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Biofuels and Biomass
Molecular-Level Kinetic Modeling of Methyl Laurate: The Intrinsic Kinetics of Triglyceride Hydroprocessing Pratyush Agarwal, Nicholas Evenepoel, Sulaiman Saleh Fahad Al-Khattaf, and Michael T Klein Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.8b00647 • Publication Date (Web): 29 Mar 2018 Downloaded from http://pubs.acs.org on March 29, 2018
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Energy & Fuels
Molecular-Level Kinetic Modeling of Methyl Laurate: The Intrinsic Kinetics of Triglyceride Hydroprocessing
Pratyush Agarwal1, Nicholas Evenepoel1, Sulaiman S. Al-Khattaf2, and Michael T. Klein1,2* 1
Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, DE 19716 2 Center for Refining and Petrochemicals, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia
ABSTRACT A molecular-level kinetic model for the hydroprocessing of methyl laurate was constructed. The reaction network was deduced using experimental observations in the context of the delplot method for the discernment of product rank. The resulting 45 species and 83 reactions were used to construct the set of material balances in the kinetic model. Kinetic parameters of the model were determined by minimizing the difference between model outputs and experimental data for methyl laurate hydroprocessing. Differences in reactivity due to catalyst metal composition were modeled via the catalyst family concept. The model results show good agreement with the experimental results for a range of process conditions. INTRODUCTION The utilization of biomass as a raw material for the production of fuels and chemicals is an active area of research and commercial practice aimed at reducing the world’s reliance on fossil resources .1–3 A promising pathway is the production of engine fuels via upgradation of triglycerides, fatty acids, and fatty acid esters from algal, plant, and animal sources. This is because these feedstocks have a relatively high energy density coupled with low oxygen content. While triglycerides can be directly used as engine fuels, the high viscosity and cloud point of vegetable oils lead to poor fuel atomization and incomplete combustion in a diesel engine. This results in a high engine wear and a significant increase in particulate and CO emissions. Additionally, oxygenated compounds such as triglycerides and fatty acid methyl esters
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have poor oxidation stability and are incompatible with petroleum fuels.4–6 Hydroprocessing of these long-chain triglyceride molecules can produce fuels like green diesel, which has been shown to be a viable renewable diesel fuel because of its high cetane number, high oxidation stability, low impurity content, and feed flexibility.6–9 These biomass feeds usually exist as a complex mixture of different types of triglycerides and fatty acids. Additionally, due to limited supply, economics, food coproduction, and seasonal dependence of biomass, there can be a wide selection of molecules and mixtures.3,10 Studying model compounds that represent typical feed moieties can alleviate the burden of determining the behavior of every feed component in every possible feed. These model compounds should undergo the same intrinsic reactions as the whole feeds, but their use allows for an isolated kinetic study of the products for varying reactor conditions. Extensive experimental work has been performed to study the kinetics of fatty acids and fatty acid methyl esters (FAMEs) as model compounds.11–16 However, few studies have modeled the process at the molecular level. Azizan et al. developed a simulation for triolein hydrodeoxygenation based on thermodynamic equilibrium that provided qualitative insights in the model with no comparison to experimental data.17 Forghani et al.18 and Anand et al.19 considered lumped kinetic models for triglyceride hydroprocessing where the products were described in terms of four carbon number-based lumps. Kumar and Froment described the hydrocracking activity in detail in a mechanistic kinetic model but did not focus on the deoxygenation activity.20 This present work explored recently published experimental data to develop a molecular-level kinetic model that will serve as a starting point for a more complex feed like coconut oil. In the experimental work, NiMo supported over alumina was tested to hydrogenate the carboxyl group in methyl laurate. The reaction conditions were 300°C and 0.1 to 0.8 MPa of H2 pressure to produce the green diesel.12,13 From the data, delplot analysis allowed elucidation of the reaction pathways. The resulting network was used in a kinetic model to extract the rate constants of the prevalent reactions in the hydroprocessing of biomass derived feeds.
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REACTION NETWORK GENERATION Reaction pathway analysis to determine product rank was done via the method of delplots. The delplot method is a set of plots that allow for the rank-based separation of products. A first-rank delplot is a plot of molar yield/conversion (/) versus conversion () for the yields of the various products. The intercepts as → 0 in the first-rank delplot “rank” the product as follows: primary products have finite intercepts and higher-rank products have zero intercept. The method can be extended to higher rank delplots by plotting / vs , where is the delplot rank. In each case, the current rank () products have finite intercepts, higher-rank products have zero intercept, and lower-rank products diverge.21
a)
b)
1
10
1
Y/X
Y/X2
0.1 0.1
0.01 0.01
0.001 0.0
0.2
0.4
0.6
0.8
0.001 0.0
1.0
X 10
d) 100
1
10
Y/X4
c)
Y/X3
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Energy & Fuels
0.1
0.01
0.001 0.0
0.2
0.4
0.6
0.8
1.0
0.6
0.8
1.0
X
1
0.1
0.2
0.4
0.6
0.8
1.0
0.01 0.0
0.2
0.4
X
X CO
CH4
C2-C10
C11
C12
Figure 1. a) First-rank, b) second-rank, c) third-rank, and d) fourth-rank delplots for methyl laurate conversion from experimental data by Imai et al12, where Y is the yield and X is the conversion of methyl laurate
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The data of Imai et al12 are shown in the delplot context in Figure 1. The data represent the conversion of methyl laurate over catalysts with different Ni/Mo ratios under similar reaction conditions. Inspection of Figure 1a shows that the production of methane, C11, and C2 to C10 cracking products were primary products that formed directly from the methyl laurate reactant. Figure 1b, the second-rank delplot, shows methane, C11, and C2 to C10 diverging and C12 with a zero intercept. In Figure 1c, C12 seems to have a finite intercept suggesting that it is a third-rank product while methane, C11, and C2 to C10 still diverge. The fourth-rank delplot in Figure 1d shows all of methane, C11, C12, and C2 to C10 diverging. For all delplots, the carbon monoxide formation was difficult to interpret due to the methanation activity of the nickel catalyst resulting in a non-detectable concentration of CO in some cases.
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Energy & Fuels
Table 1. Reaction families for methyl laurate hydroprocessing. Atom subscripts represent atom labels.
Reaction Family
Sample Reaction*
Reaction Matrix O1
C2
H3
H4
R’
R’’
1
0
1
0
0
0
0
2
1
0
0
0
-1
-1
3
0
0
0
-1
1
0
4
H
0
0
-1
0
0
1
R’
0
-1
1
0
0
0
R’’
0
-1
0
1
0
0
1
2
3
H
4
H
O C
Decarbonylation
H
CO Hydrogenolysis
O
C
1
O
0
-1
1
0
C2
-1
0
0
1
3
1
0
0
-1
4
0
1
-1
0
H
H
1
Hydrodeoxygenation
O
C
2
H
H4
O1
0
-1
1
0
2
-1
0
0
1
3
1
0
0
-1
4
0
1
-1
0
C
H
H
C
CC Hydrogenolysis
1
1
0
-1
0
0
1
3
1
0
0
-1
4
0
1
-1
O
C
H
H4
O1
0
-1
1
0
2
-1
0
0
1
3
1
0
0
-1
4
0
1
-1
0
3
H4
H
H
C
C
2
C
C1
0
-1
1
0
C
2
-1
0
0
1
C
3
1
0
0
-1
4
0
1
-1
0
H
C
1
C
2
3
H
H4 0
C1
0
-1
1
2
-1
0
0
1
H3
1
0
0
-1
H4
0
1
-1
0
C
5
1
3
0
2
C
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H4
-1
1
*Atom superscripts represent atom labels
H
0
H
Paraffin Cracking
3
2
H
Paraffin Isomerization
2
C1 C
Aldehyde Hydrogenation
C
3
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Along with experimentally observed products1,2,9,16, this information was used to generate the candidate reaction families for methyl laurate hydroprocessing shown in Table 1. To make n-undecane as a primary product, a decarbonylation reaction was used, with CO and methanol as co-products. Methane as a primary product could be produced by either a CO bond cleavage reaction on the ML ester group, resulting in a carboxylic acid and a methane, or a CC hydrogenolysis at the end of the carbon chain in ML. Hydrogenolysis reactions are typically much slower than CO bond cleavage and so were ignored on ML. Due to it being a co-product in methane product, carboxylic acid formation then coincides with the formation of n-dodecane as a third-rank product via a carboxylic acid intermediate followed by two successive hydrodeoxygenations to form the alcohol intermediate and the dodecane product. The other possible pathway for third-rank n-dodecane production is a CO bond cleavage reaction on the ML ester group resulting in an aldehyde that can undergo a hydrogenation and a hydrodeoxygenation to form the alcohol intermediate and the dodecane product, respectively. However, it should be noted that aldehydes are not experimentally observed in significant quantities due to their high reactivities, so it is difficult to discern their rank.9 Additionally, although C2-C10 formation can be directly from cracking ML (first-rank) or any other intermediate , the cracking function of the reactor is low. Therefore, cracking was limited to the paraffins to reduce the overall network complexity. A methanation reaction22,23 was used to model the conversion of the CO group to CH4 on the nickel sites as experimentally observed by the lack of CO formation on nickel catalysts12. Table 2. Network statistics generated using the Interactive Network Generator (INGen)
Species Type FAME Carboxylic Acid Aldehyde Alcohol n-Paraffin i-Paraffin CO, H2O, H2
Number 1 1 1 2 12 25 3
Total Species
45
Reaction Type CO Hydrogenolysis Hydrodeoxygenation Decarbonylation Aldehyde Hydrogenation Paraffin Isomerization Paraffin Cracking CC Hydrogenolysis Methanation Total Reactions
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Count 2 3 3 1 25 28 19 1 83
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Energy & Fuels
The reactions identified using the delplot method represent the likely reactions during hydroprocessing of methyl laurate. The reaction network was systematically generated starting from methyl laurate using the Interactive Network Generator (INGen).24,25 INGen uses bond-electron matrices to computationally represent molecule structures. A reactive site can be identified as a subgroup of the overall molecule that is universal for a homologous series of reactions (reaction family). The reaction itself is characterized as a matrix addition operation representing bond making and breaking behavior of the reactive subgroup. The reactive subgroup and reaction matrices are presented in Table 1. Table 2 shows the final network statistics. There was a total of 45 species: the methyl laurate FAME, dodecanoic acid, dodecanal, dodecanol, methanol, CO, water, hydrogen, and the remainder being the n-dodecane and n-undecane with their cracking and isomerization products. Some additional reaction rules were used for the reaction families in Table 2 . CO hydrogenolysis was only allowed to break a CO bond in an ester group with the use of hydrogen. Hydrodeoxygenation (HDO) was for the specific CO hydrogenolysis where an alcohol group was cleaved with water as a product. Decarbonylation searched for C=O groups in any configuration: FAME, aldehyde, or carboxylic acid. Aldehyde hydrogenation was limited to search for aldehyde groups and reducing them to alcohol groups with hydrogen. Paraffin isomerization was allowed to create methyl branches only, and paraffin cracking could only occur at a branch site which would not require a primary carbenium ion formation in its underlying mechanism on an acid site. CC hydrogenolysis was used in the case where C-C bond breaking occurred on a metal site and allowed for methane and ethane cracking from the paraffins. The methanation reaction could only convert carbon monoxide and hydrogen to methane and water. This resulted in a total of 83 reactions for the methyl laurate feed. The final network is depicted in Figure 2.
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+2H2 -CH4 -H2O
-CO
-CO O +H2
O O
C
-CH3OH C11H23
H
C
+H2
HO
C11H23
+H2 -H2O +2H2
+H2 -H2O
C11H24
C12H25
C12H26
+H2
-H2O
+H2
+H2
Cracking Products
Cracking Products
O
-CH4 HO
C
+H2
C11H23
-H2O
-CO
CH4 + H2O
CO + 3H2
Figure 2. Parallel reaction pathways for paraffin production from a methyl laurate reactant
MODEL EQUATIONS AND KINETICS The reaction network was used to generate a set of material balances, one for each species. The material balances, along with the initial conditions of the feed and the reactor, defined the initial value problem used to solve the kinetic model. The model development was done in an in-house software, the Kinetic Model Editor (KME).24 In this study, a fixed-bed hydrotreating unit with a bifunctional metal/acid catalyst under plug-flow conditions was modeled. The Langmuir-Hinshelwood-Hougen-Watson (LHHW) rate law formalism assuming surface reaction rate control was used to model the reactions on catalyst surfaces, as shown in equation 1.26,27 An explicit H2 partial pressure dependence was assumed on the adsorption denominator.
=
∗ ∏ ,
∗
∏
!#,$ %1 + ∑) "
8
∏ −
,$ ) *
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(1)
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Surface rate constants were modeled using the Arrhenius equation modified with the Bell-EvansPolyani28,29 linear free energy relationship (LFER) to describe the activation energies for each reaction, as shown in equation 2. The LFER concept exploits the systematic differences in rates of reaction between member reactions . of a reaction family /, where a reaction family is a homologous set of reactants subject to the same type of reaction. This significantly reduced the number of tunable parameters in the model, with each reaction family requiring only three tunable parameters, 0 , 12 , and 3, rather than a pre-exponential factor and activation energy for each reaction. A further extension of the LFER concept to catalyst families was also made to account for the differences in activity of different catalysts. This was accomplished using a departure term on the ln 0 factor, as shown in equation 3.30 The catalyst family extension models the change in reactivity between two different catalysts as constant for all reactions in a reaction family. This further reduces the number of model parameters of the same reaction system on different catalysts so that only one additional parameter is needed per reaction family for each new catalyst. ln , = ln 0 −
12 + 3 ∆7 89
(2)
ln 0, = ln 0,;
