Rule of 100: An inherent limitation or performance measure in oxidative coupling of methane?

Journal of Natural Gas Chemistry 21(2012)308–313

Rule of 100: An inherent limitation or performance measure in oxidative coupling of methane? Saeed Sahebdelfar,

Maryam Takht Ravanchi∗ ,

Mahtab Gharibi, Marzieh Hamidzadeh

Catalyst Research Group, Petrochemical Research and Technology Company, National Petrochemical Company, No. 27, Sarv Alley, Shirazi-south, Mollasadra, P. O. Box 1435884711, Tehran, Iran [ Manuscript received November 4, 2011; revised December 19, 2011 ]

Abstract The oxidative coupling of methane over La2 O3 /CaO type-catalyst in a fixed-bed reactor is studied under a wide range of operating conditions (973
1. Introduction Natural gas has received great attention as alternative feedstock to petroleum for chemical synthesis [1,2]. It has a number of advantages such as abundance, easy purification, source independent conversion and also that its conversion to higher hydrocarbons does not necessitate further hydrogen. The index of hydrogen deficiency, i, defined by Olah et al. [3] for hydrocarbons can be extended to oxygenates as i=

(2C + 2) − H + 2O 2

(1)

where, C, H and O are the number of carbon, hydrogen and oxygen atoms, respectively. This index indicates the amount of theoretical hydrogen required to obtain alkanes from corresponding hydrocarbons or oxygenates. Therefore, it is zero for methane and higher alkanes and also it increases with the degree of unsaturation of the hydrocarbon. Compared with other carbon sources, coal is very hydrogen deficient. Biomass is of variable composition and is also hydrogen deficient due to its high oxygen content (refer to Equation 1). ∗

Consequently, natural gas remains currently the most potential alternative to petroleum. The direct conversion of methane to higher hydrocarbons through oxidative coupling of methane (OCM) has been considered as a promising route to utilize natural gas resources as a feedstock for refining and petrochemical industries. Currently, low yield and highly exothermic nature of the reactions delayed the commercialization of this process [1]. The concepts proposed for OCM process in the last two decades, including OXCO Process, UCC Process, ARCO Process, Suzuki Process, Turek-Schwittay Process, and Co-generation Process for which all have a similar structure, high energy demand for product separation and purification in common [4]. The challenge results in a concurrent design and improvement of catalyst, reactor unit and the downstream process. A great variety of oxides are active catalysts in OCM. It has been found that a wide range of basic oxides are effective catalysts with irreducible Group IIA metal oxides being the most effective. Other good catalysts are supported metal oxides and carbonates. Many of these oxides show remarkably similar conversion-selectivity results, suggesting common

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Copyright©2012, Dalian Institute of Chemical Physics, Chinese Academy of Sciences. All rights reserved. doi:10.1016/S1003-9953(11)60369-1

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active sites and mechanism [3]. The observed products are C2 H6 , C2 H4 , CO, CO2 , H2 O, H2 and some higher hydrocarbons. CH3 OH and CH2 O are also found in trace amounts. It has been found that reactor configuration and operating mode play an important role in achieving high conversion and selectivity. In fixed-bed reactors, 50% selectivity can be obtained for 40% conversion at atmospheric pressures. C2 yields of 20%−25% are commonly achieved [3]. However, because higher hydrocarbon products are more susceptible than methane feed to deep oxidation, higher once-through yields are rather rare in the literature. The oxygen attack typically results in yield-conversion trajectories that go through a maximum at some intermediate methane conversion [5]. The use of alternative oxidants such as carbon dioxide has been proposed to avoid homogeneous reactions which are considered as an important cause of the undesired deep oxidation reactions when oxygen is used as the oxidant [6−9]. Equilibrium yields of C2 H6 and C2 H4 evaluated by thermodynamic calculations exceed 15% and 25% at 800 ◦ C for a feed with CO2 /CH4 ratio of 2, respectively [7,8]. The screening of a large number of catalysts, however, shows that the practical yields are much lower, typically less than 10% [6−12]. This is due to the poor performance of the available catalysts which should be improved to be capable of activating both CH4 and CO2 and also producing C2 hydrocarbons selectively. It has been found that the injection of chloromethanes as catalyst modifiers or incorporation of chloride ion as catalyst promoter can further improve the catalyst performance in OCM reaction [13−15]. Controlled oxygen addition strategies which avoid product degradation have also been suggested [5]. From the above discussion, it appears that C2 yield is limited to a certain level. It has been also found that C2 selectivity decreases almost linearly with methane conversion, which is usually achieved by increasing the concentration of oxygen in the feed. This undesirable behavior has been formulated as the “rule of 100” (or “100% rule”), which implies that the sum of methane conversion and C2 selectivity is nearly 100% [16−19]. Therefore, the sum of conversion and selectivity reaching 100% was occasionally considered as a desired performance of the best catalyst discovered for OCM reaction during the past two decades. Unfortunately, very few catalytic systems with two supported transition metal oxides promoted by alkali metal ions have been proven to attain this level. The alkali earth metal oxides and/or rare earth metal oxides without halogen ion doping have not achieved this goal yet [20]. The rule of 100 is an emperical formula that has been obtained from experimental results. No systematic and modeling work has been done to identify its applicability and/or limitations. In the present work, oxidative coupling of methane in a fixed-bed reactor over a La2 O3 /CaO type-catalyst is studied. This catalyst is very active and selective in OCM reaction [21]. The reactor is modeled assuming one-dimensional, pseudohomogenous and plug-flow conditions. The model is solved by Matlab software. The results are discussed and compared with the rule of 100 and the findings are compared with some of the best performance test results reported in the literature.

2. Kinetic model Several kinetic models have been reported for OCM reaction [22−27]. The model of Stansch et al. [24] is an adequate one as it considers the main products in a 10-step reaction network shown in Figure 1.

Figure 1. Main reaction paths according to 10-reaction model of Stansch et al. [24]

All reactions except for the homogenous dehydrogenation of ethane (Step 7) are catalytic: Step 1:

CH4 +2O2 −→ CO2 +2H2 O

(2)

Step 2:

2CH4 +1/2O2 −→ C2 H6 +H2 O

(3)

Step 3:

CH4 +O2 −→ CO+H2 O+H2

(4)

Step 4:

CO+1/2O2 −→ CO2

(5)

Step 5:

C2 H6 +1/2O2 −→ C2 H4 +H2 O

(6)

Step 6:

C2 H4 +2O2 −→ 2CO+2H2 O

(7)

Step 7:

C2 H6 −→ C2 H4 +H2

(8)

Step 8:

C2 H4 +2H2 O −→ 2CO+4H2

(9)

Step 9:

CO+H2 O −→ CO2 +H2

(10)

Step 10:

CO2 +H2 −→ CO+H2 O

(11)

The inhibiting effect of oxygen and carbon dioxide on ethane formation rate is described by Hougen-Watson type rate equation [24,28] −E a

r2 =

k0,2 e RT (K0,O2 e [1 + K0,O2 e

−ΔHad,O 2 RT

−ΔHad,O 2 RT

pO2 )n2 pCH4

pO2 + K2,CO2 e

−ΔHad,CO 2 RT

pCO2 ]2 (12) For other oxidation reactions, only the inhibiting effect of carbon dioxide is considered in Hougen-Watson type rate equations m

rj =

n

k0,j e−Ea,j/RT pc j pOj2

(1 + Kj,CO2 e−ΔHad,CO2 ,j /RT pCO2 )2

j = 1, 3 − 6

(13) where, subscript C denotes carbon-containing reactant in step j. All the remaining equation kinetics are described by power law rate equations: 7 r7 = k0,7 e−Ea,7 /RT pm C2 H6

(14)

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m

n

r8 = k0,8 e−Ea,8 /RT pC28H4 pH82 O m

n

r9 = k0,9 e−Ea,9 /RT pCO9 pH92 O

m

n

(15)

r10 = k0,10 e−Ea,10 /RT pCO102 pH10 2

(16)

where, the subscripts refer to reaction steps. The kinetic parameters are given in Table 1.

(17)

Table 1. Kinetic parameters of catalytic reactions [24,28] Step 1 2 3 4 5 6 7 8 9 10 ∗

k0,j

(mol·Pa(m+n) /(s·g) 1.97×10−6 2.31×101 5.20×10−7 1.06×10−4 1.69×10−1 6.05×10−2 9.00×103 1.22×107∗ 2.64×10−2 1.88×10−4

Ea (kJ/mol) 48 182 68 105 157 166 300 226 220 173

Kj,CO2 (Pa−1 ) 0.24×10−12 0.82×10−13 0.35×10−13 0.40×10−12 0.44×10−12 0.16×10−12

ΔHad,CO2 (kJ/mol) −176 −187 −187 −168 −166 −211

KO2 (Pa−1 )

ΔHad,O2 (kJ/mol)

−124

0.23×10−11

mj 0.25 1.0 0.55 1.0 0.95 1.0 1.0 1.0 1.0 1.0

nj 0.75 0.40 0.85 0.55 0.35 0.95 0.0 0.0 1.0 1.0

mol/(s·m3 ·Pa)

3. Reactor model The assumptions in modeling of the reactor were same as those considered by Stansch et al. [24], that is, onedimensional, pseudo-homogenous and plug-flow model. Nitrogen was present as diluent and the reactor was assumed as isothermal. The governing equations are as follows. Mass balance for species i dFi /dz − πdWc Ri = 0

(18)

where, F is the molar flow rate, z is axial distance along the bed, d is reactor diameter, and Wc is catalyst loading or bed void volume per wall area for heterogeneous or homogeneous reactions, respectively. Ri is the net rate of formation of species i Ri = Σνij rj

(19)

the range of ±20% which is within the range given in reference [24]. Using various methane to oxygen molar ratios in the feed, the conversion of methane and selectivity to C2 products were calculated under different operating conditions and compared with the rule of 100. 4. Results and discussion 4.1. Model results Figure 2 shows a typical molar flow rate profile of different species involved in OCM reaction network. The flow rate of the reactants, methane and oxygen decreased through the reactor. The flow of primary products, that is, higher hydrocarbons, tended to pass a maximum while that of water and COx tended to increase as the ultimate products.

where, νij is the stoichiometric coefficient for the species i in reaction j. The energy balance equation is dT /dz −

Wc U A(T s − T )/Wc − ∑ rj (−ΔHj ) =0 l ΣFi cpi

(20)

where, T is fluid temperature, U is heat transfer coefficient, A is heat transfer area, Ts is reactor wall temperature, Wc is the catalyst loading and ΔH represents the heat of reaction at the reaction temperature. The molar flow of species i at each point within the reactor can be obtained through solving set of differential equations given by Equations (18) and (20), thereby performance parameters such as methane conversion, product selectivity and yields can be calculated. The model was solved by Matlab codes using ode15s solver function due to strong stiffness of the set of differential equations involved. The reactor output was checked for carbon, oxygen and hydrogen balance. Under most conditions, the experimental data were fitted fairly well with an error in

Figure 2. Typical molar flow rate profiles along the reactor. Reaction conditions: CH4 /O2 /N2 = 2/1/2, T = 1073 K, p = 1 atm, mcat /VSTP = 50 kg·s·m−3

Journal of Natural Gas Chemistry Vol. 21 No. 3 2012

Carbon oxides and water are the thermodynamically favored products in OCM reaction and the product distribution should be controlled kinetically to achieve acceptable yields. Therefore, in the case of availability of oxygen and long residence times, carbon oxides will be the dominant products as shown in reaction scheme of Figure 1. At all temperatures, methane conversion increased by decreasing methane to oxygen molar ratios, accompanying a decrease in C2 selectivity (Figure 3). This is due to the fact that C2 products are more reactive than methane feed, therefore, at lower conversion levels most of carbon oxides are derived from methane, whereas at higher conversions required for practical application, ethylene is the dominant source of carbon oxides. It has been confirmed by isotope labeling tests [29]. Figure 3 also illustrates that C2 yield passed through a maximum at intermediate methane conversions. The optimum CH4 /O2 molar ratio was close to 2, which is also the stoichiometric ratio in ethylene formation reaction. It is noteworthy that experimental observations on other catalytic systems also resulted in the same ratio as the optimum value for maximum C2 yield [30].

311

Figure 4. Influence of temperature on deviation from the rule of 100 (dash line) for 973 K, 1073 and 1103 K. Reaction conditions: p = 1 atm, mcat /VSTP = 25 kg·s·m−3

Figure 5 illustrates the influence of the operating pressure on conversion-selectivity behavior. The higher the pressure, the lower the deviation from rule of 100 was. However, the effect of pressure was not as pronounced as that of temperature. Relatively few works has been done on the influence of the total pressure on OCM catalyst performance. As an example, it has been shown that over Na-Mn-W/SiO2 catalyst total pressure adversely influence OCM reaction, which can be revealed using appropriate operating conditions [32].

Figure 3. Influence of methane/oxygen molar ratio on methane conversion, C2 selectivity and C2 yield. Reaction conditions: T = 1073 K, p = 1 atm, mcat /VSTP = 25 kg·s·m−3

Figure 4 shows the selectivity versus conversion at different temperatures obtained by varying the methane/oxygen molar ratio in the feed, which was compared with the rule of 100. It shows that the deviation from the rule of 100 decreased through increasing the temperature. The rather fair superposition of the selectivity versus conversion curves under higher temperature conditions, however, imply that there exists an optimum temperature close to the upper temperature bound beyond which the performance decreases by further increasing the temperature. This result is closely consistent with the findings of Tye et al. [31] arrived at the same conclusion for this system by plotting C2 yield versus methane to oxygen ratio and temperature. Too high temperatures enhance the C2 degradation pathways in the reaction network, e.g., via conversion of ethane to ethylene and subsequently ethylene to carbon oxides through the endothermic thermal dehydrogenation of ethane (Step 7) and steam reforming of ethylene (Step 8), respectively.

Figure 5. Influence of total pressure on deviation from the rule of 100 (dash line) for p = 0.5 atm, 1 atm and 2 atm. Reaction conditions: T = 1103 K, mcat /VSTP = 25 kg·s·m−3

Figure 6 shows that deviation from the rule of 100 decreased with decreasing the space velocity. Again, the rather fair superposition of the selectivity versus conversion curves at higher residence times imply that there exists an optimum contact time close to the upper contact time bound beyond which the performance decreases by further increasing the residence time. It can be attributed to the fact that C2 products are the intermediates in reaction network, as long as oxygen is available in reaction mixture, and the yield of these compounds should pass a maximum upon increasing the residence time, after which further increase will reduce the yield.

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reported data of good single-pass results [1,3]. The maximum yield of C2+ of 25% occurs at 50% methane conversion. However, due to predominant negative deviation and upward curvature of selectivity-conversion curve, the maximum yield is smaller and occurs at conversion levels somewhat lower than 50%. 4.2. Other catalytic systems

Figure 6. Influence of space velocity on deviation from the rule of 100 (dash line) for mcat /VSTP = 3.70 kg·s·m−3 , 25 kg·s·m−3 and 50 kg·s·m−3 . Reaction conditions: T = 1103 K, p = 1 atm

In Figures 4−6, one observed a monotonic decline of selectivity with conversion except at the extreme of methane conversion (i.e. ∼100% conversion) where after an inflection point the curvature became downwards. It is noteworthy that by extrapolating the conversion curve of Figure 3 to zero, methane concentration (corresponding to 100% conversion), a similar non-monotonic trend was observed in the conversion at the same region (i.e. ∼100% conversion) and the curve was a reversed S-shaped one. This trend accounts for the observed non-monotonic behavior for C2 selectivities versus conversion at high methane conversions in Figures 4−6. At extreme methane conversions, the concentration of oxygen was in great excess to that of methane and the oxygen concentration remained virtually constant. In other words, the method of excess can be applied. Under these conditions, the rate equations for the three main reactions (Equations 2−4), are merely a function of methane partial pressure. According to Table 1, the exponents of methane partial pressure in rate equations for deep oxidation reactions (Equations 2 and 4) were less than unity and lower than that for OCM reaction (Equation 3). Consequently, these predominant reactions were rather weakly effected by methane concentration, and also by methane conversion. In fact, in the extreme region, the addition of methane to the oxygen-rich feed results in its instantaneous consumption by rapid deep oxidation reactions and therefore fairly completes methane conversion. Consequently, any factor reducing deep oxidation should result in more monotonic selectivityconversion behavior. Accordingly, when the temperature and pressure decrease, or space-velocity increases, deep oxidation reactions are reduced and smoother selectivity-conversion trends are obtained, as shown in Figures 4−6, respectively. To have a better insight into the interpretation of Figures 4−6, it should be noted that C2 yield is the area of the rectangle bounded by the axes with its edge located on the conversion-selectivity curve. Consequently, when the rule of 100 is valid, the maximum yield is 25% corresponding to the area of a bounded square. This value is consistent with the

Figure 7 illustrates the validity of the rule of 100 for C2 yield of 15% or higher from the literature, over a variety of catalyst systems (for details of catalyst formulation and operating condition, the interested researcher is referred to the references cited). In this figure, the dashed lines for 25% and 30% C2 yields were also drawn to provide a scale for the magnitude of yield values of experimental results depicted. These lines further illustrate the deviation of the loci of constant yields from the rule of 100 line. Despite widely different catalyst formulations and operating conditions, one observes that the data points were concentrated roughly in 20%–50% methane conversion region (bounded by the ellipse) close or on the rule of 100 line as shown in the previous section. The selectivity-activity trend was also similar to those obtained in this work. This, along with other experimental results [35−39] not shown in Figure 7, illustrates that the findings of this work can be extended to other catalytic systems. In a recent work, Ahari et al. [40] optimized OCM reaction conditions by multi-objective optimization of a supervised artificial neural network model for Na-W-Mn/SiO2 catalyst to maximize methane conversion and C2+ selectivity simultaneously. The optimal operating conditions (that is, C2+ yield>23%) at 0.4 MPa resulted in a series of data points, located roughly around 35% methane conversion and 68% selectivity, nearly at the center of the ellipse in Figure 7, which fit fairly well the rule of 100 line. As a final remark, the data point could superpass the rule of 100 at extreme methane conversion, however, the yield is not necessarily large in these regions.

Figure 7. Applicability of the rule of 100 to experimental data of 15% yield or higher

Journal of Natural Gas Chemistry Vol. 21 No. 3 2012

5. Conclusions The modeling study of conversion-selectivity behavior over La2 O3 /CaO type-catalyst in oxidative coupling of methane shows that the approach of reaction system to the rule of 100 depends on operating conditions. Under operating conditions employed in this work, higher temperatures, pressures and residence times result in approach to the rule of 100. More generally, as the operating conditions approach the optimum levels, the deviation from the rule of 100 is minimized. It is deduced that the maximum C2 yield data points should be concentrated in the region of 20% to 50% methane conversion for negative deviations and rule of 100 behavior, respectively. These findings are found to be further confirmed by the experimental data and operating condition optimization works from the literature for other catalyst systems. As a consequence, the rule of 100 could be viewed as a formulation close to the upper limit of C2 yield for single-pass oxidative coupling of methane by oxygen, which could provide a measure for the further space for catalyst formulation improvement. Nomenclatures A heat transfer area, m2 cpi heat capacity for component i, J/(mol·K) d reactor diameter, m ΔHad adsorption enthalpy, J/mol ΔHj heat of reaction for reaction j, J/mol activation energy, J/mol Ea Fi molar flow rate for component i, mol/s pre-exponential factor of reaction j, mol·Pa(m+n) /(s·g) k0,j K adsorption constant, Pa−1 l catalyst bed length, m mj reaction order nj reaction order p partial pressure, Pa R gas constant, J/(mol·K) net rate of formation of species i, mol/(s·m3 ) Ri rj reaction rate for step j, catalytic: mol/(g·s); gas phase: mol/(m3 ·s) νSTP volumetric gas flow rate under STP conditions, m3 /h T temperature, K U heat transfer coefficient, J/(m2 ·K) vij stoichiometric coefficient of the specie i in reaction j Wc catalytic: catalyst loading per wall area, g/m2 ; gas phase: bed void volume per wall area, m z axial distance, m

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