Sensitivity of Asphaltene Aggregation toward the Molecular

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Sensitivity of Asphaltene Aggregation towards the Molecular Architecture Under Desalting Thermodynamic Conditions Hugo Santos Silva, Ahmad Al Farra, Germain Vallverdu, Didier Bégué, Brice Bouyssiere, and Isabelle Baraille Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.7b02728 • Publication Date (Web): 23 Oct 2017 Downloaded from http://pubs.acs.org on October 24, 2017

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Sensitivity of Asphaltene Aggregation towards the Molecular Architecture Under Desalting Thermodynamic Conditions H. Santos Silva,∗,† A. Alfarra,‡,¶ G. Vallverdu,†,¶ D. Bégué,†,¶ B. Bouyssiere,†,¶ and I. Baraille†,¶ †Université de Pau et des Pays de l’Adour, IPREM (CNRS-UMR 5254), 2 Avenue Président Angot, 64053 Pau, France ‡Total Research & Technology, Gonfreville, BP 27, 76700 Harfleur, France ¶Joint Laboratory C2MC: Complex Matrices Molecular Characterization, Total Research & Technology, Gonfreville, BP 27, 76700 Harfleur, France E-mail: [email protected]

Abstract The challenges faced by the oil and shale industries include the comprehension of the physical-chemical behavior of heavy-weight phases. These phases have a high tendency to aggregate, mainly due to the presence of asphaltenes, the composition of which has been fairly unclear up to now. The chemical composition of this phase is one of the driving forces behind physical-chemical behavior in oil, and the structureproperty relations of these systems are key in the development of improved refining techniques, including the design of new catalysts. In this paper, the aggregation of asphaltene molecules is studied with regard to molecular architecture and variations in the size of the aromatic core and lateral chain length using classical molecular dynamics

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simulations. How these characteristics are impacted by temperature and pressure is also examined. This analysis provides a general overview of the factors that have the strongest impact on the formation and stability of nanoaggregates and clusters of nanoaggregates.

Introduction In the modern economic system, although much progress has been made in the pursuit of alternative sources of energy, oil as an energy source will still have its place in our way of life for some years. Much work is still needed to understand the origins of the physical-chemical properties of crude oil and to discover new ways of making crude oil cleaner. Countless scientific contributions can still be made in this field, including increasing the energetic efficiency of this energy source and reducing the quantity of side-product chemicals used to treat, crack and refine oil. 1 In this context, heavy crude oils become the focus, and shale exploitation will be widespread for some years to come. Most of the problems encountered during the processing of these oils may be attributed to the asphaltene’s physicochemical properties, such as aggregation, precipitation, and emulsion stabilization. Thus, understanding the behavior of this heavy-weight phase component is key to ensuring that the exploration of oil will remain economically viable and will become environmentally cleaner. Asphaltenes are known as the phase of oil that is insoluble in light alkanes like n-pentane (C5), n-hexane (C6) and n-heptane (C7). Asphaltenes may also be soluble in aromatic solvents like toluene, but this might not be always the case. 2 Asphaltenes consist of a complex mixture of aromatic polycyclic molecules containing oxygen, sulfur and nitrogen as heteroatoms. 2,3 Several works have shown that the presence of asphaltenes can cause problems throughout the oil exploration and refinement processes 4 due to the natural tendency of these compounds to aggregate and form structures that are able to invert the flow properties of crude oil, inducing increases in viscosity and even clogging rock pores. 5 Asphaltenes are 2


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also believed to play a major role in the stability of emulsions formed during desalting since they tend to migrate to the oil/water interface. 6,7 Asphaltenes form nanoaggregates that are composed of ∼ 6 molecules, and these nanoaggregates form clusters that are composed of ∼ 8 nanoaggregates. 8 This hierarchical aggregation model, known as the Yen-Mullins model, 9 indicates that the polycyclic (aromatic core) structure of the asphaltene molecules are responsible for the formation of primarily faceto-face (π-stacking) structures that are cohesive through van der Waals interactions. The first asphaltene molecules interact in this way, and the subsequent aggregation of additional molecules is then constrained by the presence of the alkane substituents (lateral chains) that begin to repulse one another by steric hindrance. 10 In this way, the addition of more asphaltene molecules induces the appearance of other nanoaggregates instead of enlarging the existing nanoaggregates. 11 Since there is no longer a high-energy molecular surface available to stabilize additional asphaltene molecules, the nanoaggregates eventually undergo cluster formation, for which the energy of interaction between nanoaggregates is much lower than that between asphaltene molecules within a nanoaggregate. 10 This model has been corroborated by several experimental and modeling studies, mainly small angle X-ray (SAXS) and neutron (SANS) scattering, 3,12 1 H NMR, 13 and classical molecular dynamics (CMD) simulations. 14 More specifically, the cohesion of asphaltenes within a nanoaggregate is governed by three types of chemical interactions: dispersive (ruled by van der Waals forces) interactions; dipole interactions; and H-bonding (both through electrostatic forces). During the self-assembly of asphaltene into nanoaggregates, molecules can assume face-to-face (π-stacking/π-π), edge-on (T-shaped geometry/H-π/π-σ) and offset π-stacked (σ-σ) geometries, as has been shown by the work of Pacheco et al., 15 among others, using CMD simulations. This work in particular has shown that the aromatic cores are solely responsible for the stacking tendency of the aromatic sheets, whereas the aliphatic chains have a role in inhibiting the stacking formation, depending on the type of asphaltene under study.

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Since the mid 90’s, CMD simulations have been valuable tools 16 in understanding in more detail the role of each molecular feature in the aggregation of asphaltenes. Even though the molecular models used at that time are not consistent with the recent findings concerning the molecular structure of asphaltenes, mainly the number of fused aromatic rings on the structure, 8 this technique has proven to be very useful in estimating the shape of the nanoaggregates, 17,18 their energy of interaction and partitioning, 19,20 and their solubility in common solvents, 21 among others. 22 In fact, CMD simulations have proven that the aggregation of asphaltenes is driven by a tendency towards stabilization within crude oil given that through the formation of nanoaggregates, the lateral chains become more exposed to the oil phase (which is mainly composed of aliphatics) instead of exposing the conjugated core. 23 This understanding of the chemical interactions an asphaltene nanoaggregate and cluster can have with their surroundings as obtained by CMD simulations can be directly linked to the experimental studies on the solubilization of asphaltenes in common solvents, as is the case for the determination the Hansen solubility parameters (HSP). 24 These parameters demonstrate that dispersive interactions are the strongest interactions within an asphaltene nanoaggregate, followed by hydrogen bonding. Surprisingly, however, the dipole interactions are weak, indicating a low polarity and, possibly, a low effect of the heteroatom content on the aggregation of asphaltenes. Despite these advances, the structure-function link in the aggregation of asphaltenes is highly dependent on molecular architecture. Without the appropriate molecules to simulate, one may miss some aspects of the structure of asphaltenes. As mentioned above, assessing the molecular structure of asphaltene molecules is a difficult task since the structure can easily vary within a crude oil source and across different sources. 25 However, very recently, Schuler et al. 26 shed some light on this topic by isolating and identifying some of these molecules using Atomic Force Microscopy (AFM). This study is the first of its kind since it establishes a new basis for the research on asphaltenes by using molecular modeling techniques that can

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now employ the molecular structure of real molecules instead of making use of models, as has been done historically. The structures reported by these authors agree with the knowledge on asphaltenes generated to date: asphaltenes are basically composed of aromatic cores, which are substituted by heteroatoms and present alkyl side chains with a variable number of carbons. 14 In this domain, our group has recently used CMD simulations on these experimentallyobserved molecules, and our results corroborate the experimental findings reported in the literature, 13 primarily those studies concerning the role played by heteroatoms in the asphaltene aggregation process. 27–29 We have been able to show that heteroatom substitution in the aromatic core does not change the type of aggregation in the nano-structures but can change, to some extent, the energies of interactions between asphaltenes by changing the dipoles formed in the aromatic core. 28 Moreover, we presented solid arguments on the identification of the impact of these heteroatoms on the shape of the aggregates found in the lateral chains: oxygen, mainly, can induce strong H-bond interactions and completely change the aggregation scenario of these molecules. Sulfur can also induce the appearance of new H-bond and S-O interactions, as was also shown by our group recently. 27 Another striking result of these works is that the aggregation strength depends strongly on the shape of the aromatic core: larger aromatic cores tend to aggregate more easily than smaller ones. 14,28 Thus, this paper is a follow-up to this strategy of elucidating the molecular architecture of asphaltenes in order to study the impact of this structure on aggregation properties. In this work, we tackle the following questions: 1 - what is the influence of the size of the conjugated core on the aggregation pattern of any given asphaltene molecule?; 2 - what is the influence of the lateral chain length on this same aggregation pattern?; 3 - are these two effects coupled?; 4 - how can temperature and pressure change these two effects?; 5 are the observations obtained consistent with as the system size increases? Our intention is to study the effect of every molecular architecture feature of asphaltene on the aggregation properties by decoupling these effects from all other effects. Furthermore, by making

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incremental variations in chain length and conjugated core size, for instance, we intend to elucidate each effect and study any coupling between effects. This strategy is thus based on the experimentally-observed molecules by Schuler et al., but slight modifications are made to these molecules. The resulting molecular architectures are still consistent with the common knowledge on the structure of asphaltenes, even though the structures themselves are hypothetical.

Methodology Next, we list the strategies undertaken to answer the questions that motivated this work. To determine the influence of the conjugated core size on the aggregation of asphaltenes, we have modeled different asphaltene molecules belonging to the same class and family. All of these molecules have the same basic molecular structure, to which carbon atoms were added stepwise, forming new aromatic rings. Then, the aggregation process was studied separately for each lateral chain. The influence of the lateral chain length on the aggregation process was studied by increasing the chain length for each single asphaltene molecule considered in this study. Additionally, polar and apolar ends of the chain were considered by including −COOH or −CH3 groups at the end of each chain. This portion of the analysis highlights any possible link between the aggregation and the lateral chain length and/or polarity. The extrinsic parameter of the number of molecules within the system was studied by calculating the dynamics in simulation boxes containing 5, 15, 45 or 135 asphaltene molecules, increasing the number of solvent molecules and the box volume accordingly in order to maintain a constant concentration across the dimensions. This measure ensures that each observed phenomenon is dependent on the nanoaggregate clusters. Last, the influence of pressure and temperature was taken into account in the form of three distinct thermodynamic conditions: 298 K and 1 bar, 298 K and 15 bar and 423 K and 15 bar. The intermediate condition (298 K, 15 bar) is not experimentally useful in this context but was needed in order to decouple

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any indistinct effect due to either pressure or temperature. These conditions simulate the operational conditions to which asphaltene-containing crude oils are subjected during the desalting process once they arrive at the refinery. 30,31 The computational details behind the CMD simulations are fully presented in the ESI. In brief, the simulations consist of using the GROMOS96 force field with the 53a6 parameter set 32 within the Gromacs 5.0 33 package. This United-Atom (UA) force field allows one to increase the size of the systems being treated without compromising accuracy. Moreover, bond vibrations have been constrained since they occur at time scales that are orders of magnitude faster than the physical-chemical process of interest. The molecular systems studied herein are based on the so-called CA22 (Figure 1.a) molecule identified by Schuler et al., 26 to which we have grafted two lateral chains on the opposite sides of the molecule. Then, the length of this chain was screened to be between n-C6 H13 to n-C16 H33 , and the number of fused rings on the conjugated core was increased (7, 8, 9 and 11), as seen in Figure 1.b-d (both chains had the same length, except for a particular case where one of the chains was a n-C6 H13 and the other a n-C16 H33 one). The so-called PA3 molecule type described by the above authors was also studied with two different lateral chains. Toluene was used as a solvent in order to mimic the infinite dissolution effect and to avoid the formation of the aggregates due to differences in polarity. The so-formed solutions have an asphaltene concentration on the order of ∼ 5 wt.%. These molecules are defined as presented in Table 1 alongside the labeling system used. Other physicochemical properties of these molecules are presented in Table 2. The analysis method examines the radial distribution functions (RDFs g(r)) of the dynamics. Essentially, these functions are probability functions that determine how the liquid, in this case, is structured. RDFs are calculated by counting the number of molecules found in each increment of the radial coordinate centered on the center of mass of a reference molecule for each time step in the dynamics. By iterating this process for all the molecules of interest in the system, one can obtain a histogram-like curve that can indicate how as-

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phaltene molecules are arranged at short (within the nanoaggregate) and long (in-between nanoaggregates) distances. The integral of this function allows for the determination of the number of neighbors around a central molecule through the following:

N=

Z

∞

ρg(r)4πr2 dr + 1

(1)

r=0

where N is the number of molecules, ρ is the density of the system and r is the radial coordinate. In the same way, the integral evaluated up to the first minimum (rm ) gives the coordination number (CN ):

CN =

Z

rm

ρg(r)4πr2 dr

(2)

r=0

For asphaltenes, rm is the first minimum of the RDF after the first peak that is found at approximately 0.38 nm. For all of the studied molecules, the first minimum is fixed to rm = 0.6 nm. The ratio CN/N (%) estimates the proportion of the molecules that have a πstacking aggregation pattern among the first neighbors compared to all the other molecules present in the system, i.e., this ratio is an index that compares the proportion of the number of asphaltene molecules within the nanoaggregates to the number of nanoaggregates in the simulation box. This measure can be thought of as an index of local, quasi-crystalline order that can be found around the asphaltene molecules with a high aggregation potential. We also analyzed the partitioning of the potential energy for interactions within the asphaltene nanoaggregates and clusters. The RDF curves used throughout this work can be found in the ESI material.

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Results and Discussion Effect of the System Dimension Very often, CMD simulations consider a very low number of asphaltene molecules within the simulation box. It is common sense to rely on periodic boundary conditions to account for the total effect of these heavy fractions in oil. Previously, we used 5-8 asphaltene molecules, and we were able to describe generic trends in the formation of nanoaggregates for different heteroatom configurations. Even though these nanoaggregates were limited in size, the aim of these previous works was to calculate, among other features, the shape and the energy of interaction for different molecular structures. 28,29 However, before going any further, it is necessary to analyze the convergence of the results concerning asphaltene aggregation for increasing sizes of simulation boxes with increasing numbers of molecules modeled. This strategy allows one to take into consideration the formation of clusters of nanoaggregates if the concentration of asphaltenes is high enough. However, when increasing the number of asphaltene molecules, one also needs to increase the number of solvent molecules accordingly, which also results in a considerable increase in the simulation time needed. An compromise between the number of asphaltene molecules, accuracy and capturing all relevant physicochemical effects is necessary for such simulations. To achieve such a balance, we studied systems containing 5, 15, 45 and 135 asphaltene molecules in order to determine the minimum number of molecules from which physical-chemical properties can be reproduced. This assessment was performed using the three thermodynamic conditions considered in this work. The challenge of such a study is the calculation effort required: in order to keep the concentration constant across all the studied dimensions, the quantity of solvent molecules should be increased accordingly. For instance, for 135 asphaltene molecules, one has ∼ 17000 toluene molecules.

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T = 298 K, P = 1 bar For most of the systems, the RDFs (Figures S.1-S.3) for systems containing 45 and 135 asphaltene molecules are similar in the 2-24 Å region (and even further). Generally, the π-stacking, H-π and chain-chain interactions are fully described by the boxes containing 45 asphaltenes. This finding indicates that the aggregates have already reached their maximum size at this dimension. The systems that have a lower agreement with this trend are those including AAH, AAI and ADH molecules, which are the molecules with −COOH-type polar chain ends. This result is an indication that asphaltenes containing such chain ends (and given the concentration of −COOH groups present in the simulation box) can form aggregates that continue to grow in size with the increasing number of molecules modeled, i.e., the presence of the polar chains makes it so that the asphaltenes can continue to interact even though the aromatic cores are already “protected ” from the solution. Figure 2 illustrates this behavior. One can then define an indicator to evaluate the convergence of the aggregation properties, ∆R . For each molecular system, this indicator is the difference between the asphalteneasphaltene RDF integral of the system containing 135 molecules (taken as a reference) and the same curve evaluated for systems containing a lower number of asphaltene molecules. Such differences are explicitly plotted and can be found in the ESI†, Figures S.8 and S.9. Figure 3 presents the evolution of this indicator for all the studied systems. The analysis of this figure indicates that ∆R assumes the lowest values for systems containing 45 asphaltene molecules, meaning that these can capture the main interactions governing the aggregation process (either within nanoaggregates or within clusters, since the RDFs are integrated from 0 to ∞). The deviations of this trend are attributed to the presence of polar groups on the ends of chains, which favor the further growth of aggregates via H-bond interactions. The same conclusions can be drawn from the analysis of the CN/N (%) ratio (Figure S.15), where the trends observed for systems containing 5 molecules are not followed for those containing 15: the intensity ratios can be inverted, and the intensity distribution is different between 10


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the two dimensions. The same is also true if the systems containing 15 and 45 molecules are compared, but these findings are not the same when comparing 45 and 135 molecules: in this latter case, the center of mass of the distribution of ratios remains unchanged. T = 298 K, P = 15 bar Under these thermodynamic conditions, in order to reduce the number of studied systems and the redundancy of the results, we considered only 10 molecules instead of the 20 studied for the ambient conditions. Increasing the pressure to which the molecules were subjected during the simulations has the effect of increasing the deviations from the reference of 135 molecules (see Figures S.4 and S.5). Except for the A13 and A14 molecules, the RDFs for systems containing 135 molecules diverge from those of the systems containing 45 molecules for any r higher than 16 Å. This particular r value corresponds to 3rd-neighbor π-stacking and this indicates that aggregates containing more than 3 asphaltene molecules are the most sensitive to pressure. For some molecules, such as ADH, ADF and A13, the peaks attributed to π-stacking beyond the third neighbor are better resolved for the systems containing 135 molecules, indicating that such a pressure gives rise to the formation of asphaltene aggregates that are longer and better organized. Moreover, the Gaussian behavior (signal of the disorder present in the system) at long ranges (the nanoaggregate-nanoaggregate interaction region) is reduced for all the molecules but causes compression of the molecules against one another. This effect is more visible for the curves of systems containing 15 molecules: these curves, regardless of molecule, tend to reach zero faster than those under ambient thermodynamic conditions. In this way, the quantity of nanoaggregates not interacting with others is greatly reduced, i.e., under pressure, the systems are constrained to self-organize into more compact structures, favoring π-stacking, H-π and chain-chain interactions. These observations are derived through the analysis of the differences between the RDFs and their integrals, Figure S.11, where two novel peaks attributed to π-stacking appear for the systems containing 15 molecules. The final snapshots for all the simulated systems can be found in the ESI.

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T = 423 K, P = 15 bar With the increase of both temperature and pressure, one can identify from an analysis of Figures S.6 and S.7 the opposite behavior: high-r regions now present signatures of disorder introduced by the extra kinetic energy provided by the temperature. These signatures of disorder are present for all the systems, even those containing only 5 molecules. Except for some molecules, such as A13 and A14, such disorder (depicted by the intensity of the RDFs for high-r regions) increases with the dimension of the system. This effect is clearly an indication that temperature increases the separation between nanoaggregates. The curves related to the systems containing 45 and 135 molecules are similar for all the thermodynamic conditions and molecular systems. The differences between systems are due either to the presence of polar lateral chains, which allow for an increased level of growth of aggregates, or to the temperature-induced disorder effects that overlap the signatures attributed to aggregation. The analysis of ∆R for the systems containing 45 molecules indicate that these systems are structurally very similarly to those containing 135 molecules, as can be seen in Figures S.13 and S.14. This is true for most of the studied molecules and indicates that even under such thermodynamic conditions, the systems with 45 molecules are capable of reproducing the aggregation behaviors in asphaltene systems and that these systems can capture the aggregation at both the nanoaggregate and cluster scales. Based on this finding, hereafter, the description of the physical-chemical properties of asphaltenes will be presented only for the systems containing 45 asphaltene molecules.

Effect of the Size of the Conjugated Core Once the effect of the dimension of the systems has been studied, we present hereafter the effect of increasing the size of the conjugated core of asphaltene molecules on the aggregation for any given lateral chain.

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Apolar Lateral Chains (n-Cx Hy , x={6, 8, 12, 16}, y={13, 17, 25, 33} and nC6 H13 /n-C16 H33 ) The full RDFs for this case are presented in Figure S.16-S.20. Figure 4 depicts one of these curves for systems containing 5 molecules and having n-C6 H13 as a lateral chain. AAC and ABC systems (7 and 8 fused rings, respectively) present widened π-stacking peaks that are, however, centered on the same r values as in the other systems. The planes formed by these molecules are not perfectly parallel, and the angle between the planes can vary more freely during the simulation, which is clearly an indication of the presence of H-π interactions, which are more probable for such smaller molecules. The analysis of the angles between aromatic planes also corroborates this observation, as can be seen in Figures S.30-S.34. The angles for systems AAC and ABC (Figure S.30) oscillate during all the simulations between 0 and 180◦ , while those for ACC, ADC and A13 (9 and 11 fused rings, respectively) converge more easily to 0 or 180◦ , indicating that even though some H-π interactions are present, π-stacking finishes taking over the overall configuration within the nanoaggregate. When increasing the dimensions of the systems, the π-stacking peaks of A13 are the best resolved, probably due to oxygen atoms in the conjugated core interacting with adjacent molecules via the Coulomb interaction in addition to the traditional van der Waals π-stacking interaction energy. This is better depicted in Figure 5. Regardless of whether the lateral chains are n-C8 H17 , n-C12 H25 or n-C16 H33 , the larger the conjugated cores are, the more the angles between aromatic planes of molecules tend towards planarity during the simulation, thereby reducing the formation of H-π interactions and favoring the formation of π-stacks. This dynamic is easily seen in the analysis of the RDFs in Figures S.17-S.19 and angles in Figures S.31-S.33 where, mainly for the n-C16 H33 lateral chain, the systems are rapidly self-organized for π-stacks when the molecules have 29, 32 or 35 π-carbon atoms (9 or 11 fused rings) in the conjugated core. For the molecules containing 25 and 27 atoms (7 or 8 fused rings - AAF and ABF, for instance), the RDFs peaks beyond the 3rd neighbor are poorly resolved. Undoubtedly, and as expected, larger 13


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conjugated cores govern the formation of nanoaggregates as π-stacks regardless of the size of the lateral chain, and this impact is clearly shown by the better resolution of the peaks and angles of the RDFs between planes. In order to study the asymmetry of the lateral chains for any given molecule, we simulated molecules AAG (25 π-carbon atoms - 7 fused rings) and ADG (35 π-carbon atoms - 11 fused rings), both having one n-C6 H13 chain and one n-C16 H33 chain. The aforementioned observations are also valid in this case, i.e., larger conjugated cores form more organized π-stacks. On the other hand, when analyzing the influence of the size of the conjugated core on the CN/N (%) ratio (calculated for systems containing 135 asphaltene molecules), no particular trend can be obtained in Figures S.23-S.27. Regardless of the type of the lateral chain, the CN/N (%) ratio remains unchanged across the different molecules, indicating that the conjugated core has no effect on the disorder of the system (i.e., no effect on the interaction between nanoaggregates within clusters). Rather, the conjugated core is only responsible for π-stacking interactions within the nanoaggregates. Polar Lateral Chains (n-C6 H13 /n-C5 H10 COOH and n-C16 H33 /n-C15 H30 COOH) The presence of a polar group at the end of a chain, which is capable of forming H-bonds, was studied and is herein reported. The presence of such groups at the ends of chains of asphaltenes is still not confirmed, but experimental work has shown that the asphaltenic phase of bitumen has a high degree of hydrogen bonding interactions. 23,24 The RDFs for these cases are depicted in Figures S.21-S.22, and the angles between planes are presented in Figures S.35-S.36. The first observed characteristic of the RDFs is the presence of a peak centered at 2 Å that is attributed to the formation of these H-bonds between the lateral chains of two different asphaltene molecules. 27,28 Secondly, even if long-range disorder is more present for these systems than for the other aforementioned systems, the systems comprising ADH molecules (35 π-carbon atoms, 11 fused rings, n-C6 H13 /n-C5 H10 COOH) became structured in π-stacks more rapidly than AAH (25 π-carbon atoms, 7 fused rings, n-

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C6 H13 /n-C5 H10 COOH) molecules, a finding that was also observed for apolar lateral chains. This result highlights the role played by the aromatic core on the formation of the nanoaggregates. These conclusions are not completely the same for a longer lateral chain (n-C16 H33 /nC15 H30 COOH): the RDFs for both AAI and ADI molecules differ less than for the former case as these two molecules have very different conjugated core sizes, and in this case, the aggregation process is somehow governed by the lateral chain’s end. Overall, these systems are subjected to three concomitant effects: (i) the influence of the size of the conjugated core on their capacity to form π-stacks; (ii) the presence of a polar chain end that gives rise to H-bond interactions between neighboring molecules and neighboring aggregates; and (iii) the effect of the lateral chain length on stabilizing some of the H-π interactions, as will be discussed in more detail in the next section. The same observations are also valid for the CN/N (%) ratio, as can be seen in Figures S.28-S.29.

Effect of the Length of the Lateral Chains The RDFs associated with this analysis can be found in the ESI† Figures S.37-S.41, and the angles between planes can be found in Figures S.50-S.54. Regardless of the size of the conjugated core, the longer the lateral chain is, the more nanoaggregates one can find in the simulation box for any given conjugated core (see Figure 2). Moreover, the long lateral chains are also linked to the presence of Gaussian disorder that can be observed from the RDF plots for long ranges (the more separated they are, the higher the probability of different interaction geometries). Even though this disorder is observed, the formation of π-stacks seems to be insensitive to the presence of longer lateral chains. As mentioned before, the presence of asymmetric chains, such as in the case of AAG (ADG), induces an intermediary aggregation behavior compared to the molecules that have both lateral chains equal to one of the different chains of AAG (AAC and AAF (ADC and ADF), in this case). This finding indicates that the asymmetry of the chains does not give rise to any new effect on the aggregation pattern of these asphaltene molecules. 15


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Molecules containing polar chain ends, such as AAH and AAI, have similar RDF behaviors, even if the underlying Gaussian disorder at long ranges is different (different possibilities of interactions between nanoaggregates). The presence of polar chain ends also seems to govern the mechanism of aggregation in addition to π-stacking, whereas the length of the lateral chain is responsible only for separating aggregates (see Figure S.37). The analysis of the angles between the aromatic planes corroborates these observations. However, for molecules containing 29 or 35 π-carbon atoms (9 or 11 fused rings) on the conjugated core, with longer chains, H-π interactions seem to be stabilized for longer time periods during the simulation length. These T-shape structures, which are very probable for the molecules with 25 or 27 carbon atoms (7 or 8 fused rings) in the conjugated core, become rarer for molecules that are larger, and only become possible in the presence of these long alkyl lateral chains. The probable mechanism behind this dynamic is that long chains may prevent the solvent or other asphaltene molecules from forcing the T-shaped configuration to collapse to a single π-stacking configuration. Finally, the fact that these observations are valid for any size of conjugated core confirms that the disorder (the separation between nanoaggregates) is introduced by the lateral chains, while the formation of nanoaggregates is governed by the conjugated core forming π-stacking interactions and/or by the presence of polar groups making possible the formation of H-bonds. These observations are better visualized from the analysis of the CN/N (%) ratio, as one can see in Figures S.42-S.49 and in a more condensed way in Figure 6. With the increase in lateral chain length for any given conjugated core size, this ratio decreases by 10-30%, depending on the molecules. For the very same conjugated core and chain length, polar chain ends induce an increase in this ratio of about 20% when compared to apolar chain ends (see Figure S.48). H-bond formation should force asphaltene molecules to be closer together during the simulation, thus increasing the possibility of these molecules interacting through π-stacking. Finally, the fact that the lateral chain length is the dominant factor in the CN/N (%) ratio indicates that long-range interactions (interactions between nanoaggregates)

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are ruled by this structural factor. Consequently, during refining, breaking down these lateral chains (by heating the material under vacuum) would induce the formation of more organized and more closely packed asphaltene aggregates. Conversely, catalytic hydrogenation of the conjugated cores would induce the reduction of the importance of π-stacking aggregation as an aggregation mechanism. In the most extreme case, breaking down the H-bonds would increase the separation between nanoaggregates and reduce their energy of interaction, as will be discussed later. These observations are illustrated by the final snapshots of the ADC, ADF, ADH and ADI systems depicted in Figure 7.

Effect of Thermodynamic Conditions Asphaltenes are known to recover water droplets in water-in-oil emulsions (W/O), causing several problems during the refining of heavy crude oil. Asphaltenes form an interface between the water and the oil, stabilizing the water droplets and making it more difficult to remove these droplets. 6,7 The process of dewatering/desalting requires temperatures of approximately 150 ◦ C (423 K) and pressures of approximately 15 bar. To gain some insight into the influence of these thermodynamic conditions on the aggregation of asphaltenes in terms of the function of their molecular architecture, we have also analyzed our CMD simulations to isolate this parameter. The initial configurations of these simulations are the final configuration of the 60-ns simulation at ambient temperature and pressure conditions. Before the production phase of the molecular dynamics simulations (also equal to 60 ns) under the desired thermodynamic conditions, a stabilization phase of 3 ns was again imposed. The structural extremes of the molecules presented in Table 1, i.e., the AAC and AAF, ADC and ADF molecules (apolar side chains with 6 or 16 linear carbon atoms, 25 or 35 π-carbon atoms in the conjugated core) were picked for the sake of simplicity of comparison. The RDFs for associated with this analysis can be found in the ESI† Figures S.55-S.64 and the angles between planes are in Figures S.79-S.88. The energy of interaction between asphaltene molecules and its decomposition into elec17


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trostatic and van der Waals parts for each molecule were also analyzed. Two representations of this analysis were produced: (i) the mean energy of interaction and its decomposition for each molecule, calculated during the 60 ns of dynamics; and (ii) the total energy of interaction calculated at each frame in dynamics simulation time, the standard deviation of which was also taken into account. Both representations were produced for the systems containing 135 molecules under different thermodynamic conditions. Given that the systems are composed of molecules with different molecular architectures, two scaling conditions were used: (i) the total energy of interaction is divided by the number of atoms in the asphaltene molecules within the system; and (ii) this energy is divided by the number of π-carbon atoms in the conjugated core of all the asphaltene molecules within the simulation box. For T = 298 K and P = 1 bar, these two representations (1 and 2) and two scaling conditions (1a and 1b) are depicted in the ESI† Figures S.65-S.67. At ambient conditions, the energy of interaction for all the molecules ranges between -1.0 and -2.0 kcal·mol−1 per π-carbon atom within the simulation box, as can be seen from Figure S.66. The Coulomb (electrostatic) fraction is near zero for all the molecules and is negative for those containing polar chain ends and is positive for the molecules containing 27 carbon atoms in the conjugated core, mainly because of the quinoid structure of these systems. The aggregation process is mainly dominated by van der Waals (described by a Lenard-Jones potential) forces regardless of the molecule type. The representation presented in Figure S.67 was obtained by enveloping the average asphaltene-asphaltene total energy of interaction by Gaussian functions, the full width of which at half maximum equals the standard deviation of this energy throughout the whole simulation. With these two representations in hand, it is interesting to note that the molecules with polar chain ends have an increased energy of interaction and the Gaussian curves describing these energies are also wider.

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Effect of Pressure Regardless of the quantity of AAC molecules in the simulation box, an increase in pressure induces the reduction of the disorder at long ranges (the collapse of nanoaggregates against each other). A pressure reduction also stabilizes the formation of T-shape structures that exist through H-π interactions, which can be seen in the analysis of the angles between the aromatic planes. This finding is probably due to the fact that pressure freezes molecular structures, thereby reducing the possibility of dissociation in this configuration. For a longer lateral chain, as is the case of AAF, in addition to these observations, the short-range disorder is also reduced with an increase in the π-stacking. Similarly, the stabilization of H-π interactions and the reduction of disorder are also identified for ADC and ADF molecules. However, given the extended size of their conjugated cores, once the π-stacks are in place, the aggregation mechanism is not altered by the pressure, which indicates that this effect is only detected in the interactions between nano-aggregates, not within them. AAH- and AAI-based systems also exhibit a reduction in disorder, even with an increase in π-stacking, which is clearly the case for small systems (5 or 15 molecules), i.e., the pressure forces the systems to be structured in π-stacks. Larger systems develop a wide Gaussian disorder band centered at 16 Å, which is also the case for ADH- and ADI-based systems: the difference being that this band is now centered at longer ranges. This result can be attributed to the fixing of the positions of the nanoaggregates within the cluster architecture. This disorder band can also be partially attributed to the H-bond interactions between different nano-aggregates via the −COOH final groups. The pressure reduces the intermolecular distance, thereby increasing the probability of forming larger π-stacks. The same effects are again observed for A13- and A14-based systems, which also exhibit an increase of π-stacking. Several new peaks can now be resolved in the RDF curves for the systems containing 15, 45 and 135 molecules. That these peaks are not visible for 5-molecules systems indicates that nanoaggregates are naturally formed by more than 5 molecules and that this number can sometimes be greater than 15 when different nanoaggregates are compressed against each 19


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other. Finally, one can deduce from the analysis of Figure S.68-S.70 that pressure increases the energies of interaction for all the studied molecules under these conditions. These energies assume values ranging between -1.5 and -3.0 kcal·mol−1 per π-carbon atom, representing an increase of ∼ 33%. Moreover, pressure also impacts the width of the Gaussian curves enveloping each of these energy values: these curves are now narrower than those found under ambient conditions and are more separated along the energy scale. Effect of the Temperature Increasing temperature gives rise to long-range disorder at a higher level than can be found at ambient conditions, i.e., the nanoaggregates have now an increased probability of interacting with each other. Additionally, temperature does not seem to have an effect on the π-stacking structure, which indicates that the influence of temperature is limited to the interactions between nanoaggregates only, not within them. Rather than stabilizing the H-π interactions induced by the pressure, increasing the temperature seems to cancel this effect out, reducing the probability of finding T-shape structures. These observations are made for AAC- and AAF-based systems. For the molecules with larger conjugated cores, such as ADC, the aggregation mechanism is not impacted by this thermodynamic property, i.e., once the πstacks are in place, they are not disturbed by temperature because with a such extended conjugated core, the energy of interaction is strong enough to resist to the extra kinetic energy of the system. Keeping this same conjugated core but increasing the length of the lateral chain, as is the case for ADF, the effect of the temperature is identified in the level of disorder (i.e., how nano-aggregates interact and their separation). With this in mind, we can easily say that longer lateral chains are more sensitive to the effect of temperature only because of the perturbation of the interactions among nanoaggregates, not within them. In other words, at this temperature, there is not enough energy to break nanoaggregates apart, and the only interactions that are impacted by temperature are the steric repulsion of lateral chains and the H-π interactions. Similarly, for the molecules having polar chain ends,

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such as AAH, AAI, ADH and ADI, temperature is not capable of breaking the Hydrogen bonds apart but again introduces some degree of disorder between the nanoaggregates for the AAI and ADI systems due to their long lateral chains. Generally speaking, neither pressure nor temperature reduce the aggregation of systems presenting H-bonds. Moreover, these thermodynamic conditions seems to increase the aggregation strength in these systems. From Figure 8, the CN/N (%) ratios for the systems containing 135 molecules under all the thermodynamic conditions clearly show the molecules that are the most sensitive to the effect of temperature. The molecules containing polar chain ends are visibly less impacted by this effect, as aforementioned. Conversely, the smaller the conjugated core and the shorter the lateral length, the more the molecule is sensitive to the effect of temperature as it is responsible for separating the nanoaggregates from one another. A general overview of these effects is illustrated in Figure 9. From Figure S.71-S.73, one can verify that temperature and pressure together induce energies of interactions that range between -1.0 and -2.5 kcal·mol−1 per π-carbon atom, which are values closer to those found under ambient conditions. However, the narrowing of the Gaussian curves that was observed when pressure was included is still preserved, as is the separation between the peaks associated with each of these molecules. If we assume that a higher energy of interaction results in larger aggregates, we could then associate these curves with the size distribution of the asphaltene aggregates across all the studied molecules. In a typical chromatography experiment, molecules are excluded by their sizes as they pass through the column. If no interaction with the column is assumed, if a heavy crude oil containing these ten molecules in equal parts is submitted to such an experiment, its chromatogram would be the result of all these curves added together. This representation was done and is presented in Figure 10, where the blue, green and red curve are the resultant addition of each individual Gaussian at each thermodynamic condition studied in this word. One can then visualize the spreading of the energy of interaction between asphaltenes for a crude oil that is composed of equal parts of each molecule pre-

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sented herein. Interestingly, although neither pressure nor pressure and temperature has an effect in reducing the interaction energies, these factors separate the peaks across the energy range, i.e., these thermodynamic properties, though not favoring any disaggregation process, provide an energy gradient that can be used in the successful separation of nanoaggregates. A more descriptive version of this figure is presented in the ESI, Figure S.74, where one can clearly verify that: 1 - molecules containing polar lateral chains interact more strongly under the effect of pressure and temperature; 2 - molecules containing apolar lateral chains interact more strongly under the effect of the pressure, but this effect can be, to some extent, counterbalanced by the inclusion of temperature, which is only valid for molecules containing small conjugated cores; and 3 - molecules containing extended conjugated cores will, on the other side, also interact more strongly with the effect of temperature. These results indicate that the thermodynamic conditions used nowadays during the dewatering/desalting processes may be capable of breaking down only nanoaggregates composed of molecules having small (under 29 π-carbon atoms - 8 fused rings) conjugated cores, even though some increase in the mean distance between nanoaggregates can be observed for other systems. For other larger molecules, or for those with polar chain ends, an increase in the interaction energies can be noted instead under these conditions. 8 This observation proves that the design, by molecular modeling techniques, of new physical processes to yield less-aggregated crude oils during refining is still an open challenge.

Conclusions In this work, the effects of molecular structure (conjugated core size, lateral chain length) and thermodynamic conditions (temperature and pressure) on the aggregation pattern of asphaltene molecules were studied. This examination was only possible by the analysis of several factors and data treatments, including radial distribution functions, the angles between the aromatic planes and the interaction energies between asphaltenes for each frame

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of the simulation. Systems with 45 asphaltenes in the simulation boxes reproduce qualitatively the results obtained for those systems containing 135 molecules, while the boxes containing 5 or 15 molecules do not include enough molecules to account for the interactions between nanoaggregates, what may indicate that the average number of molecules in a nanoaggregate is of the order of 15 molecules. Systems containing 45 molecules can thereby capture the aggregation behavior within and between nanoaggregates. Moreover, molecules having polar chain ends do not always follow this trend, which is an indication that this structural characteristic has the effect of increasing the growth level of the aggregates mediated by the H-bonds formed between the polar groups. The size of the conjugated core is the main factor governing the formation of π-stacks, and this is the main aggregation mechanism for molecules having more than 29 π-carbon atoms in its structure. Molecules having 25 or 27 of these atoms may also interact by H-π interactions as well, whereas this type of interaction is almost non-existent for larger aromatic cores. On the other hand, the length of the lateral chains was found to separate the nanoaggregates and to control their number, which nonetheless does not avoid the formation of π-stacks. Moreover, the molecules with asymmetric lateral chains displayed intermediary behaviors between the extremes of this chain. This finding means that the asymmetry does not give rise to any new interaction pattern (i.e., the effects of each moiety are additive). Finally, the polar chain ends govern the aggregation pattern and the shape of the nanoaggregates. The inclusion of pressure only reduces long-range disorder (i.e., interaction between nanoaggregates) and stabilizes H-π interactions. Temperature, in contrast, introduces more long-range disorder, but this disorder is clearly not enough to dissociate the nanoaggregates, mainly when their interaction is mediated by H-bonds. For these systems characterized by H-bonds, pressure and temperature have the counter-effect of increasing the aggregation strength by π-stacking. For apolar chain ends, temperature can then introduce disorder and separate the nanoaggregates without having an observable effect within the nanoaggregates

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themselves. Last, the results presented in this work may reduce the number of parameters to examine in forthcoming experiments to understand the asphaltene aggregation phenomenon. Additionally, we have shown that the thermodynamic conditions used in the desalting process are not enough to break down nanoaggregates or reduce their interaction energies but can indeed introduce an energy gradient that favors their separation.

Acknowledgement The authors would like to thank to the DN (Direction du Numérique) from Université de Pau et des Pays de l’Adour, MCIA (Mésocentre de Calcul Intensif Aquitain) and GENCI-CINES (Grant 2017-c2016087698) for providing the computation power needed for this project. Isifor-Carnot Institute and Total Refining & Chemicals are also acknowledged for their financial support to this research project.

References (1) Ghose, M. K. Challenges in delinking economic growth and environmental degradation for sustainable development. TIDEE: TERI Inf. Dig. Energy Environ. 2016, 15, 151– 162. (2) Mullins, O. C. The asphaltenes. Annu. Rev. Anal. Chem. 2011, 4, 393–418. (3) Eyssautier, J.; Levitz, P.; Espinat, D.; Jestin, J.; Gummel, J.; Grillo, I.; Barré, L. Insight into asphaltene nanoaggregate structure inferred by small angle neutron and X-ray scattering. J. Phys. Chem. B 2011, 115, 6827–6837. (4) Adams, J. J. Asphaltene adsorption, a literature review. Energy Fuels 2014, 28, 2831– 2856.

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(5) Benamsili, L.; Korb, J.-P.; Hamon, G.; Louis-Joseph, A.; Bouyssiere, B.; Zhou, H.; Bryant, R. G. Multi-dimensional nuclear magnetic resonance characterizations of dynamics and saturations of brine/crude oil/mud filtrate mixtures confined in rocks: The role of asphaltene. Energy Fuels 2013, 28, 1629–1640. (6) Ligiero, L. M.; Bouriat, P.; Dicharry, C.; Passade-Boupat, N.; Lalli, P. M.; Rodgers, R. P.; Barrère-Mangote, C.; Giusti, P.; Bouyssiere, B. Characterization of crude oil interfacial material isolated by the wet silica method. Part I–Gel permeation chromatography inductively coupled plasma high resolution mass spectrometry analysis. Energy Fuels 2017, 31, 1065–1071. (7) Ligiero, L. M.; Dicharry, C.; Passade-Boupat, N.; Bouyssiere, B.; Lalli, P. M.; Rodgers, R. P.; Barrère-Mangote, C.; Giusti, P.; Bouriat, P. Characterization of crude oil interfacial material isolated by the wet silica method. Part II–Dilatational and shear interfacial properties. Energy Fuels 2017, 31, 1072–1081. (8) Mullins, O. C.; Seifert, D. J.; Zuo, J. Y.; Zeybek, M. Clusters of asphaltene nanoaggregates observed in oilfield reservoirs. Energy Fuels 2013, 27, 1752–1761. (9) others„ et al. Advances in asphaltene science and the Yen–Mullins model. Energy Fuels 2012, 26, 3986–4003. (10) Andreatta, G.; Bostrom, N.; Mullins, O. C. High-Q ultrasonic determination of the critical nanoaggregate concentration of asphaltenes and the critical micelle concentration of standard surfactants. Langmuir 2005, 21, 2728–2736. (11) Mullins, O. C.; Betancourt, S. S.; Cribbs, M. E.; Dubost, F. X.; Creek, J. L.; Andrews, A. B.; Venkataramanan, L. The colloidal structure of crude oil and the structure of oil reservoirs. Energy Fuels 2007, 21, 2785–2794. (12) Barré, L.; Jestin, J.; Morisset, A.; Palermo, T.; Simon, S. Relation between nanoscale

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structure of asphaltene aggregates and their macroscopic solution properties. Oil Gas Sci. Technol.-Rev. Inst. Fr. Pet. 2009, 64, 617–628. (13) Majumdar, R. D.; Montina, T.; Mullins, O.; Gerken, M.; Hazendonk, P. Insights into asphaltene aggregate structure using ultrafast MAS solid-state 1 H NMR spectroscopy. Fuel 2017, 193, 359–368. (14) Headen, T.; Boek, E.; Jackson, G.; Totton, T.; Müller, E. Simulation of asphaltene aggregation through molecular dynamics: Insights and limitations. Energy Fuels 2017, 31, 1108–1125. (15) Pacheco-Sánchez, J.; Alvarez-Ramirez, F.; Martínez-Magadán, J. Morphology of aggregated asphaltene structural models. Energy Fuels 2004, 18, 1676–1686. (16) Rogel, E. Studies on asphaltene aggregation via computational chemistry. Colloids Surf., A 1995, 104, 85–93. (17) Zhang, L.; Greenfield, M. L. Molecular orientation in model asphalts using molecular simulation. Energy Fuels 2007, 21, 1102–1111. (18) Wang, J.; Gayatri, M. A.; Ferguson, A. L. Mesoscale simulation and machine learning of asphaltene aggregation phase behavior and molecular assembly landscapes. J. Phys. Chem. B 2017, 121, 4923–4944. (19) Sedghi, M.; Goual, L.; Welch, W.; Kubelka, J. Effect of asphaltene structure on association and aggregation using molecular dynamics. J. Phys. Chem. B 2013, 117, 5765–5776. (20) Liu, J.; Zhao, Y.; Ren, S. Molecular dynamics simulation of self-aggregation of asphaltenes at an oil/water interface: Formation and destruction of the asphaltene protective film. Energy Fuels 2015, 29, 1233–1242.

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(21) Yaseen, S.; Mansoori, G. A. Molecular dynamics studies of interaction between asphaltenes and solvents. J. Pet. Sci. Eng. 2017, 156, 118–124. (22) Miller, E. D.; Jones, M. L.; Jankowski, E. Enhanced computational sampling of perylene and perylothiophene packing with rigid-body models. ACS Omega 2017, 2, 353–362. (23) Rogel, E. Simulation of interactions in asphaltene aggregates. Energy Fuels 2000, 14, 566–574. (24) Redelius, P. Bitumen solubility model using Hansen solubility parameter. Energy Fuels 2004, 18, 1087–1092. (25) Sabbah, H.; Morrow, A. L.; Pomerantz, A. E.; Zare, R. N. Evidence for island structures as the dominant architecture of asphaltenes. Energy Fuels 2011, 25, 1597–1604. (26) Schuler, B.; Meyer, G.; Peña, D.; Mullins, O. C.; Gross, L. Unraveling the molecular structures of asphaltenes by atomic force microscopy. J. Am. Chem. Soc. 2015, 137, 9870–9876. (27) Santos Silva, H.; Sodero, A. C. R.; Guevara Level, P.; Bouyssiere, B.; Korb, J.-P.; Carrier, H.; Alfarra, A.; Bégué, D.; Baraille, I. Investigation of the effect of sulfur heteroatom on asphaltene aggregation. Energy Fuels 2016, 30, 4758–4766. (28) Santos Silva, H.; Sodero, A. C.; Bouyssiere, B.; Carrier, H.; Korb, J.-P.; Alfarra, A.; Vallverdu, G.; Bégué, D.; Baraille, I. Molecular dynamics study of nanoaggregation in asphaltene mixtures: Effects of the N, O, and S heteroatoms. Energy Fuels 2016, 30, 5656–5664. (29) Santos Silva, H.; Sodero, A. C.; Korb, J.-P.; Alfarra, A.; Giusti, P.; Vallverdu, G.; Bégué, D.; Baraille, I.; Bouyssiere, B. The role of metalloporphyrins on the physicalchemical properties of petroleum fluids. Fuel 2017, 188, 374–381.

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(30) Varadaraj, R.; Patel, R. D.; Hemrajani, R. R.; Rossetti, S. J.; Savage, D. W. Oil desalting and dewatering. 2006; US Patent 7,008,536. (31) Vafajoo, L.; Ganjian, K.; Fattahi, M. Influence of key parameters on crude oil desalting: An experimental and theoretical study. J. Pet. Sci. Eng. 2012, 90, 107–111. (32) van Gunsteren, W. F.; Daura, X.; Mark, A. E. Encyclopedia of Computational Chemistry; John Wiley & Sons, Ltd: Chichester, UK, 2002. (33) Van Der Spoel, D.; Lindahl, E.; Hess, B.; Groenhof, G.; Mark, A. E.; Berendsen, H. J. GROMACS: Fast, flexible, and free. J. Comput. Chem. 2005, 26, 1701–1718.

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Table 1: Definition of All the 20 Studied Molecules in This Work and the Labeling System. NC Stands for Number of Conjugated Carbon Atoms. Both chains present in the molecules are identical and when this is not the case, it is indicated by two chain labels separated by a slash symbol. NC nC6 H13 25 27 29 35 32

AAC ABC ACC ADC A13

nC8 H17

nC12 H25

nC16 H33

AAD ADD -

AAE ADE -

AAF ABF ACF ADF A14

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n-C6 H13 / nC16 H33 AAG ADG -


n-C6 H13 / nC5 H10 COOH AAH ADH -

n-C16 H33 / nC15 H30 COOH AAI ADI -

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Table 2: Details for the Molecules Presented in Table 1. NC, NFR, DBE, Mw and KMD Stand for the Number of Conjugated Carbon Atoms, Number of Fused Rings, Double Bond Equivalent, and Kendrick Mass Defect (KMD), Respectively. Molecular Weight Is Expressed in g·mol−1 Molecule NC NFR DBE AAC 25 7 20 AAD 25 7 20 AAE 25 7 20 AAF 25 7 20 AAG 25 7 20 AAH 25 7 20 AAI 25 7 20 ABC 27 8 22 ABF 27 8 22 ACC 29 9 24 ACF 29 9 24 ADC 35 11 29 ADD 35 11 29 ADE 35 11 29 ADF 35 11 29 ADG 35 11 29 ADH 35 11 29 ADI 35 11 29 A13 32 9 25 A14 32 9 25

Class N1 N1 N1 N1 N1 N1 N1 N1 N1 N1 N1 N1 N1 N1 N1 N1 N1 N1 O3 O3

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Mw 495.7 551.8 664.0 776.2 635.9 525.7 806.2 518.7 800.2 543.7 822.2 617.8 673.9 786.1 898.3 758.1 647.8 928.3 630.8 912.3


KMD 0.739002 0.739002 0.739002 0.739002 0.739002 0.679713 0.679713 0.712204 0.712204 0.685405 0.685405 0.618409 0.618409 0.618409 0.618409 0.618409 0.559119 0.559119 0.609033 0.609033

H/C 1.000 1.097 1.245 1.351 1.213 0.946 1.316 0.949 1.305 0.902 1.262 0.808 0.902 1.051 1.164 1.017 0.766 1.134 0.954 1.281

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AAC

AAH

AAF

AAI

Figure 2: Final snapshots of AAC, AAH, AAF and AAI containing 45 asphaltene molecules each depicting the formation of nanoaggregates and clusters at T = 298 K and P = 1 bar and the influence of the lateral chain’s length and polarity. One can note that longer lateral chains increase the distance between nanoaggregates (AAC and AAF) and that the presence of polar chain ends induces the opposite effect for lateral chains of the same length (AAC/AAH and AAF/AAI).

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AAC

ADC

A13 Figure 5: Final snapshots of AAC, ADC and A13, both having n-C6 H13 as a lateral chain under T = 298 K and P = 1 bar thermodynamic conditions indicating the effect of the number of fused rings on the formation of the nanoaggregate.

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Figure 7: Final snapshots of ADC, ADF, ADH and ADI, all having 35 π-carbon atoms (11 fused rings) in the conjugated core at T = 298 K and P = 1 bar thermodynamic conditions, illustrating the effect of lateral chain length on the patterns of clusters of nanoaggregates.

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T = 298 K, P = 1 bar

T = 298 K, P = 15 bar

T = 423 K, P = 15 bar

Figure 9: Final snapshots of CMD simulations of systems containing 135 molecules of A13 under all the three thermodynamic conditions studied in this work.

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Sensitivity of Asphaltene Aggregation toward the Molecular

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