A Combined Experimental and Computational Study on Selected

Jan 13, 2014 - General Electric Global Research, 1 Research Circle, Niskayuna, New York 12309, United States. ‡. Physics Department, University of ...
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A Combined Experimental and Computational Study on Selected Physical Properties of Aminosilicones Robert J. Perry,*,† Sarah E. Genovese,† Rachel L. Farnum,† Irina Spiry,† Thomas M. Perry,‡ Michael J. O’Brien,† Hong-bin Xie,§,⊥ De-Li Chen,§,⊥ Robert M. Enick,§,⊥ J. Karl Johnson,§,⊥ and Saeed S. Alshahrani§ †

General Electric Global Research, 1 Research Circle, Niskayuna, New York 12309, United States Physics Department, University of Wisconsin, 1150 University Avenue, Madison, Wisconsin 53706, United States § Department of Chemical and Petroleum Engineering, University of Pittsburgh, Benedum Hall, 3700 O’Hara Street, Pittsburgh, Pennsylvania 15261, United States ⊥ National Energy Technology Laboratory, 626 Cochrans Mill Road, Pittsburgh, Pennsylvania 15236, United States ‡

S Supporting Information *

ABSTRACT: A number of physical properties of aminosilicones have been determined experimentally and predicted computationally. It was found that COSMO-RS predicted the densities of the materials under study to within about 4% of the experimentally determined values. Vapor pressure measurements were performed, and all of the aminosilicones of interest were found to be significantly less volatile than the benchmark MEA material. COSMO-RS was reasonably accurate for predicting the vapor pressures for aminosilicones that were thermally stable. The heat capacities of all aminosilicones tested were between 2.0 and 2.3 J/(g·°C); again substantially lower than a benchmark 30% aqueous MEA solution. Surface energies for the aminosilicones were found to be 23.3−28.3 dyne/cm and were accurately predicted using the parachor method.

1. INTRODUCTION Global concern over rising levels of CO2 in the atmosphere and its implication in global warming has spawned numerous efforts to mitigate the effects of greenhouse gas emissions. The U.S. Department of Energy (DOE) has set a target for the capture and sequestration of 90% of the CO2 in flue gas with no more than a 35% increase in the cost of electricity.1 Organic materials known as alkanolamines have been the most heavily studied materials for postcombustion CO2 capture from flue gas.2−7 Of these materials, aqueous monoethanolamine (MEA) is the most widely used solvent, having been used for over half a century for natural gas purification and food-grade CO2 production,8−10 and more recently as a candidate for CO2 capture from flue gas.11−15 However, MEA-based systems have several negative attributes that have hindered their scale-up including a substantial parasitic energy loss due to the energy needed to heat and condense large quantities of water. In addition, MEA is relatively volatile and corrosive16,17 and has poor thermo-oxidative stability.13,18,19 The MEA process has resulted in an estimated increase in the cost of electricity (COE) of about 80% and a decrease in power plant efficiency of 30%.1 Our research has focused on the use of aminosilicones for the postcombustion capture of CO2. While a variety of siliconbased materials have been examined in the past as CO2-capture media,20−29 recent reports have shown that aminosilicones are promising alternatives to the benchmark aqueous organic amine systems.30−32 Aminosilicones possess properties that offset some of the deficiencies found in the organic amines noted above. Thermophysical property data are crucial in designing an integrated process as mass and heat transfer © 2014 American Chemical Society

parameters, among others, are dependent on such factors as viscosity, density, vapor pressure, heat capacity, and surface tension. This work reports some of these physical parameters that were experimentally determined as well as some predicted values.

2. RESULTS 2.1. Materials. A variety of aminosilicones were prepared and are shown in Table 1. GAP-0 and GAP-AEAM were obtained from commercial sources with the remainder being synthesized as previously reported.31 The selection of primary and secondary amines as well as mono- and disubstituted materials and substrates with varying degrees of steric hindrance were chosen to provide a cross-section of sorbents for structure/property analysis. 2.2. Density. Densities were measured by determining the weight of the sample in a 10 mL volumetric flask at 22 °C. Three or more measurements were taken and the mean values and standard deviations are reported in the Supporting Information, Table S1. As expected, the densities were considerably lower for all aminosilicones compared to MEA. The conductor-like screening model for real solvents (COSMO-RS) was used to predict the physical properties of aminosilicones including viscosity, density, and vapor pressure. This method is widely used to predict thermodynamic properties of fluids.33 Density predictions were performed Received: Revised: Accepted: Published: 1334

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Table 1. Structures of Aminosilicones

Information, Table S1). Also note that the actual temperature in the experimental data is 3 °C lower from that used for calculations. 2.3. Viscosity. Viscosity values for aminosilicones were determined using a Brookfield DV-II + Pro Programmable viscometer. This cone-and-plate device was equipped with

using COSMO-RS and were about 2%−4% higher than those experimentally determined. The density trend: M′3T′ > GAPAEAM > GAP-AEAP > M′D′M′ = GAP-1 > GAP-Dytek > GAP-0 > DAB-0 > DAB-Me2 ≈ GAP-nPr predicted by COSMO-RS is in good agreement with that from experiments except M′D′M′ and GAP-0 (Figure 1 and Supporting 1335

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behavior was exhibited by each of the aminosilicones considered in this study. Supporting Information, Table S2 and Figure 3 show the average viscosity of the aminosilicone over the 40−800 s−1

Figure 1. Comparison of calculated and experimentally determined density values.

temperature control and had a small sample holder (∼1 cc), which was ideal for testing small amounts of these novel compounds. Again, COSMO-RS was used to predict the viscosities. As seen in Table 2, the predicted viscosities are

Figure 3. Viscosity as a function of temperature for aminosilicones.

shear rate range as a function of temperature at atmospheric pressure. As expected, viscosity decreases with increasing temperature. Aminosilicone viscosity increases with the molecular weight (e.g., GAP-1 vs GAP-0), branching (e.g., DAB-Me2 vs DAB-0), and number of amines in the compound (e.g., GAP-AEAM vs GAP-0). The latter effect is due to the Hbonding ability of the amine groups.35 In general, lower viscosity values were associated with the smaller, linear aminosilicones with only two amine groups. 2.4. Vapor Pressure. Vapor pressures for nine of the aminosilicones were estimated with COSMO-RS. To validate the model, the vapor pressure of MEA reported in the literature was compared to the COSMO-RS calculation. As seen in Figure 4, the vapor pressure of MEA predicted by COSMO-RS is in reasonable agreement with literature values. Figure 4 also confirmed that the testing method employed was valid as seen by the good agreement between experimental and literature data.36

Table 2. Comparison of Calculated and Experimental Viscosity Values compound

viscosity (cP) (theory) (25 °C)

viscosity (cP) (experiment) (25 °C)

GAP-0 GAP-1 GAP-AEAM GAP-AEAP GAP-nPr DAB-0 DAB-Me2 M′3T′

40.1 120.3 61.1 410.5 74.7 79.6 66.4 1666.5

4.4 4.4 11.0 22.0 5.8 5.5 9.1 18.3

much higher than those from experiments. Also, viscosity trends for aminosilicones from calculation do not agree with those from experiment. This indicates that COSMO-RS is a poor predictor of aminosilicone viscosity. Figure 2 illustrates the effect of shear rate on viscosity at 25, 46, 60, and 80 °C for GAP-nPr. This solvent is essentially shear rate-independent over this temperature and shear rate range, which is not surprising given the relatively low molecular weight of these silicone materials.34 Similar Newtonian

Figure 2. Viscosity of GAP-nPr as a function of temperature and shear rate.

Figure 4. Comparison of experimental and calculated vapor pressure curves for aminosilicones. 1336

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As expected, vapor pressures of the aminosilicones were low; pressure measurements were conducted in a system fitted with a high temperature pressure transducer, with a range of 0.0026−1.03 bar. Temperature and pressure were continuously monitored throughout the experiment and the sample holder and valve were designed to be submersible in the oil bath, to maintain a consistent system temperature. While all the aminosilicones synthesized were of sufficient purity for most of the property measurements, the vapor pressure experiments were uniquely influenced by very low levels of volatile impurities. To remove the impurities in the aminosilicones, these materials were subjected to a pretreatment that initially consisted of bubbling nitrogen through the sample for 2−3 h. The material was then loaded into the apparatus, positioned with only the sample holder in the oil bath, and heated under vacuum (2 Torr) for 1 h at 180 °C. Samples that were found to be more thermally sensitive (GAPnPr and DAB-Me2) were only heated to 120 °C. Several of the aminosilicones (GAP-Dytek, GAP-AEAM, GAP-AEAP and M′3T′) still released volatile species at this lower temperature and reliable vapor pressure measurements could not be obtained. This is consistent with results from thermal stability studies that are currently in progress and will be reported at a later date. Each temperature ramp ranged from room temperature (approximately 25 °C) to 180 °C. A comparison of the calculated vapor pressure curves with experimental data is given in Figure 4 for the aminosilicones GAP-0, M′D′M′, and DAB-0. The experimental data are shown as filled symbols while the calculated data are plotted using open symbols of the same type. The lines are to guide the eye. As can be seen from Figure 4, there is excellent agreement between experiments and calculations for MEA and DAB-0. We note, however, that the experimental data for both M′D′M′ and GAP-0 exhibit significant change in curvature at about 1/T = 0.0027 (close to 100 °C). This change in slope would signify an abrupt change in the heat of vaporization, which is physically unrealistic. We therefore conclude that the change in slope may be due to residual impurities or perhaps to degradation of those compounds. We note that the agreement between calculated and experimental vapor pressures for M′D′M′ and GAP-0 are also much worse than for MEA or DAB-0. The experimental data from which Figure 4 was constructed are reported in Supporting Information, Table S3, along with additional experimental data for which we have not performed COSMO-RS calculations. 2.5. Surface Energy. The pendant drop method was used to determine surface energy values for selected aminosilicones. This method involved the determination of the profile of the drop and then inferred the interfacial tension by either theoretical derivation37 or software calculation. Surface tension was determined by fitting the shape of the drop to the Young− Laplace equation, which relates interfacial tension to drop shape.37 A drop of suspended liquid is in mechanical equilibrium, and its shape is determined by balance of the gravitational forces and surface tension. In order for the Young−Laplace equation to be satisfied, the drop must be distorted, because surface tension cannot be evaluated for a spherical drop. Therefore, the height of drop must be sufficient for the pressure difference between the top and bottom to distort the drop.38 The interfacial tension γ can be calculated by eq 1:

γ=

gDe 2Δρ H

(1) 2

where g = acceleration due to gravity, m/s , De = the equatorial diameter of the drop; Δρ = difference in densities of vapor and liquid; H = correction factor related to the shape factor of the pendant drop. S is defined as

S=

Ds De

(2)

where Ds is the drop diameter measured horizontally at a distance De away from the apex of the drop contour, as shown in Figure 5.

Figure 5. Pendant drop parameters.

Surface tension was measured for known compounds to determine the accuracy of the measurement and equipment. Four different solvents with different ranges of the surface tension values were used: isopropanol (IPA), deionized (DI) water, triethylene glycol (TEG), and ethylene glycol. The aminosilicones were tested with 20 measurements taken. The results are presented in Supporting Information, Table S4 and Figure 6. It can be seen that the values of surface tension for all aminosilicones are in the same range. Theoretical methods for surface tension prediction exist, and among them is the parachor method, which is based on group contributions to the surface tension. For pure liquids an approach was suggested by Macleod39 and modified by Sugden,40 which relates surface tension, σ, to the liquid and vapor molar densities and a temperature-independent parameter called the parachor P: 4 ⎛ mN ⎞ ⎡ ⎛ ρL − ρV ⎞⎤ ⎟ = ⎢P⎜ σ⎜ ⎥ ⎟ ⎝ m ⎠ ⎣ ⎝ 103kmol/m 3 ⎠⎦

(3)

where ρL, ρV are the saturated molar liquid and vapor densities, respectively. At low temperatures, where ρL ≫ ρV, the vapor density can be neglected, but at higher temperatures the density of both phases must be calculated.41 Group contribution to the parachor value can be found in various references, and P for the compound can be calculated from the following expression: P=

∑ Δpn i i i

(4)

Predictions based on this method are presented in Supporting Information, Table S4. The difference in predicted values from the experimentally determined ones can be explained by the absence of sufficient examples of aminosilicones in the database that would allow for corrections to the parachor values and account for molecular interactions specific to these types of molecules. However, the agreement with experimentally determined values is quite good, with the exception of DAB-0. 1337

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Figure 6. Literature, experimental, and estimated values of surface tension for the reference compounds and aminosilicones.

Table 3. Heat Capacities of Aminosilicone Solvents Cp (J/g °C) (uncertainties listed are 95% confidence intervals) aminosilicone

T = 40 °C

GAP-0 GAP-1 GAP-AEAM GAP-AEAP GAP-nPr M′3T′ DAB-0 DAB-Me DAB-Me2

2.3 2.0 2.2 2.2 2.1 2.1 2.2 2.2 2.1

± ± ± ± ± ± ± ± ±

0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

T = 60 °C 2.2 2.0 2.1 2.2 2.0 2.1 2.2 2.1 2.0

± ± ± ± ± ± ± ± ±

0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

T = 80 °C 2.2 1.9 2.1 2.2 2.0 2.2 2.2 2.1 2.0

± ± ± ± ± ± ± ± ±

0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2

2.6. Heat Capacity. The heat capacity of the solvent has a profound influence on the energy needed to elevate the temperature of a CO2-rich solvent during a thermal desorption step. The traditional aqueous solution of MEA has a heat capacity of nearly 4 J/g °C.42 This is in stark contrast to all the aminosilicones examined which ranged between 2.0 and 2.3 J/g °C at 40 °C (Table 3). This factor of 2 translates into significant energy savings. While the heat capacities for a few of the materials shown in Table 3 appear to decrease with increasing temperature, the change is within the variability of the measurement and therefore is not statistically significant.

T = 100 °C 2.2 1.9 2.1 2.2 2.0 2.2 2.2 2.1 1.9

± ± ± ± ± ± ± ± ±

0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2

T = 120 °C 2.2 1.9 2.1 2.3 1.9 2.2 2.2 2.0 1.9

± ± ± ± ± ± ± ± ±

0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2

T = 140 °C 2.2 1.8 2.1 2.2 1.9 2.2 2.3 1.8 1.8

± ± ± ± ± ± ± ± ±

0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3

determined values. Viscosity predictions using the same software program were not accurate. Determination of vapor pressures were performed and all of the aminosilicones of interest were found to be significantly less volatile than the benchmark MEA material. COSMO-RS was reasonably accurate for predicting the vapor pressures for aminosilicones that were thermally stable. The heat capacities of all aminosilicones tested were between 2.0 and 2.3 J/(g·°C); again substantially lower than 30% aqueous MEA at 3.7 J/ (g·°C).42

4.0. COMPUTATIONAL AND EXPERIMENTAL DETAILS Computational Details for COSMO-RS. The conductorlike screening model for real solvents (COSMO-RS) developed by Klamt and colleagues43,44 was used to predict the density, vapor pressure, and viscosity of various amino silicones. The standard procedure for COSMO-RS calculations used in this

3.0. SUMMARY/CONCLUSIONS A number of physical properties of aminosilicones have been determined experimentally and predicted computationally. It was found that COSMO-RS predicted the densities of the materials under study to within about 4% of the experimentally 1338

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paper is the same as that previously published by our group,45,46 which consisted of two steps. In the first step, density functional theory (DFT) calculations using the B88-PW8647,48 functional, together with a triple-ζ valence polarized basis set (TZVP) and the RI approximation were carried out for all molecules. The continuum solvation model COSMO was used in these calculations to simulate a virtual conductor environment for the molecules. Random configurations of the solute molecules were optimized and converged to local minima in a conductor. All DFT/COSMO calculations were performed using the quantum chemical program TURBOMOLE.49 In the second step, the σ-profile from the output of the first step was used to quantify the interaction energy of pairwise interacting surface segments with regards to the most important molecular interaction modes. All COSMO-RS calculations were carried out as implemented in the COSMOtherm program.50 The BP_TZVP_C21_010750 parametrization was adopted in this work. Density. A preweighed, 5 or 10 mL volumetric flask was filled with the appropriate aminosilicone and weighed. The temperature was 22 ± 1 °C, and a minimum of three measurements were taken. The average value with a standard deviation is reported. Viscosity. Viscosity values for aminosilicones were determined using a Brookfield DV-II + Pro Programmable viscometer. This cone-and-plate device was equipped with temperature control and had a small sample holder (∼1 mL). Temperatures were varied between 25 and 80 °C and the shear rate between 40 and 800 s−1 Vapor Pressure. Experimental vapor pressure measurements were conducted in a 25 mL, stainless steel pressure vessel equipped with a valve and a high temperature, 0−15 psia pressure transducer. The bomb was charged with approximately 5−10 g of aminosilicone, sealed, and placed in an oil bath. The temperature and pressure were continuously monitored throughout the experiment. The sample holder and valve were designed to be submersible in the oil bath, to maintain a consistent system temperature. For most of the materials, each test consisted of at least two temperature ramps. In some cases where there were concerns about the thermal stability of the material at the highest temperatures, only one temperature ramp was completed. Prior to completing the temperature ramps, nitrogen was bubbled through the material for 2−3 h. The material was then loaded into the apparatus, positioned with only the sample holder in the oil bath and placed under vacuum. For thermally sensitive materials, vacuum was applied for 45 min to 2 h (depending on the material) while the sample was held at 120 °C. For more robust aminosilicones, the vacuum was applied for 1 h while the sample was held at 180 °C. These procedures were employed to remove most of the volatile contaminants from the samples. Surface Energy. Surface tension was measured by the pendant drop method using VCA Optima XE equipment. The 100 μL Hamilton microsyringe and blunt straight 28 gauge Hamilton needles were used for the deposition of all fluids. During each measurement the microsyringe was carefully filled with solvent to avoid air bubble formation. The syringe was placed vertically into the VCA Optima holder so that the tip of the needle was visible on the monitor. The solvent was then manually dispensed from the syringe to obtain the maximum size droplet. The droplet image was analyzed by VCA Optima software after inputting the density of the liquid. Baseline

solvents isopropyl alcohol, deionized water, triethylene glycol, and ethylene glycol were used as calibration standards. Heat Capacity. Heat capacities were measured using a Perkin-Elmer DSC7 differential scanning calorimeter under a 10 mL/min purge of house nitrogen following the method described in ASTM-E1269.51 The samples were weighed into T zero hermetic aluminum sample pans immediately prior to analysis. For samples observed to consistently evaporate, the procedure was altered to end at a temperature below where the evaporation was observed to begin. Runs in which sample weight loss was observed at the completion of the test were not analyzed in the data set. Overall measurement standard deviations were determined at each temperature setting with measurement error increasing with increasing temperature

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ASSOCIATED CONTENT

S Supporting Information *

Additional tables of data for calculated and experimental density values, viscosity as a function of temperature, vapor pressure, and surface tension. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Notes

The information, data, or work presented herein was funded in part by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The information, data, or work presented herein was funded in part by the Advanced Research Projects Agency−Energy (ARPA−E), U.S. Department of Energy, under Award Number DE-AR0000084 and by the Department of Energy, National Energy Technology Laboratory under Award Number DENT0005310.

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REFERENCES

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