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Methane recovery from coal bed gas using modified activated carbons: a combined method for assessing the role of functional groups Ziyi Li, Yingshu Liu, Chuan Zhao Zhang, Xiong Yang, Jianliang Ren, and Lijun Jiang Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.5b01706 • Publication Date (Web): 11 Sep 2015 Downloaded from http://pubs.acs.org on September 19, 2015
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Methane recovery from coal bed gas using modified activated carbons: a combined method for assessing the role of functional groups
Zi-Yi Lia, Ying-Shu Liua, Chuan-Zhao Zhang b,*, Xiong Yanga,**, Jian-Liang Rena, Li-Jun Jianga
a
School of Mechanical Engineering, University of Science and Technology Beijing, Beijing
100083,PR China b
College of Biochemical Engineering, Beijing Union University, Beijing 100023,PR China
*Corresponding author (T) +86-10-52072257; (F) +86-10-62329145. E-mail address:
[email protected]. **Co-corresponding author: (T) +86-10-62332730; (F) +86-10-62334210. E-mail address:
[email protected].
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ABSTRACT Chemical modification at room temperature on adsorbents is a cost-effective and convenient way of enhancing the methane recovery from the coal bed gas. In this study, modifications on coconut shell-based activated carbons (ACs) by aqueous ammonia and KOH agents were investigated and their performances on CH4/N2 separation were evaluated through equilibrium and dynamic adsorption tests. The roles of the oxygen- and nitrogen- containing groups in selective adsorption for CH4 over N2 on modified ACs were mainly discussed, based on the results of the Fourier Transform Infrared spectroscopy (FTIR) characterization and the Density functional theory (DFT) calculation. With this combined method, the practical changes in AC surface chemistry during modifications and the theoretical adsorption energies of CH4 and N2 over graphene models were obtained. Aqueous ammonia was shown to improve equilibrium and dynamic selectivities of CH4 by 11.7 % and 14.9 %, respectively, likely due to the introductions of amine and amide capable of differentiating the adsorption energy of CH4 and N2 on ACs. However, KOH modification reduced the selectivity of CH4 as a result of the decreases in amine and hydroxyl, in spite of an increased CH4 adsorption capacity likely due to the decreased epoxy and hydroxyl.
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1. INTRODUCTION Coal bed methane (CBM) is a mixture of coal mine methane and air, which is produced or released in association with coal mining activities. In recent years, CBM has drawn worldwide attention due to their potential of being an available clean energy source1 as well as the negativities of greenhouse effect2 and explosion harzard.3 Capturing and utilizing CBM will provide an additional energy source that otherwise would be lost and several technologies are commercially used to separate methane from other impurities,4 such as cryogenic, pressure swing adsorption (PSA), solvent absorption, molecular gate, and membrane technologies. Among these techniques, PSA is often recommended due to its easy operation, low energy requirements, and low maintenance,5 for which activated carbon is considered one of the most advantageous adsorbents because of its thermal stability and high separation ability. The adsorption behaviors of the typical CBM gases, CH4 and N2, on activated carbons are of great significance to separate CH4 from the coal bed gas.6-9 To improve the practical efficacy of activated carbons in CBM recovery, different approaches of modifying adsorbents have been studied, either physically in terms of pore size, structure and connectivity,10 or chemically in terms of surface functional groups.11,12 In comparison to the modifications with heating processes, the chemical modification at room temperature has advantages of low energy consumption, convenient operation and high control accuracy. Surface chemistry changes are expected to mainly affect the methane selective adsorption by, for instance, functionalizing the solid supports with some key oxygen- or nitrogen- containing groups.13,14 These heteroatoms generally determine the charge, hydrophobicity, and electronic density of the carbon layers.15,16 To gain deeper insight into the effects of functional groups on CH4/N2 separation, more recently, significant progress has been made for methane-carbon systems through molecular simulation.17 Based on the density functional theory (DFT) method, the adsorption of CH4 on the graphene is frequently used as the model to calculate energy exchanges of moleculemolecule and molecule-substrate.18 Lu et al. studied the chemical functionalization on planar 3
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graphane using fluorination as an example on the basis of DFT calculations.19 Liu et al. indicated that the use of N-, B- or NB-doped graphenes provide a simple and important way to explore the microcosmic of CH4 with heterogeneous coal, and offered a deeper understanding of the gas behavior on chemically-modified surfaces.20 Wood et al. computed methane binding energies for a wide variety of functional groups, yielding microscopic information on the affinity of binding sites toward methane.21 From theoretical point of view, DFT calculation merits a wide use for exploring CH4 adsorption behaviors on carbons, while it also needs to be checked by experiments for the sake of validation and completeness. To our best knowledge, investigations combining both results of experiments and DFT calculations into the CH4/N2 selective adsorption are very limited. In this work, the separation performances of CH4/N2 on modified activated carbon (AC) by two common alkaline activating agents (aqueous ammonia and KOH) were studied. Equilibrium and dynamic adsorption tests were conducted to pick out the optimal modification condition for each agent. Fourier transform infrared spectroscopy (FTIR) characterizations for changes in AC surface functional groups and DFT calculations for adsorption energies of CH4 and N2 over appropriate graphene models were combined to elucidate the roles of the oxygenand nitrogen- containing groups in CH4 selective adsorption.
2. MATERIAL AND METHODS 2.1. Sample descriptions A coconut-shell activated carbon (ST1000, Nantong Carbon Co., Ltd, China) was used as the precursor, and was ground and sieved to the US mesh size 12-20 (1400-850 μm). It was then washed with deionized (DI) water to eliminate ash impurities, dried at 353 K for 12 h to remove moisture, and stored in ziplock bags until use (denoted as AC0). The aqueous ammonia and solid KOH were dissolved into water as the modification agents, respectively. The adsorbents were impregnated into NH3⋅H2O and KOH solutions at a ratio of 5 g AC0 to 100 ml 4
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solution. Five volume fractions of both agents in the solutions, 5, 10, 15, 20 and 25 %, and three impregnation times, 6, 12 and 24 h, were chosen as the investigated variables. The impregnation temperature was set at 293 K. After impregnations, the ammonia- and KOHmodified ACs were washed with DI water and then dried at 383 K for 2 h. 2.2. Characterizations of AC samples Infrared spectroscopy was used to study changes in surface functional groups before and after modifications. The infrared spectra were recorded on a Fourier Transform Infrared spectroscopy (FTIR) (Nicolet 6700, Thermo Scientific, USA) in the 1000 - 4000 cm−1 range with a resolution of 4 cm−1 and a scan rate of 0.2 cm-1. The KBr pellet technique was used with 1.0 mg of AC per 900 mg KBr. The carbon-KBr mixtures were ground, then desorbed under vacuum (10-2 Pa) and finally pressed in a hydraulic press. Before the spectra of a sample was recorded, the background line obtained was automatically subtracted. Nitrogen isotherms were measured using a surface area and porosimetric instrument (Autosorb-1, Quantachrome Instruments, USA) at 77 K for characterizing texture properties of the activated carbon. Prior to the measurement, samples were heated at 393 K and then outgassed at this temperature under a vacuum of 10−5 Torr for at least 12 h. The specific surface areas (SBET) were determined by the Brunauer−Emmett−Teller (BET) method using N2 adsorption data in a relative pressure range from 0.1 to 0.3. The micropores (dp < 2nm) size distributions were obtained using the non-local density functional theory (NLDFT) method which is also capable of giving the mesopore volume (Vmicro) and the average micropore widths (L). The total pore volumes (Vt) were estimated according to N2 uptake at a relative pressure (P/P0) of 0.99. 2.3. Equilibrium adsorption test Equilibrium adsorption isotherms of CH4 and N2 were measured at 298 K using the static volumetric adsorption method on a surface area and porosimetric instrument (Autosorb-1 (Quantachrome Instrument, USA). The samples were out-gassed at 393 K under vacuum for 5
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12 h prior to measurement. The equilibrium selectivity and adsorption capacity for CH4 can be obtained by fitting Langmuir equation to the measured isotherms. The Langmuir model can be represented as follows:
qi qm
bP 1 bP
(1)
where qi is the amount adsorbed in equilibrium with the concentration of adsorbate in gas phase (mg/g), qm is the maximum adsorption amount (mg/g), b is the Langmuir constant, P is the equilibrium pressure of the adsorbate in gas phase (kPa). In the model, qm and b can be calculated from the linear plots of P/qi versus P. The equilibrium selectivity (αe,AB) is a parameter obtained without complicated calculations, and Ruthven considered that if the isotherms satisfy Langmuir equation,22 αe,AB could be an ideal constant for the entire range of partial pressures as:
e,AB
q b x A xB xA yA mA A y A yB (1 x A ) (1 y A ) qmB bB
(2)
where xA, xB are the mole fractions of the two gaseous components, and yA, yB are their corresponding mole fractions in the gas phase, respectively. 2.4. Dynamic adsorption test To assess the practical CH4/N2 separation performance on modified samples, dynamic adsorption was carried out with the schematic diagram shown in Figure 1. Real-time volume concentration of the gas at the outlet of the column was measured with a mass spectrometer (QGA, Hiden Analytical, UK). Before each run, the adsorption column and pipes were purged with He (purity > 99.999 %) at 10 L/min, and then filled with pure N2 (purity > 99.999 %) at atmospheric pressure. By allowing 1 % volume faction of CH4 balanced by 99 % of N2 at 7.9 6
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L/min to flow through a column packed with ACs (~ 340 g) at room temperature and atmospheric pressure, the breakthrough curves of CH4 and N2 were measured. The use of the very small volume fraction of CH4 in the feed is to keep a constant exit velocity equal to the inlet one, and thus guarantee the data accuracy. As indicated by previous literatures,23,24 when the fraction of the adsorbable component in the feed is large, it introduces a velocity variation at the exit of the column due to adsorption or desorption. Based on the sigmoid shape of the data points, the experimental breakthrough curves were fitted by means of Boltzmann’s function which has generally been accepted as an accurate method:25
y A2
A1 A2 1 e( x x0 ) / dx
(3)
where x is the adsorption time (s); y is the exit number of moles flow rate for a gaseous compound (mol/s); A1, A2 are the beginning and ending number of moles flow rate for a gas, respectively (mol/s); x0 is the time at which y reaches the value of (A1 + A2)/2; and dx is a parameter related to the slope of the curve at x=x0 (y'∣x=x0 = (A2 - A2)/2dx). The total amount of the effluent gas during a period (t), nout (mol), can be obtained as:
A1 A2 nout A2 dx 1 e( x x0 ) / dx 0 t
(4)
Then the dynamic adsorption capacity of the adsorbents packed in the column at the adsorption time t, qd, can be determined as:
A1 A2 qd nin q0 nout yin t qe mad A2 dx 1 e( x x0 ) / dx 0 t
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(5)
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where yin is the inlet number of moles flow rate for the compound; qe is the equilibrium adsorption capacity of the compound on the adsorbent at atmospheric pressure, which can be obtained from corresponding isotherms (figure 5); mad is the mass of the packed adsorbents. As a key parameter to evaluate the practical performance of CH4/N4 separation, the dynamic selectivity, αd,CH4/N2, can be obtained as:
αd,CH4 /N 2
xCH4 xN 2 yCH4 yN 2
qd ,CH4 qd , N 2
99
(6)
2.5. Computational detail The DFT calculations of the original and modified carbon surfaces were carried out using the CASTEP package in Materials Studio program. The calculation was based on ultrasoft pseu-dopotential method for the plan-wave basis set.26,27 The electronic exchange and correlation were evaluated using PBE mode of the generalized gradient approximation (GGA).28 A Monkhorst−Pack k-point mesh of 4×4×2 for Brillouin zone sampling29 and a cutoff energy of 400 eV were selected from convergence tests in which geometry structures were relaxed until the force on each atom was less than 0.01 eV/Å with the convergence criteria of 10-5 eV. A 2×2 graphene supercell was used as the carbon model being doped with functional groups. After the energies for each optimized structure in the CH4–surface system was obtained, the adsorption energy,30 Ead, of adsorbate molecules on the graphene can be defined as:
Ead ( EGadsorbate EG Eadsorbate)
(7)
where EG, EG-adsorbate and Eadsorbate are the total energy of the CH4–graphene system, the graphene without adsorption and the isolated adsorbate molecule, respectively. 8
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In building of the graphene layer as the carbon model being functionalized, several models have been put forward according to graphite oxide (GO) structures that are close to the quasicrystalline graphite unit.31 Lerf and Klinowski confirmed a widely accepted structural model based on experimental NMR spectra of GO derivative.32,33 It is believed that GO has mainly hydroxyl (-OH) and epoxy (-O-) groups on the basal graphene layer and carboxylic acid groups (-COOH) at edge sites. Carbonyl groups (C=O) are found to be randomly distributed as holelike structures in the GO sheets34 or on the free edges of GO sheets.35 For N-containing groups, the carbon-nitrogen bond intends to form at the edges of the graphene where chemical reactivity is high.36 Accordingly in this simulation work, the epoxy and hydroxyl groups were grafted onto the perfect graphene sheets, and the carbonyl, carboxyl, amide and amino groups were doped at the edges or vacancy sites of the defect graphene sheets. Considering a general situation that epoxy and hydroxyl groups are more likely to appear on both sides of the perfect graphene to form stable structures,37,38 two-sided configurations of perfect graphene doped with epoxy and hydroxyl pairs were established, respectively. Two possible relative locations of epoxy pairs and three those of hydroxyl pairs in hexagonal carbon rings are shown in Figure 2 and Figure 3, respectively. The locations of the epoxy and hydroxyl groups on graphenes were determined depending on which one exhibited a lower total energy after the structure optimizations. One the other hand, for the carbonyl, carboxyl, amide and amino groups doped onto defect graphene sheets, there was only one location for each of these isolated groups as shown in Figure 4, respectively. 3. RESULTS AND DISCUSSION 3.1. Equilibrium adsorption Figures 5 (a) and (b) show the adsorption amount for each gas in equilibrium with bulk pressure, namely the adsorption isotherms, on modified samples at different impregnation times with 10 % aqueous ammonia and 10 % KOH agents, respectively. The isotherms can be 9
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well described by Langmuir equation with fitting correlation coefficients R2 of more than 0.99 as shown in Table 1. The fitting curve for each isotherm is also shown in the figures and related parameters are listed in Table 1. It can be found that KOH failed to improve the selectivity for CH4 over N2 at either impregnation time, although its adsorption capacity of CH4 after 12-h modification is higher compared to the original AC sample. 12-h is also the optimal impregnation time for the aqueous ammonia modification in terms of higher qm and αe of CH4 as compared to 6- and 24-h samples. The shorter impregnation time might be not enough long for the functionalized groups completely being doped onto the AC surface, while a prolonged impregnation time would result in severe carbon-KOH reaction, leading to the collapse of some microporous structures. The effects of the impregnation concentration for both agents on CH4/N2 separation were also evaluated from the results of Langmuir fitting to the equilibrium isotherms. Figure 6 (a) and (b) directly depict the qm and αe of CH4 as a function of agent concentration on ammoniaand KOH- modified (12-h) samples, respectively. For the ammonia modification, αe at all impregnation concentration were increased compared to AC0, which peaks at the concentration of 10 % (5.45), 11.7 % higher than that of the AC0 (4.88). qm monotonically decreased from 1.982 mmol/g at 5 % to 1.748 mmol/g at 25 %, a different variation trend from αe, indicative of the weaker correlation between the adsorption capacity and CH4 selectivity on ammoniamodified samples compared to that on KOH-modified ones which exhibited similar variation trends of qm and αe. This to some extent suggests the contribution of modified surface properties on ammonia-modified ACs to the improved selectivity of CH4 over N2. For the KOH modification, αe also peaks at concentration of 10 % (4.84) but as above mentioned, still lower than the original value. Variations of qm and αe with the impregnation concentration show irregular trends but correlate with each other well, which indicates the CH4 adsorption capacity play an important role in selectivity of CH4 on KOH-modified AC surfaces. But the current improvement on CH4 adsorption capacity seems not prominent enough for 10
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reaching an enhanced CH4 selectivity, since the N2 was also increasingly adsorbed after the modification (Table 1). 3.2. Dynamic adsorption According to the results of the equilibrium adsorption test, the representative modified sample for each agent was selected and denoted as ACNH3⋅H2O-10%,12h and ACKOH-10%,12h, respectively. Dynamic adsorption of CH4/N2 on original and these two modified samples were carried out for further validation and analysis. Figure 7 shows the breakthrough curves of CH4/N2 binary gas and the fitting curves on these samples. The regression parameters of the curve-fitting, dynamic adsorption capacity and selectivity for each sample are listed in table 2. High correlation coefficient (R2 > 0.999) indicates that the Boltzmann function fit the experimental data well, and the dynamic capacity calculated based on it (eq 5) should be reliable. It should be noted that in contrast to the equilibrium adsorption, the very small dynamic adsorption capacity for CH4 than for N2 on samples were attributed to the much higher partial pressure of N2 than of CH4 in the feed gas (yN2 : yCH4= 99:1). The αd,CH4/N2 of CH4 over N2 for each sample follow the order of: ACNH3⋅H2O-10%,12h > AC0 > ACKOH-10%,12h, which is consistent with the order of the αe,CH4/N2 (table 1) and the median breakthrough times (X0) (table 2). The αd,CH4/N2 on ACNH3⋅H2O-10%,12h (4.62) was increased by 14.9 % from the original value of (4.02). The qd of CH4 is higher for ACNH3⋅H2O-10%,12h than for ACKOH-10%,12h, which reverses the result of their qe of CH4. This result suggests the function of aqueous ammonia that can dynamically differentiate the CH4/N2 mixture by presenting preference in adsorption of CH4 over N2 onto the modified AC surfaces, thus contributing to an increased dynamic adsorption amount of CH4, which will be further elucidated in the later molecular simulation discussions. Interestingly, the KOH modification exhibited a lower αd,CH4/N2 value compared to the original sample. This could be owing to the poor ability of separating the dynamic CH4/N2 mixture when both gases were increasingly adsorbed on the KOH-modified AC according to the equilibrium results (table 1). Further discussions about the 11
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different modification results of the aqueous ammonia and KOH agents will be presented in following sections. 3.3. Characterizations of activated carbons Figure 8 (a) and (b) show the N2 adsorption isotherms and micro-pore (
