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SAPO-34 catalysts: Product distribution and optimization
Journal of CO₂ Utilization xxx (xxxx) xxx–xxx
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CO2 hydrogenation to light olefins over Cu-CeO2/SAPO-34 catalysts: Product distribution and optimization ⁎
Mehdi Sedighia,b, , Majid Mohammadic a
Division of Energy Systems, Department of Chemical Engineering, University of Qom, Qom, Iran Center of Environmental Research, University of Qom, Qom, Iran c Department of Energy Engineering, Faculty of Science, Qom University of Technology, Qom, Iran b
A R T I C LE I N FO
A B S T R A C T
Keywords: Carbon dioxide Hydrogenation CuCe/SAPO-34 catalyst Light olefins Optimization
The direct conversion of carbon dioxide into hydrocarbons is a very desirable but difficult approach for achieving lower value-added olefins with minimal CO selectivity. In this effort, we report the direct conversion of CO2 into light olefins on a Cu/CeO2 hybrid catalyst mixed with SAPO-34 zeolite. The samples are characterized by N2 sorption, XRD, TEM, SEM, NH3-TPD and H2 -TPR. The results showed that the acidity of modified zeolite had decreased. The response surface methodology has been used to optimize the operating parameters (temperature and space velocity (SV)) of process. A high olefin selectivity of 70.4% has been obtained on CuCe/SAPO-34 at H2/CO2 =3, 10 h, 382.46 °C, 17.33 L/g.h and 20 bar. The optimum operating conditions for multiple responses have also been achieved. The optimal values are T = 396.26 °C and SV = 5.80 L/g.h. Under these conditions, the predicted olefin and CO selectivity and CO2 conversion are 61.83%, 57.11% and 13.15%, respectively. Multiple optimization outputs are outstanding for obtaining the suitable operating conditions.
1. Introduction Human action is the key reason of ecosystem change. Individuals burn fossil fuels and convert woodland into farmland. At the outset of the Industrial Revolution, people were burning more and more fossil fuels such as natural gas, petroleum and coal [1–3]. This phenomenon produces carbon dioxide. CO2 is the major source of man-made environmental change. It remains in the atmosphere for too long. Carbon dioxide is an accessible source of renewable carbon with the advantage of being non-toxic, sufficient as well as practical [4–6]. The utilization of CO2 as a substance for synthetic chemicals [7–19] should be a sustainable solution. The conversion of carbon dioxide into light olefins is a potential solution to efficiently use of CO2 as a renewable resource. Light olefins (C=2 − C=4 ) are essential building blocks for the chemical market [20,21]. There are two main methods for the formation of light olefins from CO2. (1) In general, modified Fischer-Tropsch synthesis (FTS) catalysts are utilized to hydrogenate CO2 for the synthesis of hydrocarbons consisting of two sequential reactions: the reverse water gas shift (RWGS) reaction to provide carbon monoxide, and then by hydrogenation of carbon monoxide to HCs (FTS) [22–26], (2) Conversion of CO2 into methanol and from methanol to olefins (MTO) [27–31]. Although numerous catalysts were widely investigated and
⁎
established on the FTS pathway [22–26], there was no industrial usage for such a method due to the low C2–C4 olefin selectivity and the formation of a variety of HCs, resulting in extra costs for the separation procedure. Alternatively, the production of light olefins continuous to be systematically commercialized by the MTO method [32,33] since this process has high selectivity for C2–C4 olefins (≈ 80%) as well as the small distribution of other HCs. The catalytic hydrogenation of CO2 is a novel method to solve the difficulties of excessive CO2 emissions as well as energy shortages, as Cu-based catalysts are used on a large scale. It is remarkable that the Cu-based catalysts supported on CeO2 attracted attention because of their superior catalytic performance [34–38]. CeO2 is among the most significant oxides of heterogeneous catalysis because of its substantial redox ability [35,39–42]. One of the major problems of all catalysts used in the methanol production is the yield of methanol, which is kinetically restricted at low temperatures as well as thermodynamically limited at high temperatures. To solve this problem, one of the best options is to convert methanol in situ to other valuable products such as olefins. This method has a more economical and thermodynamic benefit over a two-step method (indirect conversion) owing to alleviation of the thermodynamic limitation applied to methanol synthesis, which can change
Corresponding author at: Division of Energy Systems, Department of Chemical Engineering, University of Qom, Qom, Iran. E-mail addresses: [email protected], [email protected] (M. Sedighi).
https://doi.org/10.1016/j.jcou.2019.10.002 Received 29 June 2019; Received in revised form 23 September 2019; Accepted 1 October 2019 2212-9820/ © 2019 Elsevier Ltd. All rights reserved.
Please cite this article as: Mehdi Sedighi and Majid Mohammadi, Journal of CO₂ Utilization, https://doi.org/10.1016/j.jcou.2019.10.002
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Fig. 1. Schematic diagram of the experimental setup for an olefin production process.
2.1.3. Preparation CuCe/SAPO-34 Crystalline CuCe/SAPO-34 has been synthesized by physically coating process [53]. Initially, a specific quantity of binder (alkaline silica sol) was diluted by deionized water. The outside surface of SAPO34 powder has been covered with Cu/CeO2 (20–40 mesh) (by the mass ratio of Cu/CeO2: SAPO-34 = 1: 1). The samples were further calcined at 823 K for 4 h.
the equilibrium towards higher CO2 conversion [30]. SAPO-34, among the most favorable identified catalysts in MTO method with particularly high carbon selectivity [43–47] of about 90% to C2–C4 olefins [32] and its modified versions are employed in the industrialized UOP/Hydro MTO method. SAPO-34, with a CHA framework as well as small pore openings (≈ 3.8 Å), includes an excellent olefin yield in the MTO process and may very well be the ideal option for this system. In this paper, we establish a direct as well as selective hydrogenation of CO2 to light olefins on a hybrid catalyst, combining methanol synthesis and the conversion of “methanol to olefins”. This unique design could reduce the thermodynamic restrictions of methanol production by consuming methanol in situ and shifting equilibrium. To achieve methodical experimental data studying a wide variety of operating factors, RSM has been employed as an organized experimental design approach, and semi-mechanistic models were developed based on the results.
2.2. Catalyst characterization XRD patterns were documented on a Bruker D8 Advance instrument with Cu Kα1 radiation. TEM has been recorded on a JEOL, JEM-2200FS electron microscope. The morphology of the catalysts has been identified by a SEM, AIS2100 (Seron Technology, South Korea). The BET surface area has been measured with N2 adsorption at −196 °C using a Quantachrome ChemBET-3000 instrument. The H2-TPR of samples were recorded in a Baidewo MFTP3060 multifunction catalyst analysis system (Xiamen, China). For H2-TPR, the sample has been pretreated with argon at 350 °C for 4 h and then cooled. The sample was then reduced by a reducing gas (50 mL/min) composed of 10% H2/Ar heated from 50 °C to 600 °C at a rate of 10 K/min. The amount of acid has been studied on a Micromeritics 2000 adsorption equipment applying NH3TPD.
2. Experimental section 2.1. Catalyst synthesis 2.1.1. Preparation of SAPO-34 The crystalline SAPO-34 has been hydrothermally synthesized using TEAOH as the template. The sources of Al, Si and P were aluminum isopropoxide (AIP, Merck), Silicic acid (SiO2, Merck) and phosphoric acid (85 wt.% H3PO4, Merck), respectively. The gel molar composition was 1Al2O3:1P2O5:0.6SiO2:1TEAOH, 50H2O. The mixture was then added to a 100 mL Teflon-lined stainless steel autoclave. The autoclave was put in an oven at 453 K for 24 h. As-synthesized product was then dried and calcined in air. The complete description of SAPO-34 synthesis is included in our previous work [46–52].
2.3. Catalytic activity test The reaction has been assessed in a stainless steel fixed-bed reactor with the internal diameter of 1.51 cm and length of 45 cm. charged with 2 g of catalyst sample. The catalyst has been pretreated by heating at 450 °C for one hour in pure Ar (130 mL/min) after which a reactive gas mixture with a H2/CO2/N2 ratio of 3:1:1 and a pressure of 20 bar were provided into the reactor. The activity studies were performed at various temperatures between 300 and 500 °C and at a gas SV between 2–20 L/g.h. An online gas chromatography (Varian Chrompack CP3800) equipped with a TCD and a FID detector were used to analyze the products. Schematic diagram of the experimental setup used for olefin production is shown in Fig.1. The conversion of carbon dioxide, selectivity of carbon monoxide and olefins selectivity (C=2 − C=4 ) in hydrocarbons are defined as follows:
2.1.2. Preparation of Cu/CeO2 CeO2 supported Cu catalyst has been synthesized using a depositionprecipitation process. Simply, Ce(NO3)3.6H2O was put into a solution of oxalate at 0.15 mol/L with vigorous stirring for 2 h at 343 K and then aged for 2 h. The precipitate was then washed several times, dried at 353 K for 10 h and calcined at 773 K for 6 h. Copper samples deposited on CeO2 supports (25 wt.% Cu) were prepared using the appropriate amount of Cu(NO3)2.3H2O as precursor and oxalate as precipitant. The as-synthesized samples were calcined at 773 K for 5 h. 2
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Table 2 Variables presented in coded form (P=20 bar, H2/CO2 = 3:1, time on stream=10 h). Variables
Symbols
Temperature (°C) Space velocity (L/g.h)
X1 X2
Levels -α
−1
0
+1
+α
300 2
329.29 4.64
400 11
470.71 17.36
500 20
Table 3 Experimental runs for CO2 hydrogenation process (P=20 bar, H2/CO2 = 3:1, time on stream=10 h). Run
Fig. 2. XRD patterns of (a) CeO2; (b) Cu/CeO2; (c) SAPO-34; (d) CuCe/SAPO34.
1 2 3 4 5 6 7 8 9 10 11
Table 1 Textural properties of fresh samples. Sample
SBET (m2 g−1)
Vpore (cm3 g−1)
Average pore diameter (nm)
Crystallinity (%)
Cu/CeO2 SAPO-34 CuCe/SAPO-34
62 482 317
0.16 0.31 0.24
12.65 0.48 6.38
89 91 85
CO2 conversion =
CO selectivity =
CO2inlet − CO2outlet × 100% CO2inlet
CO outlet × 100% CO2inlet − CO2outlet
Variables
Responses
X1: T (°C)
X2: SV (L/g.h)
Solefin (%)
CCO2 (%)
SCO (%)
500.00 400.00 400.00 400.00 470.71 470.71 400.00 300.00 329.29 329.29 400.00
11.00 11.00 2.00 11.00 17.36 4.64 20.00 11.00 17.36 4.64 11.00
15.41 65.55 59.47 65.84 34.76 29.66 69.42 41.52 53.81 44.91 64.75
20.80 11.83 15.31 11.68 16.07 19.22 8.53 4.76 3.72 6.84 11.78
82.51 55.52 62.28 55.46 70.12 77.2 50.16 28.85 24.68 32.45 55.55
Solefin: olefins selectivity; CCO2: CO2 conversion; SCO: CO selectivity; T: Temperature; SV: Space Velocity.
(1)
Olefin selectivity = (2)
nCn Hmoutlet × 100% CO2inlet − CO2outlet − CO outlet
Fig. 3. Structures of catalysts, (A) SEM image of SAPO-34, (B) TEM image of Cu/CeO2, (C) NH3-TPD curve, (D) H2-TPR profile. 3
(3)
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smaller ionic radius than Ce4+ are included into CeO2 lattice [35,54]. The XRD diffraction pattern of the samples SAPO-34 and CuCe/SAPO34 shows significant peaks at 9.6°, 13.7°, 16.2°, 20.5° and 30.8° [46,48,49,55]. In addition, the first sample shows some additional peaks at 35.8°, 38.9°, 27.9° and 47.6°, which are CuO and CeO2 diffraction peaks. The peak intensities of the SAPO-34 decreased after the introduction of CuO/CeO2, which means that the crystallinity of SAPO34 reduced (Table 1). The decrease of peak intensities may be due to mixing with Cu/CeO2. To calculate the relative crystallinity, the addition of the intensities of the sample is divided by the addition of the reference intensities. The pore volume and the specific surface area of all catalysts are presented in Table 1. SAPO-34 had a microporous structure with a large specific surface area (482 m2) and almost no mesopores. High surface area is advantageous for subjecting additional active sites and multiple reactions mass transfer, thereby supporting catalytic performance. Bifunctional catalysts have a much larger surface area compared to Cu/CeO2 and contain both mesopores and micropores. Fig. 3 shows some structural characteristics of the samples. The selected SEM image of SAPO-34 catalyst shows a typical cubic-like rhombohedral morphology (identical to natural chabazite). The typical size of the sample is about 1.5 μm. The average Cu/CeO2 particle size estimated with TEM has been about 20 nm with a narrow distribution. The acidity of SAPO-34 is characterized using NH3-TPD. The desorption curve displays two typical peaks corresponding to the weak (desorption peaks at 120–260 °C) as well as the strong acid sites (desorption peaks at 320–480 °C). The strong acid sites are mostly considered to be directly relevant to the olefin production. Modified SAPO34 shows low acidity compared to that of SAPO-34. Cu species are believed to be the active site for the synthesis of methanol from carbon dioxide and hydrogen. An H2-TPR technique has
Table 4 Analysis of variance (ANOVA) for the fitted models. Source
DF
a
Sum of Squares
Mean square
F-value
p-value
612.78 13.16 21.72 0.32
46.57
0.0003
68.15
0.0145
89.59
< 0.0001
203.48
0.0049
49.08
0.0003
11592.31
< 0.0001
2
For olefins selectivity (R = 0.97). Model 5 3063.88 Residual 5 65.80 Lack of fit 3 65.16 Pure error 2 0.64 Total 10 3129.68 For CO2 conversion (R2 = 0.98). Model 5 313.26 Residual 5 3.50 Lack of fit 3 3.49 Pure error 2 0.011 Total 10 316.76 For CO selectivity (R2 = 0.98). Model 5 3584.56 Residual 5 73.04 Lack of fit 3 73.03 Pure error 2 0.0042 Total 10 3657.60 a
62.65 0.70 1.16 0.0057
716.91 14.61 24.34 0.0021
DF: Degree of freedom.
3. Results and discussion 3.1. Catalyst characterization The XRD patterns of the samples are presented in Fig.2. The peaks centered at 27.9°, 32.97°, 47.6°, 56.4° and 59.0° are assigned to the CeO2 structure. It could clearly be found that the peaks of the CuO phase are observed after the introduction of copper ions. In addition, the CeO2 peaks become wider, indicating that copper ions with a
Fig. 4. Diagnostics plot predicted versus actual for (a) olefins selectivity, (b) CO2 conversion, and (c) CO selectivity. 4
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Fig. 5. Perturbation plots for (a) olefins selectivity, (b) CO2 conversion, and (c) CO selectivity.
CO2 conversion and CO selectivity imply that the models are significant. A low P-value (< 0.05) indicates that the models were highly significant and can be used to predict the response functions. The Rsquared statistics has been also examined for the percentage variability of the optimization parameter that is outlined by the model. Therefore, R2 is 0.97, 0.98, and 0.98 for Eqs. (4)–(6) indicate an effective match for experimental data and predicted values. The predicted and experimental values of olefins selectivity, CO2 conversion and CO selectivity are shown in Figs. 4(a)–(c), respectively. These figures showed that the models agreed well with the experimental data.
been performed to assess Cu/CeO2 reducibility. These reduction peaks correspond to diff ;erent reduction processes of CuO species. For bare CeO2 samples, peaks below 600 °C may be related to the reduction of surface oxygen, subsurface oxygen and surface Ce4+ species [56,57]. The reduction temperatures of Cu/CeO2 samples are lower than those of pure CeO2, due to the interaction between the support and the copper species[39]. Two main reduction peaks (α and β) are attributed to the reduction of well dispersed CuOx species that interact highly with ceria. This is a good feature of the catalyst activity criteria[58]. 3.2. Design of experiment
3.2.1. Perturbation plots The perturbation plot reflects the evolution of the response as each factor moves away from the chosen reference point and other factors are kept constant. In Fig. 5a–c, the curvature is most evident in temperature. These show that olefin selectivity, CO2 conversion, and CO selectivity are more temperature-sensitive than SV. Fig. 5a showed that the selectivity for the highest olefins near the temperature reference point could be achieved as it increases with SV. Fig. 5b shows that both factors have a considerable influence on CO2 conversion. However, the conversion of carbon dioxide decreases with SV as it increases with increasing temperature. Fig. 5c shows that the influence of SV is less important than temperature.
The Response Surface Methodology [59–63] has been applied in this analysis for the experimental design of the CO2 hydrogenation process. Two independent variables were used in specified amounts and coded as shown in Table 2. Two parameters with a total of 11 runs (Table 3) were presented by RSM/CCD using the statistical expert [64]. The responses, Y1, Y2, and Y3 analyzed by response surface design using the quadratic equation are expressed as follows: (Y1) Solefin (%)= -580.486 + 3.254X1 +2.739X2 -2.34E-003X1X2 -4.18E-003X12-0.048X22 (4) (Y2) CCO2 (%)= -9.673 + 0.038X1 -0.226X2 -1.88E-005X1X2 +5.73E005X12 -3.53E-003X22 (5) (Y3) SCO (%)= -91.858 + 0.469X1 -0.317X2 +3.83E-004X1X2 -2.25E004X12 -0.021X22 (6)
3.2.2. Binary effects of parameters on the response Fig. 6 demonstrates the 3D response plots and 2D contour plots found from the outcomes of the olefin selectivity, CO2 conversion, and CO selectivity with temperature and SV variations. Fig. 6a, b shows the
Table 4 shows the result of a statistical analysis of variance (ANOVA). The F-value of 46.57, 89.59, and 49.08 for olefins selectivity, 5
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Fig. 6. 3D response surfaces and 2D contour lines for olefins selectivity (C=2 − C=4 ) , CO2 conversion, and CO selectivity as functions of temperature and space velocity (P=20 bar, H2/CO2 = 3:1, time on stream=10 h).
decreased slightly with raising SV. Two parallel reactions, CO2 to methanol as well as RWGS, appear concurrently throughout the carbon dioxide hydrogenation method (Eqs. (7) and (8)). The RWGS reaction is preferred at an elevated temperature, because it is an endothermic phenomenon [5,27,65,66]. In the meantime, kinetics are preferred under the methanol production conditions for the hydrogenation of CO2. The process temperature is normally relatively low (200 − 300 °C) over methanol production catalysts. Although the coupling with the MTO procedure (Eq. (9)) can
mutual consequence of temperature and SV on the selectivity of light olefins (C=2 − C=4 ) . As the temperature increased from 300 to 380 °C, the selectivity for olefins increased from 27% to 70%, signifying the success of developed catalyst in selective hydrogenation of CO2. As the same time, the percentage selectivity of the olefins has been first increased with increasing SV and reached a maximum, then lowered. Fig. 6c, d reveals the effect of temperature and SV on the conversion of CO2. As these figures show, CO2 conversion has increased dramatically with temperature. It has also been found that the CO2 conversion 6
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Table 5 Result of the final optimal point in the single and multiple optimization (P=20 bar, H2/CO2 = 3:1, time on stream=10 h). Objective
Variables
Responses (Model)
T (°C)
SV (L/g.h)
Solefin (%)
Responses (Exp)
CCO2 (%)
SCO (%)
Solefin (%)
CCO2 (%)
SCO (%)
̶
71.18
̶
̶
25.11
̶
Single
Max Solefin
382.46
17.33
70.44
̶
Single
Max CCO2
500.00
2.00
̶
23.25
̶
̶
Single
Min SCO
300.00
20.00
̶
̶
16.19
̶
̶
17.27
Multiple
Max Solefin ; Max CCO2 ; Min SCO
396.26
5.80
61.83
13.15
57.11
63.10
15.23
56.84
Table 6 The comparison between experimental data and prediction. Variables
Solefin (%)
CCO2 (%)
SCO (%)
SCH4 (%)
SC2-C4 (%)
SC5+ (%)
T (°C)
SV (L/g.h)
Model
Exp
RMSE
Model
Exp
RMSE
Model
Exp
RMSE
Exp
Exp
Exp
397.52 496.64 363.80 458.08
12.83 11.30 18.63 16.73
68.15 16.85 68.85 47.91
67 18.11 69.15 45.86
1.58
10.97 20.30 6.23 14.92
11.33 20 8.15 12.82
1.29
53.45 81.45 38.38 67.52
55.15 80.28 40.97 65.77
1.68
3.18 21.54 2.47 9.55
26.14 51.73 24.44 37.15
3.68 8.62 3.94 7.44
SV = 5.80 L/g.h, the selectivity to olefins (61.83%), CO (57.11%), and the conversion of CO2 (13.15%) can be obtained accordingly. An experiment has been conducted to validate the optimal conditions proposed by the model. Table 5 demonstrates that the results of the verification experiment are in excellent agreement with the expected values derived from the fitted models. Table 6 also shows the comparison between the experimental data and the predictions of RSM. The RMSE values between the experimental data and the predictions are all less than 2, showing their relative accuracy in the modeling system. In addition, experimental data for other hydrocarbons (CH4, C2-C4 paraffins and C5+) were mentioned in Table 6.
derive the carbon dioxide conversion, the zeolite is not effective at such a low temperature for the CeC coupling reaction. The mismatch of their reaction temperatures leads to the formation of a considerable level of CO.
CO2 + H2 ↔ CO+ H2 O (RWGS)
(7)
CO2 + 3H2 → CH3 OH+ H2 O (CO2 to methanol)
(8)
nCH3 OH→ Cn H2n + nH2 O (MTO)
(9)
As a result, one of the major issues for the selective formation of C=2 − C=4 from carbon dioxide hydrogenation is to restrain carbon monoxide formation. Fig. 6e, f displays the simultaneous effect of temperature and SV on carbon monoxide selectivity. The CO selectivity decreases slightly with increasing SV. It has been also found that the CO selectivity has dropped from 86% to 16% at a reaction temperature of about 500 to 300 °C.
4. Conclusion The modeling and optimization of the direct conversion of CO2 into light olefins (C=2 − C=4 ) on a hybrid CuCe/SAPO-34 catalyst were accomplished, applying response surface methodology. Various characterization techniques have shown that the hybrid catalyst can improve the process of methanol production and the conversion of methanol to olefins. Temperature and SV were the control variables. The high temperature promotes the conversion of CO2 and CO selectivity, but has the contrary influence on the selectivity of olefins. In other words, olefin selectivity attains its optimum at intermediate temperature. A high olefin selectivity of 70.4% has been obtained on CuCe/SAPO-34 at H2/CO2 =3, 10 h, 382.46 °C, 17.33 L/g.h and 20 bar. The operating conditions of a multiple optimizations of the olefins and CO selectivity and CO2 conversion were obtained as a recommendation for the CO2 hydrogenation process. The respective maximum values of 61.83 and 13.15% for olefin selectivity and CO2 conversion, and the minimum of 57.11% for CO selectivity were achieved for optimum operating variables: T = 396.26 °C and space velocity = 5.80 L/g.h.
3.3. Optimization The CCD has been employed to establish the optimal conditions for reaching the maximum selectivity level for light olefins [49,67,68] in the present CO2 hydrogenation process. In single-response optimization, the Nelder-Mead Simplex method has been used to determine the optimum conditions in which each response variable achieved a maximum or minimum value [69–72]. The range of choice factors used is as follows: 300 °C ≤ Temperature ≤ 500 °C ; 2 L/g.h ≤ Space velocity ≤ 20 L/g.h For multi-responses optimization, temperature and space velocity are used to maximize olefin selectivity and CO2 conversion and to minimize CO selectivity at the same time. We define the composite desirability function (D), which ranges from zero outside the limits to one at the target. The numerical optimization discovers a point that maximizes the desirability function [69]. Table 5 shows an optimization scenario with one or more objective functions. For example, by maximizing olefin selectivity, the resulting RSM can determine the operating condition (T = 382.46 °C, SV = 17.33 L/g.h) that yields a maximum olefin. For multiple optimizations, light olefins are generally the products of interest, while the by-product, such as CO, is preferably produced in a minimal amount. For the hydrogenation of CO2 with a CuCe/SAPO-34 catalyst in a fixed-bed reactor at T = 396.26 °C,
Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:
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Acknowledgements
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Contents lists available at ScienceDirect
Journal of CO2 Utilization journal homepage: www.elsevier.com/locate/jcou
CO2 hydrogenation to light olefins over Cu-CeO2/SAPO-34 catalysts: Product distribution and optimization ⁎
Mehdi Sedighia,b, , Majid Mohammadic a
Division of Energy Systems, Department of Chemical Engineering, University of Qom, Qom, Iran Center of Environmental Research, University of Qom, Qom, Iran c Department of Energy Engineering, Faculty of Science, Qom University of Technology, Qom, Iran b
A R T I C LE I N FO
A B S T R A C T
Keywords: Carbon dioxide Hydrogenation CuCe/SAPO-34 catalyst Light olefins Optimization
The direct conversion of carbon dioxide into hydrocarbons is a very desirable but difficult approach for achieving lower value-added olefins with minimal CO selectivity. In this effort, we report the direct conversion of CO2 into light olefins on a Cu/CeO2 hybrid catalyst mixed with SAPO-34 zeolite. The samples are characterized by N2 sorption, XRD, TEM, SEM, NH3-TPD and H2 -TPR. The results showed that the acidity of modified zeolite had decreased. The response surface methodology has been used to optimize the operating parameters (temperature and space velocity (SV)) of process. A high olefin selectivity of 70.4% has been obtained on CuCe/SAPO-34 at H2/CO2 =3, 10 h, 382.46 °C, 17.33 L/g.h and 20 bar. The optimum operating conditions for multiple responses have also been achieved. The optimal values are T = 396.26 °C and SV = 5.80 L/g.h. Under these conditions, the predicted olefin and CO selectivity and CO2 conversion are 61.83%, 57.11% and 13.15%, respectively. Multiple optimization outputs are outstanding for obtaining the suitable operating conditions.
1. Introduction Human action is the key reason of ecosystem change. Individuals burn fossil fuels and convert woodland into farmland. At the outset of the Industrial Revolution, people were burning more and more fossil fuels such as natural gas, petroleum and coal [1–3]. This phenomenon produces carbon dioxide. CO2 is the major source of man-made environmental change. It remains in the atmosphere for too long. Carbon dioxide is an accessible source of renewable carbon with the advantage of being non-toxic, sufficient as well as practical [4–6]. The utilization of CO2 as a substance for synthetic chemicals [7–19] should be a sustainable solution. The conversion of carbon dioxide into light olefins is a potential solution to efficiently use of CO2 as a renewable resource. Light olefins (C=2 − C=4 ) are essential building blocks for the chemical market [20,21]. There are two main methods for the formation of light olefins from CO2. (1) In general, modified Fischer-Tropsch synthesis (FTS) catalysts are utilized to hydrogenate CO2 for the synthesis of hydrocarbons consisting of two sequential reactions: the reverse water gas shift (RWGS) reaction to provide carbon monoxide, and then by hydrogenation of carbon monoxide to HCs (FTS) [22–26], (2) Conversion of CO2 into methanol and from methanol to olefins (MTO) [27–31]. Although numerous catalysts were widely investigated and
⁎
established on the FTS pathway [22–26], there was no industrial usage for such a method due to the low C2–C4 olefin selectivity and the formation of a variety of HCs, resulting in extra costs for the separation procedure. Alternatively, the production of light olefins continuous to be systematically commercialized by the MTO method [32,33] since this process has high selectivity for C2–C4 olefins (≈ 80%) as well as the small distribution of other HCs. The catalytic hydrogenation of CO2 is a novel method to solve the difficulties of excessive CO2 emissions as well as energy shortages, as Cu-based catalysts are used on a large scale. It is remarkable that the Cu-based catalysts supported on CeO2 attracted attention because of their superior catalytic performance [34–38]. CeO2 is among the most significant oxides of heterogeneous catalysis because of its substantial redox ability [35,39–42]. One of the major problems of all catalysts used in the methanol production is the yield of methanol, which is kinetically restricted at low temperatures as well as thermodynamically limited at high temperatures. To solve this problem, one of the best options is to convert methanol in situ to other valuable products such as olefins. This method has a more economical and thermodynamic benefit over a two-step method (indirect conversion) owing to alleviation of the thermodynamic limitation applied to methanol synthesis, which can change
Corresponding author at: Division of Energy Systems, Department of Chemical Engineering, University of Qom, Qom, Iran. E-mail addresses: [email protected], [email protected] (M. Sedighi).
https://doi.org/10.1016/j.jcou.2019.10.002 Received 29 June 2019; Received in revised form 23 September 2019; Accepted 1 October 2019 2212-9820/ © 2019 Elsevier Ltd. All rights reserved.
Please cite this article as: Mehdi Sedighi and Majid Mohammadi, Journal of CO₂ Utilization, https://doi.org/10.1016/j.jcou.2019.10.002
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Fig. 1. Schematic diagram of the experimental setup for an olefin production process.
2.1.3. Preparation CuCe/SAPO-34 Crystalline CuCe/SAPO-34 has been synthesized by physically coating process [53]. Initially, a specific quantity of binder (alkaline silica sol) was diluted by deionized water. The outside surface of SAPO34 powder has been covered with Cu/CeO2 (20–40 mesh) (by the mass ratio of Cu/CeO2: SAPO-34 = 1: 1). The samples were further calcined at 823 K for 4 h.
the equilibrium towards higher CO2 conversion [30]. SAPO-34, among the most favorable identified catalysts in MTO method with particularly high carbon selectivity [43–47] of about 90% to C2–C4 olefins [32] and its modified versions are employed in the industrialized UOP/Hydro MTO method. SAPO-34, with a CHA framework as well as small pore openings (≈ 3.8 Å), includes an excellent olefin yield in the MTO process and may very well be the ideal option for this system. In this paper, we establish a direct as well as selective hydrogenation of CO2 to light olefins on a hybrid catalyst, combining methanol synthesis and the conversion of “methanol to olefins”. This unique design could reduce the thermodynamic restrictions of methanol production by consuming methanol in situ and shifting equilibrium. To achieve methodical experimental data studying a wide variety of operating factors, RSM has been employed as an organized experimental design approach, and semi-mechanistic models were developed based on the results.
2.2. Catalyst characterization XRD patterns were documented on a Bruker D8 Advance instrument with Cu Kα1 radiation. TEM has been recorded on a JEOL, JEM-2200FS electron microscope. The morphology of the catalysts has been identified by a SEM, AIS2100 (Seron Technology, South Korea). The BET surface area has been measured with N2 adsorption at −196 °C using a Quantachrome ChemBET-3000 instrument. The H2-TPR of samples were recorded in a Baidewo MFTP3060 multifunction catalyst analysis system (Xiamen, China). For H2-TPR, the sample has been pretreated with argon at 350 °C for 4 h and then cooled. The sample was then reduced by a reducing gas (50 mL/min) composed of 10% H2/Ar heated from 50 °C to 600 °C at a rate of 10 K/min. The amount of acid has been studied on a Micromeritics 2000 adsorption equipment applying NH3TPD.
2. Experimental section 2.1. Catalyst synthesis 2.1.1. Preparation of SAPO-34 The crystalline SAPO-34 has been hydrothermally synthesized using TEAOH as the template. The sources of Al, Si and P were aluminum isopropoxide (AIP, Merck), Silicic acid (SiO2, Merck) and phosphoric acid (85 wt.% H3PO4, Merck), respectively. The gel molar composition was 1Al2O3:1P2O5:0.6SiO2:1TEAOH, 50H2O. The mixture was then added to a 100 mL Teflon-lined stainless steel autoclave. The autoclave was put in an oven at 453 K for 24 h. As-synthesized product was then dried and calcined in air. The complete description of SAPO-34 synthesis is included in our previous work [46–52].
2.3. Catalytic activity test The reaction has been assessed in a stainless steel fixed-bed reactor with the internal diameter of 1.51 cm and length of 45 cm. charged with 2 g of catalyst sample. The catalyst has been pretreated by heating at 450 °C for one hour in pure Ar (130 mL/min) after which a reactive gas mixture with a H2/CO2/N2 ratio of 3:1:1 and a pressure of 20 bar were provided into the reactor. The activity studies were performed at various temperatures between 300 and 500 °C and at a gas SV between 2–20 L/g.h. An online gas chromatography (Varian Chrompack CP3800) equipped with a TCD and a FID detector were used to analyze the products. Schematic diagram of the experimental setup used for olefin production is shown in Fig.1. The conversion of carbon dioxide, selectivity of carbon monoxide and olefins selectivity (C=2 − C=4 ) in hydrocarbons are defined as follows:
2.1.2. Preparation of Cu/CeO2 CeO2 supported Cu catalyst has been synthesized using a depositionprecipitation process. Simply, Ce(NO3)3.6H2O was put into a solution of oxalate at 0.15 mol/L with vigorous stirring for 2 h at 343 K and then aged for 2 h. The precipitate was then washed several times, dried at 353 K for 10 h and calcined at 773 K for 6 h. Copper samples deposited on CeO2 supports (25 wt.% Cu) were prepared using the appropriate amount of Cu(NO3)2.3H2O as precursor and oxalate as precipitant. The as-synthesized samples were calcined at 773 K for 5 h. 2
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Table 2 Variables presented in coded form (P=20 bar, H2/CO2 = 3:1, time on stream=10 h). Variables
Symbols
Temperature (°C) Space velocity (L/g.h)
X1 X2
Levels -α
−1
0
+1
+α
300 2
329.29 4.64
400 11
470.71 17.36
500 20
Table 3 Experimental runs for CO2 hydrogenation process (P=20 bar, H2/CO2 = 3:1, time on stream=10 h). Run
Fig. 2. XRD patterns of (a) CeO2; (b) Cu/CeO2; (c) SAPO-34; (d) CuCe/SAPO34.
1 2 3 4 5 6 7 8 9 10 11
Table 1 Textural properties of fresh samples. Sample
SBET (m2 g−1)
Vpore (cm3 g−1)
Average pore diameter (nm)
Crystallinity (%)
Cu/CeO2 SAPO-34 CuCe/SAPO-34
62 482 317
0.16 0.31 0.24
12.65 0.48 6.38
89 91 85
CO2 conversion =
CO selectivity =
CO2inlet − CO2outlet × 100% CO2inlet
CO outlet × 100% CO2inlet − CO2outlet
Variables
Responses
X1: T (°C)
X2: SV (L/g.h)
Solefin (%)
CCO2 (%)
SCO (%)
500.00 400.00 400.00 400.00 470.71 470.71 400.00 300.00 329.29 329.29 400.00
11.00 11.00 2.00 11.00 17.36 4.64 20.00 11.00 17.36 4.64 11.00
15.41 65.55 59.47 65.84 34.76 29.66 69.42 41.52 53.81 44.91 64.75
20.80 11.83 15.31 11.68 16.07 19.22 8.53 4.76 3.72 6.84 11.78
82.51 55.52 62.28 55.46 70.12 77.2 50.16 28.85 24.68 32.45 55.55
Solefin: olefins selectivity; CCO2: CO2 conversion; SCO: CO selectivity; T: Temperature; SV: Space Velocity.
(1)
Olefin selectivity = (2)
nCn Hmoutlet × 100% CO2inlet − CO2outlet − CO outlet
Fig. 3. Structures of catalysts, (A) SEM image of SAPO-34, (B) TEM image of Cu/CeO2, (C) NH3-TPD curve, (D) H2-TPR profile. 3
(3)
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smaller ionic radius than Ce4+ are included into CeO2 lattice [35,54]. The XRD diffraction pattern of the samples SAPO-34 and CuCe/SAPO34 shows significant peaks at 9.6°, 13.7°, 16.2°, 20.5° and 30.8° [46,48,49,55]. In addition, the first sample shows some additional peaks at 35.8°, 38.9°, 27.9° and 47.6°, which are CuO and CeO2 diffraction peaks. The peak intensities of the SAPO-34 decreased after the introduction of CuO/CeO2, which means that the crystallinity of SAPO34 reduced (Table 1). The decrease of peak intensities may be due to mixing with Cu/CeO2. To calculate the relative crystallinity, the addition of the intensities of the sample is divided by the addition of the reference intensities. The pore volume and the specific surface area of all catalysts are presented in Table 1. SAPO-34 had a microporous structure with a large specific surface area (482 m2) and almost no mesopores. High surface area is advantageous for subjecting additional active sites and multiple reactions mass transfer, thereby supporting catalytic performance. Bifunctional catalysts have a much larger surface area compared to Cu/CeO2 and contain both mesopores and micropores. Fig. 3 shows some structural characteristics of the samples. The selected SEM image of SAPO-34 catalyst shows a typical cubic-like rhombohedral morphology (identical to natural chabazite). The typical size of the sample is about 1.5 μm. The average Cu/CeO2 particle size estimated with TEM has been about 20 nm with a narrow distribution. The acidity of SAPO-34 is characterized using NH3-TPD. The desorption curve displays two typical peaks corresponding to the weak (desorption peaks at 120–260 °C) as well as the strong acid sites (desorption peaks at 320–480 °C). The strong acid sites are mostly considered to be directly relevant to the olefin production. Modified SAPO34 shows low acidity compared to that of SAPO-34. Cu species are believed to be the active site for the synthesis of methanol from carbon dioxide and hydrogen. An H2-TPR technique has
Table 4 Analysis of variance (ANOVA) for the fitted models. Source
DF
a
Sum of Squares
Mean square
F-value
p-value
612.78 13.16 21.72 0.32
46.57
0.0003
68.15
0.0145
89.59
< 0.0001
203.48
0.0049
49.08
0.0003
11592.31
< 0.0001
2
For olefins selectivity (R = 0.97). Model 5 3063.88 Residual 5 65.80 Lack of fit 3 65.16 Pure error 2 0.64 Total 10 3129.68 For CO2 conversion (R2 = 0.98). Model 5 313.26 Residual 5 3.50 Lack of fit 3 3.49 Pure error 2 0.011 Total 10 316.76 For CO selectivity (R2 = 0.98). Model 5 3584.56 Residual 5 73.04 Lack of fit 3 73.03 Pure error 2 0.0042 Total 10 3657.60 a
62.65 0.70 1.16 0.0057
716.91 14.61 24.34 0.0021
DF: Degree of freedom.
3. Results and discussion 3.1. Catalyst characterization The XRD patterns of the samples are presented in Fig.2. The peaks centered at 27.9°, 32.97°, 47.6°, 56.4° and 59.0° are assigned to the CeO2 structure. It could clearly be found that the peaks of the CuO phase are observed after the introduction of copper ions. In addition, the CeO2 peaks become wider, indicating that copper ions with a
Fig. 4. Diagnostics plot predicted versus actual for (a) olefins selectivity, (b) CO2 conversion, and (c) CO selectivity. 4
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Fig. 5. Perturbation plots for (a) olefins selectivity, (b) CO2 conversion, and (c) CO selectivity.
CO2 conversion and CO selectivity imply that the models are significant. A low P-value (< 0.05) indicates that the models were highly significant and can be used to predict the response functions. The Rsquared statistics has been also examined for the percentage variability of the optimization parameter that is outlined by the model. Therefore, R2 is 0.97, 0.98, and 0.98 for Eqs. (4)–(6) indicate an effective match for experimental data and predicted values. The predicted and experimental values of olefins selectivity, CO2 conversion and CO selectivity are shown in Figs. 4(a)–(c), respectively. These figures showed that the models agreed well with the experimental data.
been performed to assess Cu/CeO2 reducibility. These reduction peaks correspond to diff ;erent reduction processes of CuO species. For bare CeO2 samples, peaks below 600 °C may be related to the reduction of surface oxygen, subsurface oxygen and surface Ce4+ species [56,57]. The reduction temperatures of Cu/CeO2 samples are lower than those of pure CeO2, due to the interaction between the support and the copper species[39]. Two main reduction peaks (α and β) are attributed to the reduction of well dispersed CuOx species that interact highly with ceria. This is a good feature of the catalyst activity criteria[58]. 3.2. Design of experiment
3.2.1. Perturbation plots The perturbation plot reflects the evolution of the response as each factor moves away from the chosen reference point and other factors are kept constant. In Fig. 5a–c, the curvature is most evident in temperature. These show that olefin selectivity, CO2 conversion, and CO selectivity are more temperature-sensitive than SV. Fig. 5a showed that the selectivity for the highest olefins near the temperature reference point could be achieved as it increases with SV. Fig. 5b shows that both factors have a considerable influence on CO2 conversion. However, the conversion of carbon dioxide decreases with SV as it increases with increasing temperature. Fig. 5c shows that the influence of SV is less important than temperature.
The Response Surface Methodology [59–63] has been applied in this analysis for the experimental design of the CO2 hydrogenation process. Two independent variables were used in specified amounts and coded as shown in Table 2. Two parameters with a total of 11 runs (Table 3) were presented by RSM/CCD using the statistical expert [64]. The responses, Y1, Y2, and Y3 analyzed by response surface design using the quadratic equation are expressed as follows: (Y1) Solefin (%)= -580.486 + 3.254X1 +2.739X2 -2.34E-003X1X2 -4.18E-003X12-0.048X22 (4) (Y2) CCO2 (%)= -9.673 + 0.038X1 -0.226X2 -1.88E-005X1X2 +5.73E005X12 -3.53E-003X22 (5) (Y3) SCO (%)= -91.858 + 0.469X1 -0.317X2 +3.83E-004X1X2 -2.25E004X12 -0.021X22 (6)
3.2.2. Binary effects of parameters on the response Fig. 6 demonstrates the 3D response plots and 2D contour plots found from the outcomes of the olefin selectivity, CO2 conversion, and CO selectivity with temperature and SV variations. Fig. 6a, b shows the
Table 4 shows the result of a statistical analysis of variance (ANOVA). The F-value of 46.57, 89.59, and 49.08 for olefins selectivity, 5
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Fig. 6. 3D response surfaces and 2D contour lines for olefins selectivity (C=2 − C=4 ) , CO2 conversion, and CO selectivity as functions of temperature and space velocity (P=20 bar, H2/CO2 = 3:1, time on stream=10 h).
decreased slightly with raising SV. Two parallel reactions, CO2 to methanol as well as RWGS, appear concurrently throughout the carbon dioxide hydrogenation method (Eqs. (7) and (8)). The RWGS reaction is preferred at an elevated temperature, because it is an endothermic phenomenon [5,27,65,66]. In the meantime, kinetics are preferred under the methanol production conditions for the hydrogenation of CO2. The process temperature is normally relatively low (200 − 300 °C) over methanol production catalysts. Although the coupling with the MTO procedure (Eq. (9)) can
mutual consequence of temperature and SV on the selectivity of light olefins (C=2 − C=4 ) . As the temperature increased from 300 to 380 °C, the selectivity for olefins increased from 27% to 70%, signifying the success of developed catalyst in selective hydrogenation of CO2. As the same time, the percentage selectivity of the olefins has been first increased with increasing SV and reached a maximum, then lowered. Fig. 6c, d reveals the effect of temperature and SV on the conversion of CO2. As these figures show, CO2 conversion has increased dramatically with temperature. It has also been found that the CO2 conversion 6
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Table 5 Result of the final optimal point in the single and multiple optimization (P=20 bar, H2/CO2 = 3:1, time on stream=10 h). Objective
Variables
Responses (Model)
T (°C)
SV (L/g.h)
Solefin (%)
Responses (Exp)
CCO2 (%)
SCO (%)
Solefin (%)
CCO2 (%)
SCO (%)
̶
71.18
̶
̶
25.11
̶
Single
Max Solefin
382.46
17.33
70.44
̶
Single
Max CCO2
500.00
2.00
̶
23.25
̶
̶
Single
Min SCO
300.00
20.00
̶
̶
16.19
̶
̶
17.27
Multiple
Max Solefin ; Max CCO2 ; Min SCO
396.26
5.80
61.83
13.15
57.11
63.10
15.23
56.84
Table 6 The comparison between experimental data and prediction. Variables
Solefin (%)
CCO2 (%)
SCO (%)
SCH4 (%)
SC2-C4 (%)
SC5+ (%)
T (°C)
SV (L/g.h)
Model
Exp
RMSE
Model
Exp
RMSE
Model
Exp
RMSE
Exp
Exp
Exp
397.52 496.64 363.80 458.08
12.83 11.30 18.63 16.73
68.15 16.85 68.85 47.91
67 18.11 69.15 45.86
1.58
10.97 20.30 6.23 14.92
11.33 20 8.15 12.82
1.29
53.45 81.45 38.38 67.52
55.15 80.28 40.97 65.77
1.68
3.18 21.54 2.47 9.55
26.14 51.73 24.44 37.15
3.68 8.62 3.94 7.44
SV = 5.80 L/g.h, the selectivity to olefins (61.83%), CO (57.11%), and the conversion of CO2 (13.15%) can be obtained accordingly. An experiment has been conducted to validate the optimal conditions proposed by the model. Table 5 demonstrates that the results of the verification experiment are in excellent agreement with the expected values derived from the fitted models. Table 6 also shows the comparison between the experimental data and the predictions of RSM. The RMSE values between the experimental data and the predictions are all less than 2, showing their relative accuracy in the modeling system. In addition, experimental data for other hydrocarbons (CH4, C2-C4 paraffins and C5+) were mentioned in Table 6.
derive the carbon dioxide conversion, the zeolite is not effective at such a low temperature for the CeC coupling reaction. The mismatch of their reaction temperatures leads to the formation of a considerable level of CO.
CO2 + H2 ↔ CO+ H2 O (RWGS)
(7)
CO2 + 3H2 → CH3 OH+ H2 O (CO2 to methanol)
(8)
nCH3 OH→ Cn H2n + nH2 O (MTO)
(9)
As a result, one of the major issues for the selective formation of C=2 − C=4 from carbon dioxide hydrogenation is to restrain carbon monoxide formation. Fig. 6e, f displays the simultaneous effect of temperature and SV on carbon monoxide selectivity. The CO selectivity decreases slightly with increasing SV. It has been also found that the CO selectivity has dropped from 86% to 16% at a reaction temperature of about 500 to 300 °C.
4. Conclusion The modeling and optimization of the direct conversion of CO2 into light olefins (C=2 − C=4 ) on a hybrid CuCe/SAPO-34 catalyst were accomplished, applying response surface methodology. Various characterization techniques have shown that the hybrid catalyst can improve the process of methanol production and the conversion of methanol to olefins. Temperature and SV were the control variables. The high temperature promotes the conversion of CO2 and CO selectivity, but has the contrary influence on the selectivity of olefins. In other words, olefin selectivity attains its optimum at intermediate temperature. A high olefin selectivity of 70.4% has been obtained on CuCe/SAPO-34 at H2/CO2 =3, 10 h, 382.46 °C, 17.33 L/g.h and 20 bar. The operating conditions of a multiple optimizations of the olefins and CO selectivity and CO2 conversion were obtained as a recommendation for the CO2 hydrogenation process. The respective maximum values of 61.83 and 13.15% for olefin selectivity and CO2 conversion, and the minimum of 57.11% for CO selectivity were achieved for optimum operating variables: T = 396.26 °C and space velocity = 5.80 L/g.h.
3.3. Optimization The CCD has been employed to establish the optimal conditions for reaching the maximum selectivity level for light olefins [49,67,68] in the present CO2 hydrogenation process. In single-response optimization, the Nelder-Mead Simplex method has been used to determine the optimum conditions in which each response variable achieved a maximum or minimum value [69–72]. The range of choice factors used is as follows: 300 °C ≤ Temperature ≤ 500 °C ; 2 L/g.h ≤ Space velocity ≤ 20 L/g.h For multi-responses optimization, temperature and space velocity are used to maximize olefin selectivity and CO2 conversion and to minimize CO selectivity at the same time. We define the composite desirability function (D), which ranges from zero outside the limits to one at the target. The numerical optimization discovers a point that maximizes the desirability function [69]. Table 5 shows an optimization scenario with one or more objective functions. For example, by maximizing olefin selectivity, the resulting RSM can determine the operating condition (T = 382.46 °C, SV = 17.33 L/g.h) that yields a maximum olefin. For multiple optimizations, light olefins are generally the products of interest, while the by-product, such as CO, is preferably produced in a minimal amount. For the hydrogenation of CO2 with a CuCe/SAPO-34 catalyst in a fixed-bed reactor at T = 396.26 °C,
Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:
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Acknowledgements
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Journal of CO₂ Utilization xxx (xxxx) xxx–xxx
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