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Statistical approach on ethanol reforming Isabela Dancini-Pontes, Vanderly Janeiro, Fernando Alves Silva, Rodrigo Meneghetti Pontes, Marcos De Souza, and Nádia Refina Camargo Fernandes Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.8b00624 • Publication Date (Web): 25 Apr 2018 Downloaded from http://pubs.acs.org on April 26, 2018

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Statistical approach on ethanol reforming ISABELA DANCINI-PONTESa,*, VANDERLY JANEIROb, FERNANDO A. SILVAc, RODRIGO M. PONTESd, MARCOS DE SOUZAa, NÁDIA R. C. FERNANDESa a

Department of Chemical Engineering, State University of Maringá, Av. Colombo,

5790, 87020-900, Maringá, Brazil, b

Department of Statistics, State University of Maringá, Av. Colombo, 5790, 87020-

900, Maringá, Brazil, c

Department of Chemical Engineering, Federal Technological University of Paraná -

Campus Apucarana, Street Marcílio Dias, 635, 86812-460, Apucarana, Brazil, d

Department of Chemistry, State University of Maringá, Av. Colombo, 5790, 87020-

900, Maringá, Brazil,

KEYWORDS: Ethanol reforming; statistic study; reaction routes; hydrogen.

ABSTRACT: After about 30 years of intense ethanol steam reforming study, which were done for several researches in different countries, there are some consensuses: there are many parameters involved and many reactions occurred. So, this study aims to show that the results obtained for a better understanding of ethanol reforming usually is made through complex, time-consuming and expensive chemical techniques could also be obtained in a statistical study of a factorial model in an easier way. Based on previous studies of different researches, where active phase, temperature and relative compositions of reactants were established, a statistical study was carried out to 1 ACS Paragon Plus Environment

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evaluate the contribution of the active phase (Ni or Cu or both), O2/C2H5OH ratio and temperature. It was observed that Ni and Cu favor the reaction course of the ethanol reform, reducing the occurrence of parallel reactions and by-products formation. The increase of the temperature acted in the same direction, favoring the route of ethanol reform, specifically, the reforming of the methane from previous stages. The presence of oxygen significantly influenced some parallel reactions, such as the partial oxidation of ethanol, the ethylene formation and the increase of the CH4 flow. Thus, the results obtained in this work allowed the production of a scheme of reactionary routes like those in the literature which makes valid the statistical approach for ethanol reforming.

1.

INTRODUCTION

Political and socioeconomic problems caused by environmental impacts from polluting and non-renewable energy sources have aroused greater interest in alternative energy sources. One fuel that can help meet this need is hydrogen, but for hydrogen to really be a clean renewable fuel, its production line needs to have such characteristics. Ethanol reforming is an alternative hydrogen production process that presents these requirements. However, ethanol reforming is a highly complex reaction, and although there is much research on this technology, data are rarely merged and treated as interdependent sets, as in an experimental planning followed by statistical treatment. Several catalysts were formulated and tested for the optimization of the ethanol reform, as well as several studies were carried out with the purpose of defining the best operating conditions, varying the temperature and evaluating reactions under oxidative atmosphere. The active phase is commonly formed by transition metals, such as Rh, Ni, Pd, Pt, Co, Cu, Zn, Ir and Ru 1–4. Chen et al. and Basagiannis et al. 1,5 state that, among the metals mentioned above, Ni is the most active in H2 production. Frusteri et al.

2

compared the metals Pt, Pd and Co and concluded that Ni and Rh are the ones that 2 ACS Paragon Plus Environment

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present the best selectivity in H2 and CO2. Moreover, Ni favors a greater conversion of CH4 and CO 6, as it facilitates the breakdown of the C-C bond 7,8 and does not suffer CO poisoning 6. However, in spite of these advantages, Ni favors the formation of coke

9,10

and to avoid coke deactivation, some studies indicate the co-participation of Cu in the presence of Ni as responsible for the decrease of coke and CH4 8,9. Among the supports studied for the steam or oxidative reforming of ethanol, the support that presents high mobility of oxygen atoms and hydroxyls is CeO2

11

. The

mobility of oxygen or hydroxyls is important, because it governs the stability of the catalyst activity and the conversion of CO and methyl groups to CO2 12,13. Ethanol reforming systems are highly complex, due to the several reactional routes that can be taken, in series and/or in parallel, depending on the applied variables. The influence of the several elements that compose a catalyst, as well as of the reactional parameters about the ethanol reforming process is already known right now, but this information was obtained, in the most part, through complex chemical techniques that demand time and resources not always available. Therefore, this work aims to understand, individually and jointly, the influence of the active phase, Cu and Ni supported in CeO2 and parameters of temperature and oxygen concentration, through a simple statistical planning.

2.

EXPERIMENTAL SECTION

2.1. Preparation of catalysts The catalysts were impregnated in commercial CeO2, Sigma-Aldrich. Before impregnation process, CeO2 was calcined at programmed temperature for 0.5 h at 100 °C, 1 h at 200 °C and 5 h at 800 °C. The three catalysts were synthesized by wet

3 ACS Paragon Plus Environment

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impregnation, one impregnated with copper nitrate only, one impregnated with nickel nitrate and another with simultaneous impregnation of these two nitrates. After impregnations, the precursors were dried at 100 °C for 24 h, then pressed and calcined for 0.5 h at 100 °C, 1 h at 200 °C and 5 h at 500 °C. Once ready, the catalyst granules were granulated in the range of 0.35 to 0.85 mm. The catalysts with copper after calcination contained 5% by mass of copper, based on some articles 14–16 and those with nickel contained 10% by mass of nickel, also based on some articles

15,17,18

. The

catalysts were named Cu-CeO2, Ni-CeO2 and CuNi-CeO2.

2.2. Catalytic Tests All catalytic tests were preceded by an in situ activation procedure with a reducing atmosphere composed of 60% N2 and 40% H2 volume by volume, at a flow rate of 50 cm3.min−1 and under thermal programming similar to the calcination of the catalysts, to 500 °C. In all tests performed, borosilicate glass was used to fill the reactor volume not filled by the catalyst. It was evaluated reactions in two different environmental: one named steam reforming (SR) where N2 was the carry gas and other named oxidative reforming(OSR) where synthetic air was the carry gas. For the tests performed by reforming with steam, N2 was used as carry gas with N2/C2H5OH molar ratio of 2.5. In the oxidative reforming tests, the gas used was synthetic air, with 80% N2 and 20% O2 by volume with O2/C2H5OH molar ratio of 0.5. Regardless of the gas used, the tests were conducted with the same molar flow rate of gas fed. The molar ratio H2O/C2H5OH was fixed for all tests in 10, the mass of the catalyst used was 1.5 g, and the volumetric space velocity was 70 dm3.(h.gcat)−1. Sixteen tests were performed at two different temperatures, 450 and 500 °C and for both kind of reforms, with steam (SR) and oxidative (OR).


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2.3.

Thermogravimetry (TG) and Differential Scanning Calorimeters (DSC)

These analyzes were performed with approximately 0.02 g of samples and carriers used under compressed air flow at 30 ml.min-1 and heating rate of 10 °C.min-1, from room temperature to 1000 °C and in sample port of alumina. The experiment was carried out on an equipment of the brand TA-Instruments (USA).

2.4. Statistical Study Four factors were selected to estimate the influence of experimental conditions on the production of the hydrogen and the several intermediates. Thus, a full 24 factorial design was used including: 1) the percentage of Cu; 2) the percentage of Ni; 3) The molar ratio between oxygen and ethanol (O2/C2H5OH); and the temperature. These variables were coded using Eq. (1). The physical and coded levels for each factor are presented in Table 1.

Xi =

− ( + )/2 ( − )/2

(1)

Where: Xi: coded variable (i: Cu, Ni, O2/C2H5OH, Temperature)

: uncoded variable, with high and low level (e.g.: 450 and 500 °C for temperature). To judge which factors to include in the regression model, we used Pareto plots. After the selection of terms, Eq. (2) 19 was used to fit the experimental data

y = β + β + β + є !

i = 1, 2, 3, 4 j = 1, 2, 3, 4

(2)

where β stands for the model coefficients and the summations indexes i and j refer to the factors. The rsm package form the R environment (Version 3.2.2) 20 was used for these 5 ACS Paragon Plus Environment

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regressions. The quality of the adjustments was verified by means of a residue analysis followed by the simulated envelope graph (hnp package). The terms not included in the regression were taken as replication and used for error estimates. In some cases, there was a need for mathematical transformation in the response variable to obtain a better fit of the model. The study was performed with 5% significance.

3.

RESULTS AND DISCUSSION

3.1. Catalytic Tests Throughout the catalytic tests, seven reaction products were monitored, namely, acetaldehyde, methane, carbon monoxide, ethene, acetone, carbon dioxide and hydrogen. Table 1 presents the flow rate obtained for each of these species in the various combination of factor levels, together with the conversion (total amount of ethanol consumed). Without the right statistical strategy, the joint analysis of the influence of these factors could be quite cumbersome. A factorial design analysis allows us to identify not only the main factors contributing to a given response, but also the relevant interactions among them. The basic idea is to capture the maximum information with the minimum of experiments. If this approach could be applied successfully to the development of catalyst for ethanol reforming, it would mean great resources saving. In the following discussion, we will present the relevant statistical analysis for each reaction product individually, and for the conversion of ethanol.

Acetaldehyde


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Figure 1a presents the Pareto plot for the main factors and all the interactions calculated from Table 1 for acetaldehyde. These plots allow us to identify the most relevant effects (from main factor or interactions) and to estimate the percentage of the variability explained when a given number of effects are considered. For instance, the first three most important effects depicted in Figure 1a can account for roughly 70% of the total variability in the data. Based on this, we opted to fit a linear model including these three effects, namely, the percentage of nickel, the molar ratio (oxygen/ethanol) and the interaction between the two factors, Eq. (3).

Acetaldehyde flow (mol. min56 )

= 1.332 x 1059 + 1.134 x 1059 (:; )

+ 9.448 x 105> ?:

@A E BA CD @C

+ 9.703 x 105> ?:; :

R2=0.8698

(3)

@A E BA CD @C

To verify the statistical significance of this model, we built a simulated envelope curve, Figure 1b. The conformity of the residuals to a straight line (within the limits marked by the upper and lower curves) shows that the model can successfully explain the experimental data. Also, since Cu and temperature are not included, we are left with a 22 full factorial in quadruplicate, from which a standard error of 1.973x10-5 mol/min can be estimated for the experimental measurements. All the terms included in Eq (3) are well above this value. The fitted coefficients in Eq. (3) are all positive, meaning that the acetaldehyde flow rate is increased as we increase both the percentage of Ni and the O2/C2H5OH molar ratio. From both, Eq. (3) and the Pareto plot (Figure 1a), the largest contribution to the acetaldehyde flow rate comes from the percentage of Ni. The next relevant feature is the fact that both the O2/C2H5OH molar ratio and the interaction between the O2/C2H5OH 7 ACS Paragon Plus Environment

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molar ratio and the percentage of Ni have similar contributions. This is something that could hardly be quantified without the help of factorial design analysis. Although copper is known for its ability to produce acetaldehyde

8,21

, its contribution

is less than half of that of the three most important effects and about the same of that of a three factors interaction term (Ni:Cu: O2/C2H5OH). This does not mean that copper has no dehydrogenation capacity, but for this system with Ni and oxygen its contribution is much reduced. Let us now interpret Eq. (3) based on the reaction mechanisms. There are some mechanism proposals that suggest the dehydrogenation of H-O and H-αC (carbon in the CH2 group) as the first steps of the ethanol reaction on a Ni surface

7,22,23

. This would

account the large contribution of Ni to Eq. (3). Presence of O2 in the atmosphere, favors the formation of radicals that can easily produce acetaldehyde, corroborating Sarathy et al.

24

work. Graschinsky et al.

25

, in a kinetic study, also verified that ethanol can be

oxidized to acetaldehyde in the presence of O2 in the atmosphere (Eq. 4). This explain the presence of the second term in Eq. (3).

GH I> JI + 1K2 JH → GIM GIJ + IH J

(4)

The positive contribution of the interaction between Ni and O2/C2H5OH ratio may be related to a possible Ni deactivation, which slow further reaction steps in which acetaldehyde is consumed, as follows. The presence of O2 in the atmosphere favors the formation of ethylene in parallel to the formation of acetaldehyde, according to the ethanol combustion routes suggested by Sarathy et al.

24

. Besides the formation of

ethene, the presence of O2 also favors the formation of CH4 (Eq. (7), to be presented in the sequence of the discussion).

NGH I9 → GO IP + QIH

(5)

GIP → G + QIP

(6) 8 ACS Paragon Plus Environment

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It is known that both ethylene and CHx components can be coke precursors through the ethylene polymerization routes and the dehydrogenation of CHx (Eq. 5 and 6), respectively

6,26–28

. Therefore, since Ni presents high deactivation by coke formation

with frequency 6,26, interaction of the presence of O2 with Ni may have further favored the formation of coke. This coke may deposit on Ni, so that it loses part of its activity for breaking C-C bonds. Thus, acetaldehyde consumption decreases and there is an increase in its flow rate. Coexistence of metallic Ni and O2 can also cause deactivation by oxidation of Ni to NiO. This oxidation would cause the same decrease in the consumption of acetaldehyde. Figure 1c shows the contour plot for Eq. (3) in terms of the coded variables. It is easy to see that the largest flow rate is observed when both factors (Ni and O2/C2H5OH) are at their higher levels (XNi =1 and XO2/C2H5OH =1).

CH4 Following a similar reasoning as that for acetaldehyde, we built the Pareto plot from the data of Table 1, Figure 2a. The most important factor is the O2/C2H5OH ratio, followed by the Ni percentage, the interaction between Ni percentage and O2/C2H5OH ratio and the interaction between Ni percentage and temperature, in that order. Based on this, we obtained Eq. (7):


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CH9 Flow (mol. min56 )

= 4.830 x 105>

− 1.287 x 105> (:; ) + 4.110 x 105> ?:

@A E BA CD @C

− 1.235 x 105> ?:; :

R2=0.9268

(7)

@A E BA CD @C

− 1.149 x 105> V:; :WXYZ [

The linearity of the envelope plot in Figure 2b confirms that this model can adequately describe the experimental data. Without including the percentage of Cu, we are left with a 23 factorial design in duplicate, from which a standard error of 4.119x10-6 can be estimated. All the factor included in Eq. (7) are comfortably above this limit and are statistically significant based on their p-values. Among all factors and interactions, the only factor that presented a positive coefficient was the O2/C2H5OH ratio factor, which is somewhat counterintuitive, since we could imagine CH4 being oxidized by larger amount of O2. A possible explanation for the increased production of CH4 due to the presence of O2 may be the decomposition of acetaldehyde (Eq. 8). Hung et al.

29

studied several metals and founded the same

effect in the production of CH4 by influence of the increase of O2 in the atmosphere. The explanation used in this study was also the increase of the acetaldehyde decomposition, in addition to the low reaction rate for methane oxidation. This is coherent with the results for acetaldehyde from the previous sections, i.e., with more acetaldehyde formed, there will also be a larger proportion of CH4 formed from its decomposition.

GIM GIJ → GI9 + COH

∆I^_ Hà =−14.4 kJ/mol

(8)


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Another possibility comes from the study by Matos et al.

30

and Rodriguez et al.,

31

which evaluated the ethylene hydrogenolysis-homologation reaction. These authors demonstrated that ethylene can be decomposed into CHx radical or CH4. As the presence of O2 favors the formation of ethene, there is a possibility that the increase of ethene in the system favors the formation of methane. The homologation reaction (combination of CH4 molecules for form heavier hydrocarbons in a homologous series) may be disfavored, which leads to the formation of methane and adsorbed carbon on the support surface (Eq. 9) 30. Eqs. (8) and (9) possibly make contributions to CH4, although with different weights.

GH I9 → GI9 + G

∆I^_ Hà = −127.3 kJ/mol

(9)

The negative contribution of Ni can be related to the reforming of methane, which is catalyzed by this metal according to the literature

6,29,32,33

. The negative contribution of

the interaction between Ni and O2/C2H5OH ratio may have the same reason discussed above. The possible deactivations of Ni can disfavor the C-C bond breakdown, so that it produces less CH4. This shows how informative the fitted model (Eq. 7) can be, as its terms may refer to different reaction steps and give us insights on the molecular events taking place throughout the entire process. The negative coefficient of the interaction between Ni and temperature may also be related to methane reforming, since the presence of Ni (as discussed above) and the increase of temperature, according some studies 33,34, favors a methane steam reforming, a highly endothermic reaction (Eq. 10).

GI9 + IH O → GJ + 3IH

∆I^_ Hà = 205.9 kJ/mol

(10)

Figure 2c shows the contour lines from the regression model adjusted for the CH4 flow rate, which reinforces the above-mentioned characteristics.


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CO Figure 3a depicts the Pareto graph for the CO flow. The O2/C2H5OH ratio has a much more pronounced effect than any other factor. It is possible to adjust a model based solely on the O2/C2H5OH ratio that satisfactorily describe the experimental data, but in this case a variable transformation is required, namely CO Flow ∗ = VCO Flow − 5H

CO Flow[ . The regression model becomes:

CO Flow (mol. min56 ) =

1

e43460934 − 32693983 ?:

− 0.000111

@A E BA CD @C

R2=0.9873

(11)

The linearity of simulated envelope plot granted the statistical significance of Eq. (11), Figure 3b. Moreover, the higher number of experimental runs than fitted parameters allows the estimation of a standard error of 992067. The coefficients in Eq. (11) are comfortably above this error and are significant according to their p-values. From Eq. (11), larger O2/C2H5OH ratios increase the CO flow rate. This behavior can be easily explained by the partial oxidation of the ethanol generating CO and H2 (Eq. 12)

GH I> JI + 1K2 JH → 2GJ + 3IH

∆I^_ Hà = 12.9 kJ/mol

(12)

In the absence of O2, the catalyst does not produce CO or produces only a small amount. This tendency to not produce CO in the absence of O2 can be explained by the mechanism suggested by some studies for the formation of acetate from acetaldehyde. In this mechanism the acetate dissociates directly into CO2 and CHx, with CHx being easily oxidized to CO2 due to the oxidative properties of the support 35–38.


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As discussed earlier, the presence of O2 in the atmosphere causes an increase in CH4 production. But if the mechanism above is considered, probably at least part of CH4 was produced by the mechanism proposed by Matos et al.

30

, which indicates methane

production from ethene. This may explain the production of CH4, despite its consumption by oxidation.

Ethylene Figure 4a presents the Pareto plot for ethylene flow. In this case, several effects have comparable contributions. Ni is the most important factor, followed by the interaction of Ni with the O2/C2H5OH ratio, the presence of Cu and the O2/C2H5OH ratio. The interaction between Cu and O2/C2H5OH ratio is also important, together with the interactions between the O2/C2H5OH ratio and temperature and that between Cu and Ni. Eq. (14) is the regression model obtained with the inclusion of all these terms.

Ethylene Flow (mol. min56 )

= 6.764 x 105> − 2.711 x 105> (:Bh ) − 3.544 x 105> (:; ) + 2.337 x 105> ?:

@A E BA CD @C

+ 2.046 x 105> (:Bh :; ) − 2.865 x 105> ?:; :

(13)

@A E BA CD @C

− 2.120 x 105> ?:Bh :

− 2.074 x 105> ?:

R2=0.9453

@A E BA CD @C

@A :WXYZ E BA CD @C


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The linearity of simulated envelope plot, Figure 4b, granted the statistical significance of Eq. (13). Moreover, since the interactions involving three and four factors were not included in the model, we have more experimental runs than the number of variables to fit and a standard error of 6.292x10-6 can be estimated. The coefficients of the terms in Eq. (13) are comfortably above this error and are significative according the respective p-values. Cu and Ni main factors showed negative coefficients, indicating that the presence of these factors made ethylene production difficult. Both Cu and Ni are considered the active phase that favor the production of acetaldehyde due to their ability to dehydrogenate ethanol

7,8

, which disfavor the production of ethylene and decreases its

flow rate. However, due to the positive sign of the interaction coefficient between Cu and Ni, it can be said that the interaction of these factors favors the formation of ethene. When we consider the CO2-TPD characterization data (Support Information), it becomes evident that the bimetallic catalyst has the one with the highest concentration of OH groups on the surface. OH groups are largely responsible for the production of ethylene

39,40

and they may be responsible for increasing the ethylene flow. Thus, a

significant increase of OH groups on the surface may have supplanted the dehydrogenating characteristic of the metals in question. The positive contribution of the O2/C2H5OH ratio may be in accordance with ethanol combustion works, which verifies the possibility of CH2CH2OH radical formation by hydrogen abstractions by OH radicals. With that radical formed, the decomposition of ethanol in OH and C2H4 happens rapidly at temperatures higher than 327 °C 41–44. Regarding the combination of the effect between Ni and O2/C2H5OH ratio having a negative coefficient, the coke formation deactivation mechanism discussed above can be suggested. The inactivity of the catalyst surface and the coating of the OH groups


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may hinder the formation of ethene. But there is another likely explanation. The same works

41–44

that suggest the mechanism of production of ethene in the presence of O2

presents another mechanism that would form acetaldehyde. Therefore, it is possible that when the catalyst has Ni, in the presence of O2, this mechanism of acetaldehyde production is favored in detriment of the mechanism of ethene formation. This can be confirmed by the opposite contribution of the coefficient of this interaction in the model equation for the acetaldehyde flow (Eq. 3). The interaction between Cu and O2/C2H5OH ratio may have the same explanation. Copper probably catalyzes the formation of precursor radicals of acetaldehyde and the abstraction of hydrogen atoms by O2 molecules. Thus, the conversion of ethanol to ethylene and its flow decrease. Interaction of the factors temperature and O2/C2H5OH ratio may be related to the increase in rate of other parallel reactions. Probably, the temperature increase in the presence of O2 hinders the exothermic reactions, the production of the precursor radial of the ethene, and the reactions of complete oxidation. In addition, the increase in temperature can facilitate endothermic reactions, such as the production of acetaldehyde and acetone. Thus, although the reaction of ethylene formation is also endothermic, the increase in temperature favors other parallel endothermic reactions, competing with the formation of ethene. Figure 4c shows the contour lines for all possible interactions.

Acetone


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Acetone Flow (mol. min56 )

= 1.455 x 1059 − 4.689 x 105> (:; )

− 4.211 x 105> ?:; :

R2=0.6181

(14)

@A E BA CD @C

Figure 5a presents the Pareto plot for acetone. The percentage of Ni and the interaction between percentage of Ni and the O2/C2H5OH ratio are prominent among the whole set of effects. Thus, we tried to fit the experimental data with a model including just these two terms, Eq. (15). Although the R2 value of 0.6181 is somewhat low, the linearity observed in the envelope plot, Figure 5b, shows that the model conforms reasonably well to the experimental data. Moreover, the higher number of experimental runs than fitted parameters allows the estimation of a standard error of 1.540x10-5. The coefficients in Eq. (14) are comfortably above this error and are significant according to their p-values. According to the mechanism suggested by Nishiguchi et al.

45

(Eq. 15), the

production of acetone is catalyzed by CeO2 support. However, Ni has characteristics that catalyze the breakage of the C-C bond in the acetaldehyde or its precursor radicals 7,8,21

, rather than using it in the production of acetone. This ability of Ni to catalyze the

breakdown of C-C bonding makes it a factor with the negative coefficient, as can be seen in Eq. (15), due to the competition for acetaldehyde that the presence of Ni generates.

2GH I> JI + IH O → GIM GJGIM + GJH + 4IH

∆I^_ Hà = 96.0 kJ/mol

(15)

The presence of Ni makes the interaction between Ni and O2/C2H5OH ratio of negative contribution. As previously suggested, probably the presence of Ni favored the formation of coke from the polymerization of ethylene. Since ethylene presents higher production in the presence of O2 and the interaction of these two factors causes formation of coke, which covers the surface of the catalyst. The mechanism proposed 16 ACS Paragon Plus Environment

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by Nishiguchi et al.

45

for the production of acetone involves oxygen atoms of the

support itself, the coating of the same prevents this reaction path. Figure 5c shows the interaction level curves between Ni and ratio O2/C2H5OH.

CO2 Figure 6a shows the Pareto plot for the CO2 flow rate. The O2/C2H5OH molar ratio is by far the largest effect, followed by the percentage of Ni and the Ni:O2/C2H5OH interaction. A model including these three terms was built, Eq. (16).

COH Flow(mol. min56 )

= 6.679 x 1059 + 4.049 x 1059 ?: − 1.331 x 1059 (:; )

− 1.013 x 1059 ?:; :

@A E BA CD @C

R2=0.9439

(16)

@A E BA CD @C

The envelope graph, Figure 6b, shows that the regression can describe the experimental data reasonably well. Moreover, the higher number of experimental runs than fitted parameters allows the estimation of a standard error of 3.082x10-5. The coefficients in Eq. (16) are comfortably above this error and are significant according to their p-values. The CO2 flow equation presented a positive coefficient for the ratio factor O2/C2H5OH. This can be easily explained by the complete oxidation of ethanol producing CO2 and H2O. In addition to this oxidation reaction, there is still the formation of CO2 as a byproduct of the acetone production, which is also favored by the presence of O2 in the atmosphere. Since the O2/C2H5OH ratio presents the largest effect on the Pareto graph (Figure 6a), we can conclude that the complete oxidation reaction of ethanol is the major responsible for CO2 formation. 17 ACS Paragon Plus Environment

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The Ni factor presented a negative coefficient, probably because the presence of Ni decreases the activation energy of reactions such as C-C bond breakdown and methane reforming that would compete with the complete oxidation reaction of ethanol. This does not prove a possible inability of Ni to catalyze the gas shift reaction. On the other hand, it indicates that the presence of Ni disfavors the oxidation reactions and favors the reactions that compose the ethanol reforming route. The interaction between Ni and O2/C2H5OH ratio appears again and with the sign of the negative coefficient and is probably related to deactivation, as follows. Whenever this interaction appears, some deactivation explains its performance in the reaction system. The production of CO2 is probably catalyzed by the support, in part by the production of acetone which also generates CO2 and partly because the support is probably a catalyst for the complete oxidation reaction of ethanol. When the support is coated by coke, the performance of the support is decreased or annulled, so there is a decrease in CO2 production. In Figure 6c, the level curves of the adjusted regression model for the CO2 flow are presented.

H2 Figure 7a shows the Pareto plot for hydrogen flow rate. The most important effect is the interaction between the O2/C2H5OH ratio and the temperature, followed by the main effect of temperature, the interaction between Ni and O2/C2H5OH ration and the main effect of the O2/C2H5OH ratio. To obtain a statistically significant fit, it was necessary to adjusted for the H2 flow (mol.min-1) transformed by HH Flow ∗ = (HH Flow)5H.


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HH Flow(mol. min56 )

= i1285117 − 391171 ?:

@A E BACD @C

− 526589 V:WXYZ [ + 579687 ?: + 412170 ?:; :

@A Ej BA CD @C

@A :WXYZ E BA CD @C

R2=0.7718

(17)

56/H

Figure 7b presents the simulated envelope graph, which shows that the model fits the data reasonably well. We have more experimental runs than the number of variables to fit and a standard error of 167008 can be estimated. The coefficients of the terms in Eq. (17) are comfortably above this error and are significative according the respective pvalues. By the Eq. (17), according to the Pareto graph (Figure 7a), the most important factor is the interaction between O2/C2H5OH ratio and temperature, followed by the main effect factor temperature, by the interaction between Ni and O2/C2H5OH ratio and the main effect factor ratio O2/C2H5OH, in that order. The interaction between O2/C2H5OH ratio and temperature was also significant to produce ethylene. Graschinsky et al. 34, in a thermodynamic study, stated that H2 flow is only influenced by the O2/C2H5OH ratio at temperatures above 477 °C, which confirms this interaction between O2/C2H5OH and temperature. For the ethylene flow, this interaction was suggested as an explanation for the increased activity of oxidations parallel reactions. The increase in temperature may have favored reactions that are part of the ethanol reforming route, disfavoring the oxidation reactions, including the consumption of coke by oxidation. According to Eq. (12), the partial oxidation reaction produces CO and H2. If the temperature variation favors other parallel reactions in the presence of O2, the amount of


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H2 provided by this reaction will decrease, causing a decrease in H2 formation. Since this same interaction can decrease the ethylene flow, the main influence of the interaction probably lies in the kind of radicals that start the mechanisms. To produce ethylene and acetaldehyde, the radicals must be distinct and in this case radicals that lead to the formation of acetaldehyde must have been favored. Sarathy et al.

24

, in their mechanism suggestion, indicate the formation of

acetaldehyde from the CH3CHOH radical, both by the influence of O2 and by the influence of the increase in temperature. In addition, they suggest that at high temperatures, acetaldehyde can decompose to CH3 radical and CO. As this mechanism is considered, the suggestion that this interaction explains the competition between the oxidation reactions and other reactions that are part of the reforming mechanism becomes probable.

GH I> JI + 1K2 JH → 2GJ + 3IH

∆I^_ Hà = 12.9 kJ/mol

(12)

The temperature factor suggests an increase in H2 flow with the increase in temperature, which agrees with the literature

46

. This can be explained by the reaction

∆H. Most of the reactions that produce H2 are endothermic reactions, such as ethanol dehydrogenation, acetone formation, methane reforming and partial oxidation of ethanol (Eq. 8, 15, 10 and 12, respectively). The interaction between Ni and O2/C2H5OH ratio, again, may be related to the deactivation of the catalyst, which hinders the reactions of H2 formation. In addition, this formed coke may have been consumed by CO2 formation, which would also compete with the partial oxidation, H2-supplying reaction. Regarding the O2/C2H5OH ratio factor, its positive influence must be related mainly to the partial oxidation of ethanol (Eq. 12), but also to the production of acetaldehyde and acetone, which are positively influenced by O2. However, it is worth noting that the 20 ACS Paragon Plus Environment

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ratio factor O2/C2H5OH is not the most important in Eq. (13). In addition, its performance favors the increase of H2 flow. Therefore, the oxidative reforming reaction of ethanol, under the conditions studied, does not have a negative influence H2 production. Graschinsky et al.

34

, as previously mentioned, stated that H2 flow is only

influenced by the O2/C2H5OH ratio at temperatures higher than 477 ° C, which confirms the low influence of this factor on H2 flow at 450 °C. Figure 7c shows the contour curves of the equation of the adjusted regression model for H2 flow.

Conversion Figure 8a presents the Pareto plot for conversion. The most important factor is the O2/C2H5OH ratio, followed by the interaction between Ni and O2/C2H5OH ratio and the interaction between O2/C2H5OH ratio and temperature. To get a statistically significant regression, we used the variable transformation Conversion∗ = Conversion6,n to obtain the fitted model of Eq. (18).

Conversion (%)

= i0.43567 + 0.27356 ?: − 0.04269 ?:; :

@A BA CD @C

@A E BA CD @C

E

R2=0.9764

(18)

,nH>

− 0.03419 V:; :WXYZ [j

Figure 8b presents the simulated envelope graph, which shows that the model fits the data reasonably well. We have more experimental runs than the number of variables to fit and a standard error of 0.01382 can be estimated. The coefficients of the terms in Eq. (17) are comfortably above this error and are significative according the respective pvalues. 21 ACS Paragon Plus Environment

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The factor O2/C2H5OH ratio was the only factor that presented a positive contribution. This is due to the oxidative reactions that add to the other reactions that occur in the absence of O2. In addition, the presence of O2 also favors the formation of various products of the tests performed. Thus, the presence of O2 presents only positive contributions in ethanol conversion. The interaction between Ni factors and O2/C2H5OH ratio appears again and with a negative contribution when the signals of the two factors coincide. This negative contribution to the conversion confirms the idea of deactivating the catalyst deactivation by two reasons: metal oxidation and coke formation. The interaction involving the Ni and temperature factors appeared only in the CH4 flow. Methane reforming agents appear in the negative coefficient conversion, again. This may indicate a decrease in the activation energy of Ni-catalyzed mechanisms. Thus, ethanol, which could easily be oxidized, would be adsorbed and consumed at a reaction rate that may still be lower than that of oxidation, favoring a decrease in ethanol conversion. In Figure 8c, the contour curves of the equation of the adjusted regression model for the conversion are presented. This illustrates the effects discussed for conversion.

3.2.

Thermogravimetric analysis (TG) and Differential Scanning Calorimeters

(DSC)

The thermogravimetry and Differential Scanning Calorimeters analyzes, in this study, can be used both to evaluate the coke production, which causes catalysts deactivation, and to identify mass gains by reoxidation of the support. Some studies indicate that the CeO2 support donates oxygen atoms to reactions involving oxidations, as is the case of


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the acetone production suggested in Equation (14)45 and acetate production suggested by some authors35–38. Steam reform catalysts performed on Ni-CeO2 show mass gain from 300 at 500 °C in Figure 9a, and in Figure 9b we observe an energy gain in the same mass gain temperature range. This may indicate that the oxygen atoms delivered during the catalytic test, which were not replaced during the tests, were replaced by the oxidative atmosphere of the analyzes of Figure 9. The factor temperature also had relevant importance in this mass gain, at lower temperatures, there was greater mass gain. This behavior may be related to Equation (18) concerning conversion. In it we find the interaction between the Ni and temperature factors with the negative coefficient, that is, in the presence of Ni (1) and the lower temperature (-1), we find an increase of the conversion, therefore, higher oxygen consumption of the structure of the catalyst. In samples submitted to oxidative steam reform and at 450 °C we observed a marked loss of mass accompanied by a marked increase in energy, characterizing an exothermic reaction. These characteristics can be attributed to the oxidation of coke, which also occurred in the test samples at 500 ° C, but in less quantity. The equation of ethylene flow (Eq. 13) shows the interaction between the temperature and O2/C2H5OH ratio factors with negative coefficient, indicating that when the test is oxidative steam reforming (1) and the temperature is 450 °C (-1) there is a higher formation of ethylene, probably the precursor of coke. In the catalysts from steam reform tests, the mass loss, probably due to coke oxidation, can only be noticed in the DSC between 450 and 500 ° C with a small energy gain when compared to the energy gain of the samples that underwent tests of oxidative steam reform. This refers to the interaction between the Ni and O2/C2H5OH ratio factors


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Page 24 of 51

previously discussed and which appeared in several regression models, which favors the deactivation of the catalyst by the formation of coke. Thermogravimetric and DSC analysis of the other catalysts can be found in Support Information.

3.3. Propose for a reaction path According to the statistical study with regression model equations adjusted for different products, the reaction Scheme 1 was constructed, validated by the literature data. It was observed that the ethanol can undergo dehydration to produce ethylene, as reported in several works in the literature 47–49. However, it was found that the ethylene flow can be significantly influenced by the presence of oxygen. In general, the presence of oxygen favors the abstraction of hydrogen atoms from the ethanol molecule, which makes more easy the formation of different radicals that can follow different routes, such as ethylene and acetaldehyde production, according to the suggested by Sarathy et al. 24. As shown in region A of Scheme 1, the ethylene production pathway arouses other reaction routes such as desorption of gaseous ethene. But while adsorbed, the radical that leads to ethylene can be polymerized, forming coke, as indicated in the literature 50. This coke formation due to ethylene polymerization can be explained by the strong interaction between Ni and O2/C2H5OH ratio factors found in the statistical study. The interaction between these factors indicates deactivation by coke due to the union of the known Ni deactivation by coke formation 49,51, with the increase of the ethylene flow in the presence of oxygen, as verified in this work. Thus, it can be suggested that the interaction between these two factors favors the polymerization of ethylene.


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In addition to desorption of ethylene and its polymerization, a relation between ethene and CH4 may be suggested. It was observed that the presence of oxygen favored the increase of the CH4 flow, this may be related to ethylene hydrogenolysis which produces CH4 and carbon adsorbed. It is known that the CeO2 support has mobility of the oxygen atoms of its structure [11,45,46,59] . Therefore, according to this characteristic of CeO2, there are some studies that suggest the dehydrogenation of acetaldehyde followed by oxidation, forming acetate, as shown by region C of Scheme 1. This acetate can be broken forming CO2 and CHx adsorbed which, due to the oxidizing characteristics of the support, can easily become CO2 37. Still taking into account the oxygen atom mobility in the structure of CeO2, there is a suggestion of an acetone formation mechanism, according to which, in order that two molecules of acetaldehyde react to form acetone, oxygen atoms in the structure of the support must participate in the reaction, as shown by region D of Scheme 145. This links the acetone formation, verified in the tests, to the oxidant characteristics of the support. According to the statistical study, Ni is an important factor in the formation of acetaldehyde, this may be linked both to its dehydrogenating capacity 29 and a possible favoring of desorption of acetaldehyde in the presence of Ni. But Ni is known to catalyze C-C bonds breakage

21

, therefore it is also responsible for favoring the

reactions that most commonly compose the set of reactions of the ethanol reform, such as the decomposition of acetaldehyde (region E of Scheme 1). The experimental result of this work corroborating this information is the influence of Ni on the decrease of the acetone flow rate, because probably Ni favors the breakdown of the acetaldehyde, necessary to acetone formation.


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In addition to the influence of Ni on the breakdown of C-C bonds, Ni has characteristics that favor methane reform, or methane consumption, as well as temperature increase

9,29

. The influence of these factors, Ni and temperature, on

methane reforming was clearly observed in the regression model adjusted for the CH4 flow, so that both Ni and the interaction between it and temperature favored CH4 consumption (region F of Scheme 1).

4.

CONCLUSION

Design of experiments and the related statistical tools for the construction and analysis of regression models allowed us, using only a few catalytic tests for four different catalysts, to extract information from our system in a much more economical way. From the experimental factors studied (Cu, Ni, temperature and O2/C2H5OH ratio) it was possible to structure a reaction path scheme to determine how each of these factors influence the production of each chemical species on it. For instance, copper was only significant in ethylene flow, hindering its production and favoring another reaction route. Nickel, on the other hand, presented importance in the flow of different products. It inhibited parallel reaction routes such as ethylene and acetone production and favored the methane reforming route. Following the equations of the adjusted regression models, the ability of Ni to catalyze reactions such as ethanol dehydrogenation, carbon bond breaking, and methane reforming can be visualized. Nickel possibly acted in the deactivation of the catalyst, favoring the formation of coke. The influence of temperature was observed in most of the equations as one of the interaction factors. It could be suggested that the increase in temperature favors the ethanol steam reforming route, as well as favors the reform of


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methane when combined with nickel. With respect to oxygen, the regression models suggest that the presence of O2 catalyzes the formation of radicals derived from abstractions of hydrogen atoms carried out by OH groups on the surface of the catalyst. In addition, the presence of O2 also showed significance in the production of ethylene, CH4 and when allied to Ni, caused catalyst deactivation. The formation of ethylene is intimately and directly linked to the amount of hydroxyl groups on the surface of the catalyst. Apart from the specific finding for the studied catalysts, one of the greatest contributions of this work is the approach to plan and analyze catalytic tests. This is the philosophy of design of experiments, i.e., to maximize useful information on the behavior of a given system with a minimum of experimental runs. This approach allowed us to suggest reaction routes that are coherent with our own experimental data and with literature reports, some of them based on complex and costly chemical techniques. Design of experiments, as the one used in the present work, can be used to systematically identify the main factors (catalysts types or experimental conditions) that controls the formation of every reaction intermediary throughout the path of hydrogen formation. The factors studied in this work are widely known in the research of ethanol reforming. However, studies describing their interdependence, as in the present work, are still rare, and this is a problem that can only be correctly solved with the right statistical tools. It is possible, with this knowledge, to tune these parameters in the right direction to increase the hydrogen yield or to decrease the formation of a given undesired reaction intermediary. In this way, the construction of ideal conditions to produce hydrogen becomes objective, organized and concise. This approach can, in principle, be applied to any other catalytic systems.


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AUTHOR INFORMATION Corresponding Author *Isabela Dancini-Pontes * e-mail: [email protected]; Author Contributions The manuscript was written through contributions of all authors. Isabela Dancini-Pontes‡, Vanderly Janeiro‡, Fernando Alves da Silva‡, Rodrigo Meneghetti Pontes‡, Marcos de Souza‡, Nádia Regina Camargo Fernandes‡ Funding Sources Coordenação de Aperfeiçoamento de Pessoal de Nível Superior– CAPES – Brazil.

ACKNOWLEDGEMENTS This work was supported by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior– CAPES – Brazil.

Supporting Information: • •

Table and Figure of CO2 Temperature-Programmed Desorption (CO2-TPD) Figures of Thermogravimetry and Differential Scanning Calorimeters analyzes of Cu-CeO2 and CuNi-CeO2 catalysts before and after catalytic tests.

REFERENCES (1)

Basagiannis, A. C.; Panagiotopoulou, P.; Verykios, X. E. Top. Catalisys 2008, 51, 2–12.

(2)

Frusteri, F.; Freni, S.; Spadaro, L.; Chiodo, V.; Bonura, G.; Donato, S.; Cavallaro, S. Catal. Commun. 2004, 5, 611–615.

(3)

Chen, H.; Yu, H.; Peng, F.; Wang, H.; Yang, J.; Pan, M. J. Catal. 2010, 269 (2), 281–290. 28 ACS Paragon Plus Environment

Page 29 of 51 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

(4)

Chen; Li-Chung; Lin; D., S. Appl. Catal. B Environ. 2014, 148–149, 509–519.

(5)

Chen, L.; Kai, C.; Choong, S.; Zhong, Z.; Huang, L.; Wang, Z.; Lin, J. Int. J. Hydrogen Energy 2012, 37, 16321–16332.

(6)

Lin, J.; Chen, L.; Kai, C.; Choong, S.; Zhong, Z.; Huang, L. Sci China Chem 2015, 58 (1), 60–78.

(7)

Gates, S. M.; Russell, J. N.; Yates, J. T. Surf. Sci. 1986, 171, 111–114.

(8)

Chen, L. C.; Lin, S. D. Appl. Catal. B Environ. 2014, 148–149, 509–519.

(9)

Saeki, T.; Ohkita, H.; Kakuta, N.; Mizushima, T. J. Ceram. Soc. Japan 2015, 123 (10), 955–960.

(10)

Wang, H.; Liu, Y.; Wang, L.; Qin, Y. N. Chem. Eng. J. 2008, 145, 25–31.

(11)

Rostrup-nielsen, J. R. J. Catal. 1973, 31, 173–199.

(12)

Auprêtre, F.; Descorme, C.; Duprez, D. Catal. Commun. 2002, 3, 263–267.

(13)

Song, H.; Ozkan, U. S. J. Catal. 2009, 261 (1), 66–74.

(14)

Biswas, P.; Kunzru, D. Catal. Letters 2007, 118 (1–2), 36–49.

(15)

Saeki, T.; Tsuda, K.; Ohkita, H.; Kakuta, N.; Mizushima, T. J. Japan Pet. Ist. 2016, 59 (1), 16–23.

(16)

Snytnikov, P. V; Badmaev, S. D.; Volkova, G. G.; Potemkin, D. I.; Zyryanova, M. M.; Belyaev, V. D.; Sobyanin, V. A. Int. J. Hydrogen Energy 2012, 37 (21), 16388–16396.

(17)

Moraes, T. S.; Neto, R. C. R.; Ribeiro, M. C.; Mattos, L. V.; Kourtelesis, M.; Verykios, X.; Noronha, F. B. Top. Catalisys 2015, 58, 281–294.


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 30 of 51

(18)

Siqueira, T.; Crisostomo, R.; Neto, R.; Celso, M.; Veiga, L.; Kourtelesis, M.; Ladas, S.; Verykios, X. "Applied Catal. B, Environ. 2016, 181, 754–768.

(19)

Montgomery, D. C. Design and Analysis of Experiments, Eighth Edi.; John Wiley & Sons, 2013.

(20)

Team, R. C. R Foundation for Statistical Computing: Vienna, Austria. 2015.

(21)

Chen, L.-C.; Lin, S. D. Appl. Catal. B Environ. 2011, 106 (3–4), 639–649.

(22)

Fatsikostas, A. N.; Verykios, X. E. J. Catal. 2004, 225 (2), 439–452.

(23)

Xu, J.; Zhang, X.; Zenobi, R.; Yoshinobu, J.; Xu, Z.; Yates, J. T. Surf. Sci. 1991, 256 (3), 288–300.

(24)

Sarathy, S. M.; Oßwald, P.; Hansen, N.; Kohse-höinghaus, K. Prog. Energy Combust. Sci. 2014, 44, 40–102.

(25)

Graschinsky, C.; Contreras, J. L.; Amadeo, N.; Laborde, M. Ind. Eng. Chem. Res. 2014, 53, 15348–15356.

(26)

Mattos, L. V; Jacobs, G.; Davis, B. H.; Noronha, F. B. Chem. Rev. 2012, 112, 4094–4123.

(27)

Montero, C.; Ochoa, A.; Castaño, P.; Bilbao, J.; Gayubo, A. G. J. Catal. 2015, 331, 181–192.

(28)

Aupretre, F.; Descorme, C.; Duprez, D.; Casanave, D.; Uzio, D. J. Catal. 2005, 233 (2), 464–477.

(29)

Hung, C.-C.; Chen, S.-L.; Liao, Y.-K.; Chen, C.-H.; Wang, J.-H. Int. J. Hydrogen Energy 2012, 37 (6), 4955–4966.

(30)

Matos, J.; Poon, P. S.; Lanfredi, S.; Nobre, M. A. L. Fuel 2013, 107, 503–510.

(31)

Rodriguez, E.; Leconte, M.; Basset, J.-M.; Tanaka, K. J. Catal. 1989, 119, 230– 30 ACS Paragon Plus Environment

Page 31 of 51 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

237.

(32)

Jones, G.; Jakobsen, J. G.; Shim, S. S.; Kleis, J.; Andersson, M. P.; Rossmeisl, J.; Abild-Pedersen, F.; Bligaard, T.; Helveg, S.; Hinnemann, B.; Rostrup-Nielsen, J. R.; Chorkendorff, I.; Sehested, J.; Nørskov, J. K. J. Catal. 2008, 259 (1), 147– 160.

(33)

Nikolla, E.; Schwank, J.; Linic, S. J. Catal. 2009, 263 (2), 220–227.

(34)

Graschinsky, C.; Giunta, P.; Amadeo, N.; Laborde, M. Int. J. Hydrogen Energy 2012, 37 (13), 10118–10124.

(35)

Liu, Z.; Duchoň, T.; Wang, H.; Peterson, E. W.; Zhou, Y.; Luo, S.; Zhou, J.; Matolín, V.; Stacchiola, D. J.; Rodriguez, J. a.; Senanayake, S. D. J. Phys. Chem. C 2015, No. 111, 18248–18256.

(36)

Moraes, T. S.; Rabelo Neto, R. C.; Ribeiro, M. C.; Mattos, L. V.; Kourtelesis, M.; Ladas, S.; Verykios, X.; Noronha, F. B. Appl. Catal. B Environ. 2016, 181, 754–768.

(37)

Xu, W.; Liu, Z.; Johnston-peck, A. C.; Senanayake, S. D.; Zhou, G.; Stacchiola, D.; Stach, E. A.; Rodriguez, J. A. ACS Catal. 2013, 3, 975–984.

(38)

Liu, Z.; Xu, W.; Yao, S.; Johnson-Peck, A. C.; Zhao, F.; Michorczyk, P.; Kubacka, A.; Stach, E. A.; Fernández-García, M.; Senanayake, S. D.; Rodriguez, J. A. J. Catal. 2015, 321, 90–99.

(39)

Knözinger, H.; Buhl, H.; Kochloefl, K. J. Catal. 1972, 68, 57–68.

(40)

Dancini-Pontes, I.; Silva, F. A.; DeSouza, M.; Scaliante, M. H. N. O.; Alonso, C. G.; Bianchi, G. S.; Medina Neto, A.; Pereira, G. M.; Fernandes-Machado, N. R. C. Chem. Eng. J. 2015, 273, 66–74.

(41)

Sivaramakrishnan, R.; Su, M.; Michael, J. V; Klippenstein, S. J.; Harding, L. B.; Ruscic, B. J. Phys. Chem. A 2010, 114, 9425–9439.

(42)

Tran, L.; Glaude, P.; Fournet, R.; Battin-Leclerc, F. Energy & Fuels 2013, 27, 2226–2245. 31 ACS Paragon Plus Environment

Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 32 of 51

(43)

Xu, S.; Lin, M. C. Proc. Combust. Inst. 2007, 31, 159–166.

(44)

Zheng, J.; Truhlar, D. G. Faraday Discuss. 2012, 157, 59–88.

(45)

Nishiguchi, T.; Matsumoto, T.; Kanai, H.; Utani, K.; Matsumura, Y.; Shen, W.J.; Imamura, S. Appl. Catal. A Gen. 2005, 279 (1–2), 273–277.

(46)

Hou, T.; Zhang, S.; Chen, Y.; Wang, D.; Cai, W. Renew. Sustain. Energy Rev. 2015, 44, 132–148.

(47)

Alonso, C. G.; Furtado, A. C.; Cantão, M. P.; Andreo dos Santos, O. A.; Camargo Fernandes-Machado, N. R. Int. J. Hydrogen Energy 2009, 34 (8), 3333–3341.

(48)

Guarido, C. E. M.; Cesar, D. V.; Souza, M. M. V. M.; Schmal, M. Catal. Today 2009, 142 (3–4), 252–257.

(49)

Mattos, L. V.; Jacobs, G.; Davis, B. H.; Noronha, F. B. Chem. Rev. 2012, 112, 4094–4123.

(50)

Bichon, P.; Haugom, G.; Venvik, H. J.; Holmen, A.; Blekkan, E. a. Top. Catal. 2008, 49 (1–2), 38–45.

(51)

Galetti, A. E.; Gomez, M. F.; Arrúa, L. A.; Abello, M. C. Appl. Catal. A Gen. 2008, 348 (1), 94–102.

(52)

Aupr, F.; Descorme, C.; Duprez, D. Catal. Commun. 2002, 3, 263–267.

(53)

Moraes, T. S.; Rabelo Neto, R. C.; Ribeiro, M. C.; Mattos, L. V.; Kourtelesis, M.; Ladas, S.; Verykios, X.; Noronha, F. B. Appl. Catal. B Environ. 2016, 181, 754–768.


Page 33 of 51 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Energy & Fuels

TABLE Table 1. Experimental data used to perform the statistical study of factors.

Cu (%) 0 5 0 5 0 5 0 5 0 5 0 5 0 5 0 5

Ni (%) 0 0 10 10 0 0 10 10 0 0 10 10 0 0 10 10

Factors Molar Ratio O2/C2H5OH 0 0 0 0 0.5 0.5 0.5 0.5 0 0 0 0 0.5 0.5 0.5 0.5

Temperature (°C) 450 450 450 450 450 450 450 450 500 500 500 500 500 500 500 500

Acetaldehyde 0.02 0.03 0.08 0.09 0.00 0.02 0.31 0.55 0.01 0.02 0.02 0.03 0.00 0.04 0.30 0.58

Flow rate (mmol/min) CH4 CO Ethene Acetone 0.00 0.00 0.02 0.05 0.00 0.00 0.01 0.08 0.00 0.00 0.01 0.05 0.01 0.00 0.01 0.11 0.11 0.20 0.26 0.22 0.08 0.13 0.07 0.27 0.10 0.41 0.06 0.11 0.07 0.27 0.01 0.08 0.01 0.00 0.12 0.16 0.01 0.01 0.06 0.21 0.01 0.01 0.06 0.13 0.01 0.01 0.07 0.17 0.13 0.15 0.21 0.17 0.14 0.20 0.08 0.37 0.04 0.20 0.03 0.07 0.04 0.17 0.01 0.07

CO2 0.09 0.54 0.11 0.21 1.23 1.35 0.82 0.77 0.28 0.27 0.20 0.41 1.27 1.39 0.95 0.81

H2 0.48 0.58 0.60 0.96 1.34 1.23 1.36 0.79 1.23 1.17 1.32 1.79 1.13 1.95 0.79 0.93

Conversion (mol/mol) 0.14 0.23 0.30 0.36 0.83 0.79 0.76 0.80 0.39 0.37 0.35 0.38 0.95 0.82 0.72 0.77

33

ACS Paragon Plus Environment

Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 34 of 51

FIGURES

Figure 1. Statistical results for acetaldehyde production: a) pareto plot for the variability explained by the factors of the adjusted regression model; b) simulated envelope of the regression model and c) contour curve of the regression model.


Page 35 of 51 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

Figure 2. Statistical results for CH4 flow: a) pareto plot for the variability explained by the factors of the adjusted regression model; b) simulated envelope of the regression model and c) contour curve of the regression model.

Figure 3. Statistical results for CO flow: a) pareto plot for the variability explained by the factors of the adjusted regression model; b) simulated envelope of the regression model.


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 36 of 51

Figure 4. Statistical results for ethylene flow: a) pareto plot for the variability explained by the factors of the adjusted regression model; b) simulated envelope of the regression model and c) contour curve of the regression model.


Page 37 of 51 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

Figure 5. Statistical results for acetone flow: a) pareto plot for the variability explained by the factors of the adjusted regression model; b) simulated envelope of the regression model and c) contour curve of the regression model.


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 38 of 51

Figure 6. Statistical results for CO2 flow: a) pareto plot for the variability explained by the factors of the adjusted regression model; b) simulated envelope of the regression model and c) contour curve of the regression model.


Page 39 of 51 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

Figure 7. Statistical results for H2 flow: a) pareto plot for the variability explained by the factors of the adjusted regression model; b) simulated envelope of the regression model and c) contour curve of the regression model.


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 40 of 51

Figure 8. Statistical results for conversion: a) pareto plot for the variability explained by the factors of the adjusted regression model; b) simulated envelope of the regression model and c) contour curve of the regression model.

Figure 9. Results of a) TG and b) DSC from Ni-CeO2 catalyst samples fresh and after the steam reform (SR) and oxidative steam reforming (OSR) tests at 450 and 500 °C.


Page 41 of 51 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

SCHEME

Scheme 1. Scheme of the reactions suggested in the study with the experiments performed. The factors that favor a certain route are indicated in the mechanism: CeO2, Ni, O2 and temperature (Temp).


Cu:Ni:Temp

2 0

−1.5

−1.0

−0.5

0.0

0.5

1.0

3.5

0.0

0.5

x10 -4 3x1 -4 0 0.00 02 2x10 -4

1.5x10 -4

-0.5 -1.0

1.5

Theoretical quantiles

1.0

Cu:O2/C2H5OH:Temp

Ni:Temp

Temp

Ni:O2/C2H5OH:Temp

O2/C2H5OH:Temp

Cu:Ni:O2/C2H5OH

Cu:O2/C2H5OH

Cu:Ni

Cu

●

O2/C2H5OH

Ni:O2/C2H5OH ●

●

Cu:Temp

Cu:Ni:O2/C2H5OH:Temp

●

●

●

b) Residuals

●

-2

●

25% 50% 75% 100% Cumulative Percentage

●

Page 42 of 51

0%

●

● ● ● ● ●

Ni

Frequency

a)

0

c)

XO2/C2H5OH

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

2x10-4 4x10-4 6x10-4 8x10-4 1x10-3

Energy & Fuels

1x10 -4 5x10-5

-1.0

-0.5

0.0

XNi


0.5

1.0

-1.0 -0.5 0.0 0.5 1.0

XO2/C2H5OH


0 -5

7x1 -5 0

0%

50%

75%

-3 -2 -1

0

1

Residuals 2

Cumulative Percentage

25%


−0.5

6x1

1.0

Cu:Ni:Temp Cu:Ni:O2/C2H5OH

−1.0

0.5

1.0

−1.5

0.0

0.5

●

-0.5

XTemp

0.0

Cu:Ni

O2/C2H5OH :Temp

Temp

Cu

●

-5

-1.0

-0.5

6x 7x1 - 10 -5 0 5

3

100%

●

0

-1.0

XTemp

8x10 -5

●

4x1

XO2/C2H5OH 1.0

●

8x10-5

0.5

●

9x10-5

9x10 -5

Cu:Temp

●

7x10-5 6x10-5

0.0

Cu:O2/C2H5OH

●

4x10-5

-0.5

4x10 -5 5x10 -5

Ni:O2/C2H5OH:Temp

●

Cu:O2/C2H5OH:Temp

●

5x10-5

-1.0 Ni:Temp

●

3x10 -5

●

Ni:O2/C2H5OH

Ni

O2/C2H5OH ●

2x10 -5

1x10-5

1.0

0.5

c)

0.0

●

3x10-5

-0.5

Frequency 5.0x10-5 1.0x10-4 1.5x10-4 2.0x10-4

a)

2x10-5 10x10-5

-1.0

0

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

XNi

Page 43 of 51 Energy & Fuels

●

b)


0.0

-1.0

0.5

-0.5

1.0

0.0

XNi

1.5

10 5x

-5

0.5 1.0

● ●

● ●

●

● ● ● ● ● ●

●

-3

-2

-1

0

1

Residuals 2

3


●

0%

●

Cu:O2/C2H5OH:Temp

●

Cu:Ni:Temp

Cu:Ni:O2/C2H5OH

6x10-4

a)

Cu:Ni

Cu

Cu:O2/C2H5OH

Cu:Temp


Temp

O2/C2H5OH:Temp

Ni:O2/C2H5OH:Temp

Ni:Temp

Ni:O2/C2H5OH

Ni

4x10-4

O2/C2H5OH

2x10-4

Frequency

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 0

Energy & Fuels Page 44 of 51

b)

−1.5


−1.0


−0.5 0.0 0.5 1.0 1.5

4 2 0

Residuals

-2

75% 50% 25% 0%

Ni:Temp

Cu:Temp

Cu:Ni:Temp


Ni:O2/C2H5OH:Temp

Cu:Ni:O2/C2H5OH

Cu:Ni

Cu

Ni

0

Temp

O2/C2H5OH

●

●

●

Cu:O2/C2H5OH

Ni:O2/C2H5OH

Frequency

●

●

Cu:O2/C2H5OH:Temp

O2/C2H5OH:Temp

●

●

b)

-4

100%

●

●

● ● ● ● ●

●


a)

−1.5

−1.0

−0.5

0.0

0.5

1.0

1.5

10 -

-1.0

5

-0.5

0.0

0.5

XO2/C2H5OH

1.0

-0.5 -5

0.0

XNi

0.5

4x10

1.0

-5

6x10

-5

0 8x1

-4

10 1x

-1.0

-0.5

0.0

0.5

XO2/C2H5OH


-1.0 -0.5 0.0 0.5 1.0

XCu

4x1 0 5

6x1 0 5

8x1 0 5

0 -4 1x1 -1.0

1.0

4x 10 -5

6x1 -5 0 8x1 0 -5 1x 10 4 0. 00 01 2 -1.0

-1.0 -0.5 0.0 0.5 1.0

0 -5

-1.0 -0.5 0.0 0.5 1.0

1.0

XCu

-1.0 -0.5 0.0 0.5 1.0

6x1

4x

0.5

-5

XTemp

0.0 XNi

XCu

-0.5

-1.0

-1.0 -0.5 0.0 0.5 1.0

00 4 0 1 1x -5 0 8x1 -5 6x10

0.

XTemp

2 01

4x10 -5

XO2/C2H5OH

c)

-1.0 -0.5 0.0 0.5 1.0


0 8x1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

1x10-4 2x10-4 3x10-4 4x10-4

Page 45 of 51

-0.5

0.0

XNi

0.5

1.0

0.5

1.0

-5

0 4x1

-5

0

6x1

-5

0

8x1 -1.0

-0.5

0.0

XTemp

4 3 2 1

Residuals

Cu:O2/C2H5OH

Ni:O2/C2H5OH:Temp

Cu:Temp

Cu:Ni:Temp

Cu:Ni

Ni:Temp

Temp

Cu:Ni:O2/C2H5OH

O2/C2H5OH Cu

Ni:O2/C2H5OH

Ni

1.0

0

●

●

Cu:O2/C2H5OH:Temp

O2/C2H5OH :Temp

Frequency

●

●

●


●

●

●

b)

-3 -2 -1 0

●

−1.5

−1.0

−0.5

0.0

1.5

-4

2.2 -4 0 1 .8x

0.5 0.0 -0.5

1.0

x10

1

-1.0

0.5


-4

2x10

-4

XO2/C2H5OH

c)

●


● ● ● ●

●

0%

a)

Page 46 of 51

10 1x

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

1x10-4 2x10-4 3x10-4 4x10-4 5x10-4

Energy & Fuels

-4

0 1.6x1

-4

1.4x10

-1.0

-4

1.2x10

-0.5

0.0

XNi


0.5

1.0

4 2 0

Residuals

−1.0

8x10 5

5

−0.5

0.5

1.0

-1.0

-0.5

0.0

0.5

1800 000

-1.0

-1.0

0.0

XNi

-0.5

1600 000

120 000 0 14 00 00 0 16 00 00 0

6

-0.5

XTemp

0.5

1400 000

1x106

0

-1.0

1.5

2x1

16 00 00 0 18 00 00 0

1200 000

0.0

XTemp 1200000

1400 000

1.0

5

1x10 6

-0.5

0.5 -0.5

0.0

1200000

-1.0

XO2/C2H5OH

6

0.5

8x10

10 8x

1x10

0.0


1.0

75% 50% 25%

-2

−1.5

0%

Cu:O2/C2H5OH:Temp

Ni:O2/C2H5OH:Temp

1.0

Cu:Temp

Cu:Ni:O2/C2H5OH

Ni:Temp

Cu:Ni:Temp

Temp

Cu:Ni

Cu:O2/C2H5OH

O2/C2H5OH:Temp


Ni

●

Cu

●

●

Ni:O2/C2H5OH

O2/C2H5OH

● ●

●

●

●

b)

-4

●

100%

● ● ● ● ● ●


a)

1.0

Frequency

c)

Energy & Fuels

0 00 00 18

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

0.0000 0.0005 0.0010 0.0015 0.0020

Page 47 of 51

0.0

XNi

0.5

1.0


-1.0

-0.5

0.0

0.5

XO2/C2H5OH

1.0

4 0

Residuals

-2

75% 50% 25%

-4

−1.5

0%

Cu:Temp

Cu:Ni


Cu:Ni:Temp

Cu:Ni:O2/C2H5OH

Ni

Cu:O2/C2H5OH

Cu

O2/C2H5OH

Temp

●

●

Ni:O2/C2H5OH:Temp

Cu:O2/C2H5OH:Temp Ni:Temp

Ni:O2/C2H5OH

●

●

0

●

●

●

●

b)

2

100%

●


● ● ● ● ● ●

O2/C2H5OH:Temp

4x106

Frequency

2x106

a)

Page 48 of 51

−1.0

−0.5

0.0

0.5

1.0

1.5

5

1.0

1.0

c)

1.0


8x10 5

5

8x10

0.0

XNi

0.5

1.0

-1.0

-0.5

0.5 0.0 -1.0

-1.0

1800 000

6

-0.5

-0.5

1600 000

120 000 0 140 000 0 16 00 00 0

0

-1.0

XTemp

0.0

1400 000

-0.5

XTemp

1200 000

1x10 6

2x1

1400 000 16 00 00 0 18 00 00 0

1200000

0.0

1200000

-0.5

1x10 6

0.5

6

1x10

-1.0

XO2/C2H5OH

0.5

10 8x

0 00 00 18

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

6x106

Energy & Fuels

0.0

0.5

XNi


1.0

-1.0

-0.5

0.0

0.5

XO2/C2H5OH

1.0

0.4

Ni:Temp

●

● ● ● ●

●

● ●

Cu:O2/C2H5OH:Temp

● ● ●

-4

-2

0

Residuals 2

4


●

0%

●

Cu

●

Ni:O2/C2H5OH:Temp


Cu:Ni:Temp

1.0

a)

O2/C2H5OH:Temp

Cu:Temp

Cu:O2/C2H5OH

Cu:Ni:O2/C2H5OH

Ni

Cu:Ni

Temp

0.8

O2/C2H5OH

0.6

Frequency

●

Ni:O2/C2H5OH

0.2

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 0.0

Page 49 of 51 Energy & Fuels b)

−1.5 −1.0

c)



−0.5 0.0 0.5 1.0 1.5

a)

102 100 98 96 94 92 90 88 86 84 82 80

SR 450°C SR 500°C OSR 450°C OSR 500°C Fresh 0

100

200

300

400 500 600 700 Temperature (°C) °

800

900 1000

Page 50 of 51

b)

3

Heat Flow per Weight (mW/mg)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Weight Percentage (%)

Energy & Fuels

2,5 2

SR 450°C

1,5

SR 500°C OSR 450°C

1

OSR 500°C

0,5

Fresh

0 -0,5 -1

-1,5 0

100 200 300 400 500 600 700 800 900 1000 Temperatute (°C)


Page 51 of 51

O2 Ni e O2 O2

Temp CeO2 O2

O2 CeO2

C2H5OH

+ 2H2(g) +

+ 1 (O* ou OH*) 1 2 2 CO 2(g) CeO2

Ni

*

D

Ni

CH3COO* + H*

CH4* + CO*

CH4(g)

CO* + 2H2

+ H 2O CeO2

E

A

CH4(g) + C

H2(g) + H*

O2 H Ce u O * o O O2

C2H3OH (g)

+ H 2O

C xH y

C2H3OH* + H2(g) +

C

Ni Temp

1 2 C3H6O(g)

C2H4(g)

C2H4*+ H2O

CO2(g) + H2(g)

+ H 2O CeO2

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

CO2(g) + H2(g)


B CeO2

+ 2(O* ou OH*) CeO2

CHx* + CO2(g)

CO2(g) + yH2

Statistical approach on ethanol reforming - Energy & Fuels (ACS

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