Letter pubs.acs.org/Langmuir
Multidimensional Quantitative Imaging of Gas Adsorption in Nanoporous Solids Ronny Pini* Petroleum Engineering Department, Colorado School of Mines, Golden, Colorado 80401, United States S Supporting Information *
ABSTRACT: X-ray computed tomography is applied to image gas adsorption in nanoporous solids. The equations are developed to calculate rigorous measures of adsorption, such as the excess adsorbed amount, by applying a dual-scanning technique. This approach is validated by considering the CO2/13X zeolite system in a fixed-bed adsorber, and multidimensional patterns are obtained of key characteristic properties, such as bed porosity, excess adsorption, and density of the adsorbed phase. The quantification of the spatial variability of the adsorbed amount within the system represents a major novelty with regards to conventional techniques. The ability to quantify adsorption with such a level of observational detail discloses unparalleled opportunities to interrogate and revisit adsorption processes in porous media.
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coal samples;9,10 in the latter case, however, the adsorptive gas was treated as a unique phase, and no distinction was made between free and adsorbed gas. Besides the controversy with other studies that propose krypton as a non-adsorbing fluid to probe the porosity of shale,11 it can also be argued that the use of a surrogate gas in these studies is questionable, as the latter might not properly represent the properties of the in situ adsorbing fluid. In fact, the density of the adsorbed phase is controlled among others by confinement effects that are in turn associated with the fluid’s specific interactions within the molecular-size pores of the material.12 In this Letter, a novel approach is presented to image and quantify adsorption in porous materials using an X-ray CT medical scanner. A dual-scan technique is used to visualize adsorption in a fixed-bed adsorber; hereby, the formation of a denser phase in the pores of the material when exposed to an adsorbing fluid enables a clear contrast against a background image obtained in the presence of an inert gas (Helium). The properties of the adsorbed phase are quantified through classical and thermodynamically-sound measures of adsorption, such as the excess adsorbed mass, thus allowing for direct comparison with published data. The technique is validated for the 13X zeolite/CO2 system by comparison with adsorption data obtained with conventional measurement techniques and can be readily extended to other adsorbent/adsorbate systems. It is shown that when combined with imaging techniques, fixedbed adsorption experiments become very powerful, as they allow one to simultaneously obtain information about spatial
INTRODUCTION Gas adsorption is one of the key physical processes that underlie the numerous and widespread applications of nanoporous materials. To name a few, highly uniform zeolites continue to be applied for processes within their traditional areas of use, namely ion exchange, separation, and catalysis;1 the recovery of natural gas from sedimentary microporous rocks (e.g., coal and shale) is regarded by petroleum engineers as one of the answers to securing our energy supply in the foreseeable future.2 Whether it is a synthetic material or a heterogeneous rock, the ability to link the structural properties of the solid framework (i.e. porosity, surface area and pore-size distribution) to the physics of the governing adsorption process is key for enabling further developments and, accordingly, new industrial applications of adsorbent materials.1,3 While gas adsorption techniques are still the preferred choice to achieve this objective,4 noninvasive imaging methods are increasingly being applied to complement these measurements. X-ray computed tomography (CT) belongs to this last category; hereby, the acquired images can be used to explore multidimensional patterns of various properties within samples up to several hundred cubic centimeters in size (depending on the resolution). However, as highlighted by recent reviews on the subject,5,6 most of the published literature reports on the sample’s structural characterization, rather than on the fluid’s phase behavior within the pores of the material, and very few studies have exploited X-rays to characterize adsorption processes. Some authors have used X-ray radiographs as a qualitative visual support to explain adsorption data measured by conventional gravimetric7 and breakthrough8 experiments. Others have attempted a quantitative analysis by using a socalled radio-opaque gas, such as krypton or xenon, to mimic natural gas so as to estimate the storage capacity of shale and © 2014 American Chemical Society
Received: July 5, 2014 Revised: September 9, 2014 Published: September 9, 2014 10984
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ρ ̅ = ϕbρf + (1 − ϕb)[(1 − ϕp)ρs + ϕpρf ] + m vex
heterogeneities in the system and, accordingly, interrogate their effect on gas flow and storage in complex adsorbent materials.
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(2)
where ϕb and ϕp represent the inter- and intrapellet porosities, i.e., ϕb = Vb/Vvox and ϕp = Vp/(Vvox − Vb). Note that mex v refers to the excess adsorbed amount per voxel volume. Equation 2 can be readily translated into an operating equation for the Xray scanner by replacing density with CT numbers (measured in Hounsfield units):
MATERIALS AND METHODOLOGY
13X zeolite pellets (Z10-03, Lot. 6009369.05, particle size 1.6-2.5 mm) were kindly provided by Zeochem AG (Uetikon am See, Switzerland). The material’s porosity is ϕp = 58.6% (±0.6%) and the envelop density takes a value ρenv = 1.062 g/mL (±0.001 g/mL); its crystal lattice structure contains micropores of only one size (1.2 nm diameter), while the remaining intercrystalline pore volume (∼52 % vol) includes meso- and macropores in a rather broad range (40−400 nm).13 Prior to the experiment, the sample has been activated at a temperature of 200 °C for a few hours and then transferred to the experimental setup. A packed-bed of zeolite pellets (measured bed porosity, ϕb ≈ 37%, length/diameter is 4.5/3 cm) is obtained by pouring the pellets into a teflon tube that is heat-shrinked to the end-caps of an aluminum cylindrical sample-holder. A displacement pump (Teledyne Isco 260D) maintains a slight annular water pressure around the teflon tube (1.4 MPa), thus ensuring that the arrangement is tight. The sample-holder is placed in an X-ray General Electric Hi-Speed CT/i medical scanner, and vacuum is applied for about 1.5 h at the experimental temperature of 25 °C. The experiment starts by purging the bed with Helium (99.999% purity, Praxair, Inc., USA) at a pressure of 1 atm for 30 min, followed by the acquisition of two complete scans. Gas flow is then switched to CO2 (99.995% purity, Praxair, Inc., USA) and the procedure is repeated. The scanner uses a tube current of 200 mA and the energy level of radiation is 120 keV. The 3D images are reconstructed on a grid with voxel size (0.4 × 0.4 × 1) mm3. At this resolution, a whole scan is taken in a few minutes, and voxel CT numbers are affected by an uncertainty of ±15 Hounsfield Units (HU). The latter is reduced to ±3.7 HU for images that are obtained by taking the average among two repeated scans and by applying a 4 × 4 × 2 coarsening scheme (see Supporting Information).
CT = ϕbCTf + (1 − ϕb)[(1 − ϕp)CTs + ϕpCTf ] + H ex (3)
where CTf and CTs are the CT number of the fluid and the solid, respectively. Note that while the former is a constant (at given pressure/temperature conditions), the latter can vary from voxel to voxel, as it would be the case for heterogeneous materials. Equation 3 requires that the CT number is linearly proportional to the bulk density, i.e., CT = aρ + b, and accordingly, Hex = mex v /a. This condition is indeed met due the following considerations. First, the X-ray scanner measures μ, and the CT number used in eq 3 is nothing else than a linear attenuation coefficient normalized with the coefficient of water μw, i.e., CT = k(μ − μw)/μw, with k being a constant that is obtained from the calibration of the scanner with air (in this study, k = 960 HU). Second, while for materials with an effective atomic number near water (i.e., the second calibration fluid) a linear relationship between μ (or, accordingly, the CT number) and density is indeed commonly observed, extrapolation of this behavior to materials with much larger densities (solids) has to be done with care.14,16 In the latter case, the problem can be solved (and the required assumption of linear proportionality warranted), as long as the relationship between CT and ρ is known over the entire density range (see the Supporting Information). Adsorption can be quantified by applying eq 3 to scans that have been taken upon flooding the bed with the nonadsorbing ex Helium (f = He, mex v = 0) and with CO2 (f = A, mv ≠ 0), respectively. Subtraction of the two equations allows eliminating the solid component, thus isolating the effects of adsorption:
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THEORY In the derivation that follows, it is assumed that (i) the adsorber is static, i.e., the properties of its porous framework are not varying over time, and (ii) the system is at steady-state (adsorption equilibrium and isothermal conditions are attained). Absorption tomography quantifies the attenuation of X-ray beams by means of linear attenuation coefficients, μ. The technique exploits that, for a given energy level, the latter are proportional to the bulk density of the imaged material.14 Due to its relatively low resolution (400 μm and above), a medical scanner cannot resolve the individual constituents of a solid adsorbent, such as its pores and grains, and only average properties can be observed. Accordingly, the mass density, ρ̅, of an imaged voxel with volume Vvox includes contributions from each pure component material present in the system, namely the fluid (ρf), the solid (ρs), and the adsorbed phase (ρa):
H ex = (CTA − CTHe) − (CTA − CTHe)[ϕb + (1 − ϕb)ϕp] (4)
It is worth emphasizing that the application of this dual-scan technique to eliminate the solid (and high-density) component (CTs) from eq 4 has two benefits: it allows working with heterogeneous materials where CTs varies spatially within the sample and it supports the assumption of linearity between density and CT number. In this study, experiments have been performed at atmospheric conditions and the second term in eq 4 can safely be neglected (ρHe ≈ ρCO2 and thus CTA ≈ CTHe). The experimental results are reported in terms of molar excess adsorption per unit mass of sample
Vvoxρ ̅ = (Vvox − Vb − Vp)ρs + (Vb + Vp − V a)ρf + V aρa (1)
where Vb and Vp are the inter- and intrapellet pore volumes, respectively, and Va is the volume of the adsorbed phase. The truly measurable quantity in an adsorption experiment is the socalled surface excess,15 mex = ma − ρfVa, which refers to the difference between the actual amount adsorbed, ma, and the amount of homogeneous bulk fluid with density ρf that would be present in the (unknown) volume occupied by the adsorbed phase (Va). Combining this definition with eq 1 leads to the following expression for the average density of any given voxel in the system:
nex =
a(CTA − CTHe) (1 − φb)ρenv M m
(5)
where Mm = 44.01 g/mol is the molar mass of CO2. Note that when working at higher pressure, the assumption CTA = CTHe is not valid, and the second term on the right-hand side of eq 4 cannot be neglected; in this case, the CT number of the adsorbate at the given density is readily obtained by linear interpolation between the two calibration fluids (air and water). Equation 5 is applied at the voxel scale, whereas slice- or bed10985
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Figure 1. Experimental observations from the adsorption/imaging experiments. Left: 1-D slice-averaged profiles of the CT number along the length of the zeolite bed corresponding to the Helium (CT He) and CO2 (CTA) floods (two series for each fluid). The black symbols represent the subtraction of the two sets of scans. Right: The corresponding 2-D and 3-D maps that have been reconstructed by averaging among two repeated series on a (0.4 × 0.4 × 1) mm3 grid (uncertainty at the voxel level, σCT ≈ 11 HU). The 2-D maps represent vertical cross sections taken 20 mm from the inlet of the bed.
adsorption properties. The right portion of the figure shows 3D reconstructions of the packed-bed during both helium (bottom) and CO2 (top) floods, together with 2-D maps of a slice taken halfway through the bed. These images have a resolution of (0.4 × 0.4 × 1) mm3 and have been obtained by averaging among two repeated scans. Again, the difference between the two sets of experiments is clearly visible through the colormap, with CO2 showing a “heavier” bed as compared to helium. Additionally, these maps highlight significant finescale variations in the CT number that can again be associated with variations in the bed porosity, but also in adsorption at the voxel scale. 1-D profiles are shown in Figure 2 that represent three physical measures that can be quantified from the experiment, namely, bed porosity, excess adsorption, and density of the adsorbed phase along the length of the zeolite bed. In the figure, the color-shaded regions represent the uncertainty in the measured property as given by one standard deviation from the
averaged properties are calculated using slice- or bed-averaged values for CT and ϕb. In this study, the bed porosity ϕb is obtained from eq 3 applied to the experiment with helium, CTs and CTHe being known from a scanner calibration (see Supporting Information). System calibration has been performed with air and water, whose CT numbers are measured by placing a phantom in the gantry aperture of the scanner (−960 and 0 HU, respectively). Accordingly, the slope of the calibration line, i.e., the parameter a in eq 5, takes a value of 1.037 × 10−3 HU × cm3/g. Uncertainties in the calculated properties have been estimated from classical rules of error propagation; while slice- and bed-averaged properties are solely affected by uncertainties in the structural parameters of the material (σϕb = 1.5% abs and σnex = 0.08 mol/kg), the uncertainty in the CT number at the voxel scale (∼5 mm3) limits the precision of the adsorption measurement to about ±0.2 mol/kg (see Supporting Information).
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RESULTS Figure 1 summarizes the multidimensional raw data-set obtained from the combined adsorption/imaging experiments. Results are given in terms of CT numbers for both helium and CO2 floods; on the left-hand side of the figure, 1-D profiles are shown that have been obtained by averaging the voxel CT numbers over the entire cross-section of each slice along the length of the bed (one slice is 1 mm thick). The scans have been taken 30 min after start of injection of the given fluid and each time two series have been acquired (empty and filled gray symbols). The excellent agreement between repeated scans suggests that steady-state conditions were indeed attained. Moreover, although for a given fluid the slice-averaged CT number varies along the length of the bed, the two sets of experiments closely follow an almost identical pattern with CO2 showing significantly larger values than helium (the coreaveraged CT number is −133 HU and −41 HU for He and CO2, respectively). Variations along the length of the bed can be attributed to variations in the bed porosity, ϕb, while the shift of the data is due to the presence of a denser phase in the pores of the material (adsorption). In fact, the former effect disappears when the two sets of scans are subtracted, as given by the black filled circles in the figure that represent Hex in eq 4. The very flat profile that is obtained from such operation reflects the homogeneity of this material in terms of its
Figure 2. 1-D slice-averaged profiles of bed porosity (ϕb), excess adsorbed amount (nex) and adsorbed density (ρa) along the length of the zeolite bed. Each slice is 1 mm apart, and the color-shaded regions represent the uncertainty in the measured property (± one standard deviation). 10986
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Figure 3. Quantification of adsorption heterogeneity at the voxel scale. Left: 1D slice-averaged profiles of the adsorbed amount (nex) along the length of the zeolite bed. The corresponding 2D maps are shown for four representative slices and are reconstructed on a (1.6 × 1.6 × 2) mm3 grid. Right: Histogram representing the distribution of the adsorbed amount at the voxel level within the whole zeolite bed. The width of the bins w is chosen so that w = 2σnex (voxel size ≈ 5 mm3 and σnex ≈ 0.2 mol/kg). Average CO2 adsorption values reported in the literature for various 13X zeolite samples are shown by the black dashed lines.
their relative affinity toward the porous solid. Traditional applications of this technology are chromatography and ionexchange,20 but gas separation by adsorption is also the basis for gas injection processes in the subsurface to enhance methane recovery, as is the case for coal beds22 and shale reservoirs.23 The ability to predict the distribution of each phase (free and adsorbed gas) within the porous structure of the material is key to optimize the engineering design of a given operation, in particular when heterogeneous systems are considered. In this context, multidimensional tomography represents an ideal tool to complement conventional adsorption techniques, as it additionally enables the real-time noninvasive imaging of various properties within the system. Hereby, the main advantages of using a medical X-ray scanner are that it can accommodate typical laboratory size equipment, such as the adsorber column used in this study, while offering short acquisition times (a couple of seconds for a 1 mm thick slice). The present study integrates a traditional fixed-bed adsorption experiment with the simultaneous imaging of solid and fluid phase properties at a resolution of a few cubic millimeters, i.e., the size of a pellet. Adsorption is quantified similarly to conventional measurement techniques, where an experiment with an inert fluid (helium) is combined with the experiment with the adsorbing fluid (CO2 in this study), but with the added benefits of X-ray tomography. In fact, the ability to quantify the spatial variability of both porosity and adsorption within the fixed-bed column represents the peculiarity of the proposed work and a major novelty with regards to previous studies. In the former case, an experiment with the inert Helium was sufficient to compute voxelporosities, as the homogeneity of the adsorbent material in terms of its grain density supports the assumption of a constant ϕp and a constant CT number of the solid phase (CTs ≈ 2240 HU). While the former is a fairly common situation observed in microporous materials at the spatial resolutions considered here, the latter has to be relaxed when dealing with heterogeneous adsorbents by applying a dual-scan technique; hereby, images taken at the exact same locations are combined that have been obtained with the same fluid at two distinct energy levels or with two distinct fluids at the same energy
mean value. These three measures reflect a gradual increase in the complexity of the analysis: bed porosity is obtained by considering solely the experiment with the inert helium; excess adsorption is estimated by combining helium and CO2 experiments; the prediction of the adsorbed phase density further requires one to assume that adsorption takes place only in the micropores of the material (Vm = 0.26 cm3/g, from previous measurements13). Note that the size of the 13X zeolite micropores (diameter 1.2 nm, i.e. about 3 times the kinetic diameter of the CO2 molecule) supports the assumption that the adsorbed phase fills the entire micropore volume.13,17 In each case, minimal variations along the bed are observed, this being an expected results for a regular and homogeneous system, such as a packed bed of zeolite pellets. The obtained results are in good agreement with independent observations from the literature, thus confirming the reliability of the proposed approach. In fact, the calculated core-average bed porosity (37.5%) compares well with predictions based on a random packing of monodispersed spheres (36−40%),18 and the estimated average excess adsorbed amount (3.3 mol/kg) is in close agreement with a value of 3.6 mol/kg that is reported in the literature on the same adsorbent material by using a volumetric technique (Zeochem, Z10-02).19 By considering a cage volume of 958 Å3 and a molecular volume of CO2 of 70.9 Å3 (estimated from the van der Waals covolume),20 the average density of the adsorbed phase estimated from the adsorption data (12.4 mol/L) suggests that about seven molecules are packed in each cages of the zeolite crystals; the fact that this value is below the expected saturation (13-14 molecules) confirms that adsorption in this material is controlled by a gradual filling of the micropores.21
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DISCUSSION Understanding the interplay between phase equilibrium and fluid flow in porous media is of central importance to many applications dealing with both engineered and natural materials. For instance, in adsorption-based processes, the equilibrium between fluid- and adsorbed-phase is expressed by an adsorption isotherm, which in turn determines the ability to separate the species present in the flowing fluid phase through 10987
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level.16 To this aim, a radio-opaque gas is the preferred choice to probe a microporous material, as long as its adsorption is negligible at the applied experimental conditions.11 The spatial variability of the adsorbed amount at the voxel scale (5 mm3) is presented in Figure 3, where 1-D sliceaveraged profiles of the adsorbed amount are plotted along the length of the bed, together with selected 2-D cross-sectional maps that are reconstructed on a (1.6 × 1.6 × 2) mm3 grid. It can be noticed that the adsorbed amount varies significantly, with deviations from the mean (3.3 mol/kg) up to ±25% at the conditions of the experiment (see the color-scale in the inset of the figure). The latter are significantly larger than the corresponding measurement uncertainty (±0.3 mol/kg or ±6%) and may reflect an insufficient and/or inhomogeneous reactivation of the adsorbent material. An analysis of previous data from the literature for CO2 adsorption on 13X zeolite at 1 atm and 25 °C evidence a consistent increase of the amount adsorbed with the temperature applied to regenerate the material, namely, 3.6 mol/kg (25 °C),19 3.9 mol/kg (195 °C),24 4.1−4.6 mol/kg (320 °C)25,26 and 4.6 mol/kg (350 °C).27 These data are plotted as horizontal dashed lines on the right panel of Figure 3, where an histogram representation is also shown of the voxel-adsorption obtained in this study. As expected, the mean of the distribution agrees with expectations from a regeneration driven by vacuum only (and on a sample from the same supplier),19 while the largest values coincide with literature data obtained upon application of the highest activation temperature.25,26 While it was not the purpose of the present study to reproduce adsorption data for the extensively characterized CO2/13X zeolite system, the close agreement with the first study validates the use of X-rays as an alternative method to quantify adsorption in porous solids. In fact, the main outcome of this work is associated with the characterization and quantification of heterogeneity in adsorption systems and the approach presented here represents a practical and efficient method to resolve the spatial variability of the adsorption isotherm. The latter is in turn a point of departure for the study of flows in complex porous media in the presence of an adsorbed phase; future applications of this method can be envisaged to monitor the deactivation of the adsorbent in a cyclic adsorption/desorption unit, to identify sweet spots in heterogeneous adsorbents, such as microporous rocks, and to provide the data-set for developing up-scaling methods of adsorption isotherms.
adsorption capacity and a protocol is presented that allows designing the experiment, so as to achieve the required accuracy. With the addition of a temperature measurement along the adsorbent bed, the technique has the potential to be extended to the study of adsorption under dynamic conditions.
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ASSOCIATED CONTENT
S Supporting Information *
Additional details on the experimental procedure and uncertainty analysis of measured data. 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 authors declare no competing financial interest.
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ACKNOWLEDGMENTS The author thanks Prof. Sally Benson, Department of Energy Resources Engineering, Stanford University, for making available the medical CT scanner, and Dr. Nicola Forrer (Zeochem AG) for kindly providing a batch of 13X zeolite pellets.
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REFERENCES
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CONCLUSION The use of X-ray CT scanning to measure adsorption in nanoporous materials is demonstrated by considering the CO2/ 13X zeolite system. Multidimensional patterns of key properties have been quantified at a resolution of few mm3, thus including porosity, adsorbed amounts, and density of the adsorbed phase. The 3-D reconstruction of the packed-bed evidence significant variability in the adsorption properties that reflects a different degree of reactivation of the material. This ability to image and quantify spatial variations of the adsorption isotherm is key to study coupled adsorption and flow processes in complex porous solids, thus disclosing opportunities for research in a wider spectrum of situations. The presented experimental protocol and equations are not restricted to regular porous solids, such as zeolites, but can be applied to any heterogeneous material with a well-distributed microporosity. The inherent density difference between adsorbed and bulk fluid phase suggests that systems can be studied that are characterized by relatively low 10988
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(14) Vinegar, H. J.; Wellington, S. L. Tomographic imaging of threephase flow experiments. Rev. Sci. Instrum. 1987, 58, 96−107. (15) Sircar, S. Excess properties and thermodynamics of multicomponent gas adsorption. J. Chem. Soc., Faraday Trans. 1 1985, 81, 1527−1540. (16) Akin, S.; Kovscek, A. R. Computed tomography in petroleum engineering research. In Applications of X-ray Computed Tomography in the Geosciences; Mees, F., Swennen, R., Van Geet, M., Jacobs, P., Eds.; Geological Society: London, 2003; Vol. 215, pp 23−38. (17) Do, D. D.; Do, H. D. Adsorption of supercritical fluids in nonporous and porous carbons: Analysis of adsorbed phase volume and density. Carbon 2003, 41, 1777−1791. (18) Dullien, F. Porous Media: Fluid Transport and Pore Structure; Academic Press, Inc.: San Diego, CA, 1992. (19) Siriwardane, R. V.; Shen, M.-S.; Fisher, E. P.; Poston, J. A. Adsorption of CO2 on molecular sieves and activated carbon. Energy Fuels 2001, 15, 279−284. (20) Ruthven, D. M. Principles of Adsorption and Adsorption Processes; Wiley: New York, 1984. (21) Kaneko, K.; Murata, K. An analytical method of micropore filling of a supercritical gas. Adsorption 1997, 3, 197−208. (22) Mazzotti, M.; Pini, R.; Storti, G. Enhanced coalbed methane recovery. J. Supercrit. Fluid 2009, 47, 619−627. (23) Nuttall, B. C.; Drahovzal, C. F.; Eble, C. F.; Bustin, R. M. In Carbon Dioxide Sequestration in Geological MediaState of the Science; Grobe, M., Pashin, J. C., Dodge, R. L., Eds.; AAPG Studies in Geology; American Association of Petroleum Geologists: Tulsa, OK, 2009; Vol. 59; pp 173−190. (24) Hyun, S. H.; Danner, R. P. Equilibrium adsorption of ethane, ethylene, isobutane, carbon dioxide, and their binary mixtures on 13X molecular sieves. J. Chem. Eng. Data 1982, 27, 196−200. (25) Cavenati, S.; Grande, C. A.; Rodrigues, A. E. Adsorption equilibrium of methane, carbon dioxide, and nitrogen on zeolite 13X at high pressures. J. Chem. Eng. Data 2004, 49, 1095−1101. (26) Delgado, J. A.; Á gueda, V. I.; Uguina, M. A.; Sotelo, J. L.; Brea, P.; Grande, C. A. Adsorption and Diffusion of H2, CO, CH4, and CO2 in BPL Activated Carbon and 13X Zeolite: Evaluation of Performance in Pressure Swing Adsorption Hydrogen Purification by Simulation. Ind. Eng. Chem. Res. 2014, in press. (27) Bezerra, D. P.; Oliveira, R. S.; Vieira, R. S.; Cavalcante, C. L., Jr; Azevedo, D. C. Adsorption of CO2 on nitrogen-enriched activated carbon and zeolite 13X. Adsorption 2011, 17, 235−246.
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