in water. In addition, we describe measurements to new samples of RLNG to assess the MEC reliability by determining MEG. It is notable that the samples tested herein are chemically different as regards to those analyzed in our preceding article because they relate to other stages of MEG regeneration in the pipes of RLNG production by Petrobras. Lastly, new theory considerations on the profile of ΦME with analyte concentrations are shown herein.


thermodynamically stable dispersions (microemulsions, MEs) changing the minimum volume fraction of amphiphile (AP) necessary to form ME (ΦME) taking up a fixed amount of water (W) and oil (O) phases. ΦME expresses the MEC analytical signal. With microemulsification, the generation of nanodroplets in MEs (transparent) ensures the measurement of ΦME by simply monitoring the turbidity change from unstable dispersions (cloudy). Unlike colorimetry wherein the signal changes with intensity of color,4 the measurement of ΦME depends on binary chemical information: cloudy-to-transparent conversion that occurs with microemulsification (inset of Figure 1). This conversion acts like a turning point in titrations. Accordingly, the precise

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EXPERIMENTAL SECTION

Chemicals. Ethanol, NaCl, Na2SO4, CaCl2, and MEG were supplied from Merck (Whitehouse Station, NJ), whereas oleic acid and FeCl3 were purchased from Labsynth (São Paulo, Brazil) and Sigma-Aldrich Chemical Co. (St. Louis, MO), respectively. Deionized water (Milli-Q, Millipore Corp., Bedford, MA) was attained with value of resistivity no less than 18 MΩ cm. Routine of Analysis. MEC procedure depends on the nature of the sample. According to its polarity, the analyte can be added in W, AP, or O phase for microemulsification. Thus, MEC is applicable to polar, nonpolar, and amphiphile samples. The sample tested herein is polar. In this case, W phase solutions are initially obtained changing the analyte standard concentration that is added in polar solvent. Such solutions are used to prepare W−O mixtures under a specific volume ratio. Next, MEs are achieved by transferring pure AP until cloudy-totransparent transition. The detection of ΦME was performed in solution with naked eyes. Dispersions were prepared in bottles of glass or Eppendor tubes with the aid of micropipette by vigorously shaken W−O mixtures upon transferring the amphiphile. The measurements were made with n = 4 for each analyte content. The measurement of ΦME was conducted by gradually adding the amphiphile in a unique bottle containing the W−O mixture. The first attempt in finding ΦME took about 4 min, and it was intended only to get an approximate value of analytical signal. Other attempts, in turn, lasted approximately 1 min. Continuing, the analytical curve is then constructed by relating ΦME with the analyte concentrations. For application, the microemulsifications are based on employment of sample directly as the W phase. Finally, the content of analyte is obtained by direct interpolation using the linear regression line equation fitted by leastsquares method. One scheme showing such a MEC routine is displayed in the Supporting Information.

Figure 1. Analytical curves for MEG in the W phase at different ionic strengths to investigate the MEC robustness using water−ethanol− oleic acid MEs (a) and ΔΦ as a function of ΦM for 30.00%, 60.00%, and 90.00% (v/v) ΦM to different ionic strengths (b). The W phases were prepared by adding MEG in the following saline aqueous media: 10.0 and 500.0 mmol L−1 NaCl and 10.0 mmol L−1 Na2SO4, CaCl2, and FeCl3. Inset: photo of the transition from cloudy (right) to transparency (left) that allows the detection of ΦME. The linear regression line is associated with 10.0 mmol L−1 NaCl. Analytical sensitivities in first/second linear ranges: −0.18/−0.48 (10.0 mmol L−1 NaCl), −0.17/−0.53 (500.0 mmol L−1 NaCl), −0.22/−0.46 (10.0 mmol L−1 Na2SO4), −0.21/−0.48 (10.0 mmol L−1 CaCl2), and −0.20/−0.49 (10.0 mmol L−1 FeCl3). Values of R2 were larger than 0.9900. B


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Microemulsifications were performed at room temperature (23 °C). The dispersions were composed of water (W), oleic acid (O), and ethanol hydrotrope (AP phase), whereas the analyte was ethanol, added in W phase to attain the analytical curves as aforementioned. Analyses reported in our first publication showed that the analytical performance depends on composition of ME.3 The results recorded in region of bicontinuous MEs had the best sensitivity, robustness, and accuracy levels. As a consequence, W−O mixtures presenting 50.00% v/v water to oil (ΦW,O) were employed. Such a faction does not take up the volume of AP. The volume for such W−O mixtures was 600 μL. Lastly, the concentrations of analyte were expressed as volume fractions of MEG to water (ΦM). Robustness tests. Robustness was evaluated by taking deviations not in signal as usual but in contents of analyte. The level of this figure of merit was expressed by the absolute errors determined for ΦM (ΔΦ, % v/v). Such errors were because variations in ionic strength of W phase by adding different salts. Conductivity (κ) was utilized for expressing the ionic strength (I). These parameters relate to each other from equation:13 κ2 =

2e2NA I εoεr kBT

Confidence intervals (n = 4) of the analytical curves changed between 0.08% and 0.37% (v/v) ΦME. Absolute error, in turn, was 2.67 ± 0.86 (n = 18) with all of the values in module. The errors for 90.00% (v/v) were negative. As regards to κ of the W phases used to test the robustness, this parameter is illustrated in Figure 2. The phases prepared in 500.00 mmol L−1 NaCl had

(1)

The parameters of e, NA, εo, εr, kB, and T relate to elementary charge, Avogadro constant, dielectric constants of vacuum and medium, Boltzmann constant, and temperature, respectively. Conductivity was measured by AJ Micronal AJX-522 device, São Paulo, Brazil. To calculate ΔΦ, analytical curves were recorded adding the standards of MEG in solutions of 10.0 and 500.0 mmol L−1 NaCl and 10.0 mmol L−1 Na2SO4, CaCl2, and FeCl3. Such media were the W phase of MEs. The errors were related to 30.00%, 60.00%, and 90.00% v/v ΦM at 23 °C without salt (values of reference). After, the analytical responses associated with these values were used in each curve to calculate ΦM of salt-added dispersions. Application. We tested the accuracy of the method by comparing the contents of MEG analyte obtained by MEC and iodometry in samples of MEG regeneration from processing of natural gas. Iodometry is employed by Petrobras; its protocol is confidential. Student’s t tests at 95% confidence level conducted statistical comparisons among the resulting data of ΦM. The samples were provided by the research center of Petrobras (Centro de Pesquisas e Desenvolvimento Leopoldo Américo Miguez de Mello). These samples were characterized in relation to presence of anions, carboxylic acids, and metals. Latter were determined through inductively coupled plasma atomic emission spectroscopy (PerkinElmer-Sciex model Optima 3300 DV, Waltham, MA). Anions and carboxylic acids were analyzed by ion chromatography (Metrohm 861 Advanced Compact IC model MSM II, Herisau, Switzerland). All of the confidence intervals presented in this communication were calculated for α = 0.05.

Figure 2. Conductivity of W phases applied to test robustness as a function of ΦM. Inset: amplified view of the data relative to 10.0 mmol L−1 salts.

the biggest κ, with values of up to 32.1 mS cm−1. Among the phases in 10.00 mmol L−1 salt, in turn, those obtained in FeCl3 were the more conductive. Their conductivities were of up to 3.0 mS cm−1. According to studies by principal component analyses (PCA, Supporting Information), the conductivities of W phases did not show any systematic effect on analytical sensitivity and level of robustness (ΔΦ). The robustness as regards to modifications in ionic strength was acceptable depending on conductivity of samples and needed the level of accuracy. High-accuracy analyses may require the usage of analytical curves based on saline medium with the intend to eliminate the effect of ionic strength. Signal Profile. MEG and water interfere on the response of MEC. To evaluate the individual effect of these species, values of ΦME were obtained at 23 °C for ethanol−oleic acid dispersions composed of only water or MEG like W phase. Figure 3 shows ΦME as a function of ΦW,O and ΦM,O (volume fraction of MEG to O phase; it does not take up the volume of AP) which are related to W phases composed of only water (ΦW,O) and MEG (ΦM,O). The regions highlighted in colors represent the volume fractions observed in linear ranges of the analytical curves (considering the volumes of water, MEG, and oleic acid as total volume). Herein, there is a rise in ΦM,O and reduction in ΦW,O for successive additions of MEG standards. Taking into account the highlighted regions and the analytical sensitivities shown in Figure 3, we can state that the reduction in ΦME by diminishing water is more prominent when compared to the increase in ΦME by building up MEG in the W phase. Hence, the negative angular coefficients in analytical curves are, in reality, because the effect of water on thermodynamics of dispersions. Results of droplet diameter obtained in our group by dynamic light scattering (not shown) show an inverse relationship of ΦME with the surface activity phenomenon. It

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RESULTS AND DISCUSSION Robustness. The analytical curve at 23 °C for MEG in water (W phase without salt in dispersions composed of oleic acid and ethanol) generated satisfactory analytical figures of merit for 50.00% (v/v) ΦW,O.3 The linear range was surprisingly witnessed throughout values of ΦM. Two linear regions were observed whose analytical sensitivities were −0.20 (5.00− 60.00%) and −0.40 (60.00−90.00% v/v ΦM). The limit of detection was 0.30% v/v. The analytical curves to diverse conductivities and the attained values of ΔΦ are depicted in Figure 1. Herein, we verified the same linear regions of the curve without salt added in the W phase. Their analytical sensitivities presented values on the order of −0.20 ± 0.01 (5.00−60.00%) and −0.47 ± 0.03 (60.00−90.00% v/v ΦM). All of these values are shown in caption of Figure 1. C


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the first range of curve (up to 60.00% v/v ΦM) as observed in this communication. Application. The samples presented color, particulate material, and different species like anions, (Cl−, Br−, and SO42−), metals (Na+, K+, Mg2+, Ca2+, Ba2+, Sr2+, and Fe3+), and carboxylic acids (glycolate, formate, acetate, propionate, and butyrate). The concentrations of such compounds are shown in Table 1, whereas Figure 4 illustrates photos of the samples.

Figure 3. Values of ΦME as a function of Φi that is ascribed to ΦW,O (blue) and ΦM,O (red) for water−ethanol−oleic acid and MEG− ethanol−oleic acid MEs, respectively. Analytical sensibilities were of 134.29/45.95 for ΦW,O and 91.14/41.01 for ΦM,O. R2, in turn, was 0.9845/0.9822 for ΦW,O and 0.9996/0.9989 for ΦM,O. 1 and 2 relates to Φi of first and second (ΦM greater than 60.00% v/v) linear range of analytical curves, respectively.

is ascribed to adsorption of AP at W−O interfaces creating a pressure (surface pressure, π) that diminishes the interfacial tension (γi) as follows:14 γi = γo − π (2)

Figure 4. Photos of the samples of RLNG provided by Petrobras.

The MEG concentrations recorded by MEC to nondiluted samples were very discrepant as regards to data of iodometry (not shown). ΔΦ was higher than 20.00% (v/v). This difference is not owing to high ionic strength of samples because MEC was proven to be somewhat robust for conductivities of up to 32.1 mS cm−1 with ΔΦ lower than 7.00% (v/v). This κ is greater than the average value of the samples of RLNG, 1.4 ± 1.3 mS cm−1 (n = 4). Taking into account the complexity of the samples, one probable reason is chemical interfering. Accordingly, further characterization tests by GC-MS (Shimadzu QP 2010 Plus) were made. These assays revealed the presence of diethylene glycol (DEG) and triethylene glycol (TEG) on concentrations of approximately 2.00% and 10.00%, respectively, in the brute samples. Such compounds are chemically similar to MEG presenting hydroxyl groups in their ends. According to tests with standards (data nor shown), DEG and TEG affected also the thermodynamic stabilization of dispersions. ΔΦ was around 18.00% (v/v), explaining the nonaccurate data obtained by MEC. The deviations in ΦM were positive. It indicates that the glycols interfered on MEC response by raising the surface activity, further decreasing ΦME, and, thus, generating a positive deviation in ΦM.

wherein γo is the interfacial tension before adding AP. Thereby, lowest surface activities generate a poor reduction in γi what requires increasingly less AP (ΦME) for microemulsification processes. Assuming the relationships described above, the decrease in ΦME observed in analytical curves by reducing water is owing to a more effective surface activity, further reducing γi. It favors the thermodynamic stabilization of dispersions by decreasing the Gibbs free energy.15 Our hypothesis on such a raise in surface activity lies in the high monomeric solubility of ethanol to water. Thus, the fraction of ethanol AP adsorbed as oriented monolayers at W−O interfaces is enhanced by reducing the content of water. It raises π, thus more effective decreasing γi. For oil-richer MEs, the increase in surface activity is more pronounced likely due to πO, surface pressure that stems from lateral interactions between the nonpolar groups of AP.14,15 It is important also to highlight that the profile of ΦME in the analytical curves is in agreement with the data of Figure 3. In this case, the decrease in ΦME by diminishing ΦW,O is more intense in second linear range. Furthermore, the enhancement in ΦME with ΦM,O is less prominent in this region. Both effects contribute for a higher analytical sensitivity in second than in

Table 1. Concentrations of Diverse Compounds Present in the Samples of MEG Regeneration (G1−G4) anions (mg L−1) samples G1 G2 G3 G4

−

Cl

Br

−

carboxylic acids (mg L−1)

SO4

2−

metals (mg L−1) +

glycolate

formate

acetate

propionate

butyrate

Na

2 32 1040 1670

10

43

480

55

9

72

8

Microemulsification-Based Method: Analysis of Monoethylene Glycol

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