Dynamic Molecular Modeling and Experimental Approach of

Article Cite This: J. Chem. Eng. Data XXXX, XXX, XXX−XXX

pubs.acs.org/jced

Dynamic Molecular Modeling and Experimental Approach of Fluorocarbon Surfactant-Functionalized SiO2 Nanoparticles for GasWettability Alteration on Sandstones Ivan Moncayo-Riascos,* Camilo A. Franco, and Farid B. Cortés*

J. Chem. Eng. Data Downloaded from pubs.acs.org by UNIV OF LOUISIANA AT LAFAYETTE on 03/25/19. For personal use only.

Grupo de Investigación en Fenómenos de Superficie − Michael Polanyi, Facultad de Minas, Universidad Nacional de Colombia Sede Medellín, Kra 80 No. 65−223, Medellín, Colombia S Supporting Information *

ABSTRACT: Fluorocarbon surfactants have been widely used to promote gas-wetting alteration of sandstones with the objective of inhibiting the formation damage due to condensate banking and hence increasing the oil recovery. This study is focused on understanding the behavior of the wettability alteration from a liquid-wet state to gas-wettability by SiO2 nanoparticles functionalized with 20 wt % of a commercial fluorocarbon surfactant Silnyl FSJ (SY) using molecular dynamics simulations and experimental approaches. The SY-functionalized SiO2 nanoparticles were synthesized by an incipient wetness method. Then, three nanofluids were obtained by dispersing the modified SiO2 nanoparticles at 0.3, 0.5, and 0.7 wt % in a KCl brine (2 wt %) and were employed for wettability alteration of the oil-wet sandstone samples under room conditions. Changes of the samples’ wettability were estimated by experimental contact angle measurements in brine/ rock/air and n-decane/rock/air systems. The theoretical evaluation was made using molecular dynamics for reproducing the coating of the sandstone samples with the SY-functionalized nanoparticles and the contact angles measured experimentally. Further, the wettability alteration to a gas-wet system is described from a physical insight based on the thermodynamic analysis of the interaction energies of nanoparticles−liquid, surfactant−liquid, and liquid−liquid. The molecular model developed in this study allows predictive calculations of the contact angle of liquid droplets, with deviations lower than 7% regarding the experimental value. The theoretical approach allows optimizing the use of surfactant-functionalized nanoparticles for promoting the wettability alteration from liquid-wet to gas-wet state, which can lead to cost savings and increase the performance of improved and enhanced oil recovery processes.

1. INTRODUCTION Gas-condensate deposits have been formed at high pressures and temperatures and are composed mainly of hydrocarbons of low and medium molecular weight in the gaseous state.1−3 Once production has begun, the reservoir pressure is reduced continuously, and the lightest compounds start to condense when the saturation point pressure is reached.1,4,5 As the pressure decreases at a constant temperature, the percentage of condensate deposited in the reservoir increases until a maximum stored by capillary forces, reducing the permeability of the porous medium and hence the productivity of the reservoir.1,6 This phenomenon is known as formation damage by condensate banking.7,8 Further, several researchers have evaluated different chemicals, mainly based on fluorocarbon surfactant (FS)9−14 solutions and FS-based nanofluids3,15−18 for being used in improved (IOR) and enhanced oil recovery (EOR) processes to mobilize the condensate and increase the oil recovery. The fluorocarbon structures have been widely studied8,19−22 due to the high thermal and chemical stability and their amphiphilic properties.8,20,23,24 Initially, high molecular weight surfactants © XXXX American Chemical Society

and polymers were tested to promote gas-wetting surfaces, obtaining good results in the technical evaluations (the gaswetting state was promoted by the coating)25−27 but with environmental and health implications due to the toxicity of these compounds.28−30 Contact angles promoted by these types of surfactants range between 60 and 130° and 0 and 60° for water and oil phases, respectively.8,20,31 However, the fluorocarbon surfactants with short chain lengths stand out as an alternative due to their low toxicity and high ability to promote gas-wetting surfaces, leading to contact angles in the same range reported for surfactants of longer fluorocarbon chains.17,31,32 Despite the valuable experimental findings reported in the literature, an understanding of the interactions between the fluorocarbon surfactants and nanoparticles as well as the role in Special Issue: Latin America Received: October 11, 2018 Accepted: March 12, 2019

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DOI: 10.1021/acs.jced.8b00910 J. Chem. Eng. Data XXXX, XXX, XXX−XXX

Journal of Chemical & Engineering Data

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through the incipient wetness technique50,51 using a 20 wt % SY solution in a 2 wt % KCl (99%, Panreac, USA) brine according to the procedure described in a previous study.17 The obtained material was centrifuged, washed with excess deionized water, and finally dried at 393 K. The functionalized nanoparticles were characterized according to their surface area (SBET) by N2 adsorption isotherms using an Autosorb-1 from Quantachrome. Also, the surface characterization was performed using an IRAffinity-1 Fourier transform infrared (FTIR) spectrophotometer provided by Shimadzu (Japan) to determine the presence of fluorocarbon surfactant on the hybrid nanoparticles.51,52 Desorption experiments were performed to verify the amount of SY on the nanoparticles and were carried out using a 2 wt % KCl brine by triplicate on the basis of a previous study.17 Thermogravimetric analyses were carried out in a thermogravimetric analyzer Q-50 (TAInstrument, New Castle) to quantify the amount of surfactant functionalized on the surface of the SiO2 nanoparticles. The nanofluids were prepared using the SY-functionalized nanoparticles at different concentrations of 0.3, 0.5, and 0.7 wt %, in a 2 wt % KCl brine. The obtained nanofluids were stirred at 300 rpm and then homogenized using an ultrasonic bath at 298 K. Further, the hydrodynamic diameter of the SYfunctionalized nanoparticles in the nanofluids was determined through dynamic light scattering (DLS) measurements with a nanoplus-3 from Micromeritics (Norcross, ATL).53,54 Detailed information about the nanoparticle and nanofluid synthesis and characterization can be found elsewhere.17 It is worth mentioning that the employed nanofluids do not have any free SY surfactant in the KCl brine, which allows costs reduction and process optimization in comparison with previous developments where the fluorocarbon surfactant was up to 4.6 wt % (not adsorbed over the nanoparticle) in solution.17 2.2. Contact Angle Measurements. For contact angle measurements (CAMs), sandstone samples with a diameter of 3.8 cm and length of 4.83 cm were obtained from an outcrop sandstone and washed with toluene (99%, St. Louis, MO, USA) and ethanol (99.9%, St. Louis, MO, USA). The sandstone samples were restored to an oil-wet state using an extra heavy crude oil of 7°API and 13 wt % of asphaltenes following the procedure proposed by Donaldson et al.17,55 Hereafter, the term “restored sample” was used to refer to the sandstone with an oil-wet state. Each restored sample was soaked for 48 h at 313 K in the selected nanofluids to alter the wettability under static conditions.17,56 Afterward, the samples are removed from the nanofluids and dried at 313 K. The CAMs were carried out according to the method proposed by Lamour et al.,17,57 for brine/rock/air and n-decane/rock/air systems, where a droplet of liquid was injected using a 5 μL syringe over the sandstone surface in five different positions at room temperature. Further, a photograph of each droplet was taken using a digital camera and contact angles are estimated by defining sphere- or ellipse-like approximations using the LayOut software (Trimble Inc., Sunnyvale, CA).57 The uncertainties of the CAMs are associated with the standard deviation of the mean, with a corresponding confidence level of 95%.58 The ndecane and a brine, composed of a 2 wt % KCl solution in deionized water, were employed in the CAMs. In short, a total of 10 experimental contact angles were measured; 5 for n-decane and 5 for brine were evaluated for the restored sample before and after coating with free Silnyl FSJ (SY) fluorocarbon surfactant and 0.3, 0.5, and 0.7 wt % of

altering the wettability from liquid- to gas-wet conditions has not been reached completely yet under a phenomenological point of view.33 In this sense, molecular dynamics (MD) simulations contribute to obtaining valuable physical insights from an atomistic description of the heterogeneous system, describing how the interaction energies change due to the proposed treatment (wettability modifiers such as nanoparticles or surfactants). Hence, the molecular simulations have become a powerful tool to understand the interfacial phenomena based on the study of the atomistic interactions by in silico experiments.34−39 Molecular dynamics models have widely been used to understand the interfacial phenomena in the IOR/EOR process,34,40,41 wettability alteration,36−38 and interfacial tension reduction,42−46 among others. In the specific case of the fluorocarbon surfactant applications, molecular dynamics studies are focused on the wettability alteration19,36,37 and ultralow interfacial tension.46−48 The results reported show a suitable representation by molecular dynamics simulations of the contact angles of water and oil droplets measured experimentally. Also, in wettability alteration evaluations from an initial water-wetting state to a gas-wetting state, the calculation of the interaction energies shows an important reduction of the solid−liquid interaction promoted by the fluorocarbon surfactant, at least of 49 and 37% for water and n-decane, respectively.37,38 Sepehrinia and Mohammadi49 studied through molecular dynamics simulations the wettability alteration using fluorinated SiO2 nanoparticles. Results obtained by the authors showed that the nanoparticle−mineral surface interaction is greater than the nanoparticle−nanoparticle interaction in both n-decane and water-filled pores, indicating that the spatial distribution of the nanofluid coating leads to the removal of the liquid blockage. In this work, an improved method to alter the wettability of sandstones is reported, which reduces the surfactant amount needed to promote a gas-wetting state through the addition of grafted surfactant over the silica nanoparticles. The experimental method developed is based on SiO2 nanoparticle functionalization with a fluorocarbon surfactant for the formulation of nanofluids at different nanoparticle concentrations that allow the wettability alteration process. Wettability alteration of sandstone cores was evaluated through contact angle measurements for n-decane and brine, both experimentally and theoretically. The theoretical model was based on MD simulations, which contributes to understanding of the phenomenon from an atomistic description. Further, the interaction energies involved in the wettability alteration process were evaluated to obtain physical insights of how the FS-grafted silica nanoparticles improve the wettability alteration. Despite that MD simulations have been widely used to study the wettability alteration, to the best of our knowledge, there are no studies reporting the effect of FSfunctionalized SiO2 nanoparticles in wettability alteration by molecular dynamics simulations jointly with an experimental approach. Finally, it is worth mentioning that the results obtained are a valuable contribution to increase the efficiency of IOR/EOR applications using nanofluid-based solutions.

2. EXPERIMENTAL SECTION 2.1. Nanofluid Preparation and Characterization. Silnyl FSJ (SY, 46 wt % of fluorocarbon surfactant, Siliconas ́ y Quimicos S.A.S, Colombia) was employed for nanofluid preparation and SiO2 nanoparticle (Sigma-Aldrich, St. Louis, MO) functionalization. SiO2 nanoparticles were functionalized B



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amount of surfactant needed in each case. In order to reproduce the conditions for the experimental contact angle measurements, all droplet formation simulations were carried out at 298 K. Before starting the theoretical evaluation, a preliminary assessment was performed to determine the molecular structure of the surfactant. Figure 2 shows a generic molecular

SY-functionalized nanoparticles. All CAMs were carried out under room conditions (298 K and 1 atm).

3. METHODOLOGY FOR THEORETICAL EVALUATIONS Figure 1 shows a scheme of the methodology followed in the theoretical evaluation for representing the experimental procedures described in the section above.

Figure 2. Generic molecular structure of the Silnyl FSJ fluorocarbon surfactant.

structure of the Silnyl FSJ surfactant evaluated in this study. The surfactant’s structure is composed by a polar head, with an ester functional group, while the surfactant’s chain contains a fluorocarbon structure which is a function of the n parameter that defines the fluorocarbon chain length. Therefore, the preliminary evaluation consisted of calculating the surfactant density using molecular dynamics simulations by varying the n parameter. The number of carbon atoms that compose the fluorocarbon chain was determined using an experimental density of 1.12 g/cm3 reported for the surfactant solution. The surfactant density calculation, for each n value, was carried out through an NPT ensemble (298 K and 1 atm), during 5 ns with a time step of 1 fs using periodic boundaries in all directions. The oil-wet state of the restored sample was represented through the proper description of the adhesion and cohesion energies. Adhesion energies are related to the intensity of interaction between the liquid molecules and the solid surface, while the cohesion energies consider the interaction intensities between the liquid molecules.59−61 Hence, a specific wettability state of a surface is defined by the competition of these energies, whereby for low contact angles the adhesion energies overcome the cohesion energies, and vice versa. Figure 3 shows a scheme of the system evaluated by molecular dynamics, in which the liquid molecules are

Figure 1. Representation scheme of the experimental procedures reproduced by molecular dynamics.

In the experimental evaluation, a heterogeneous system was studied, composed by a solid phase (restored sample and functionalized nanoparticles), a liquid phase (SY surfactant, brine, and n-decane), and a gas phase (air). In the theoretical approach, a simplified system was evaluated, in which the solid phase was described using two unlike representations. In a previous work,36 we found out that the 10-4-3 wall potential allows obtaining a reliable reproduction of a specific wetting state through the tuning of the energetic parameter of the wall potential; this approach was used to represent the restored rock. On the other hand, the silica nanoparticles were described using an atomistic description, similarly to representing the liquid phase composed by SY surfactant, brine, and n-decane (all molecular potentials are described in section 4). Meanwhile, the gas phase was represented by an empty space among the liquid molecules and the edge of the simulation box. This representation has been used, even for systems with an atomistic description of the surface where no significant deviations were found between the contact angles calculated with an atomistic representation of air and by an empty space for pressures up to 150 bar.59 Hence, this computational representation allows reproducing the unbalanced forces at the liquid−gas interface by the vacuum−liquid interface. As shown in Figure 1, in the theoretical evaluation, four steps were represented, namely, (i) initial wettability state of the restored sandstone sample, (ii) functionalization of nanoparticles with the SY surfactant, (iii) the restored sample coating with the SY-functionalized nanoparticles, and (iv) the brine and n-decane droplet formation on the surface coated and the interaction energy analysis. Also, the wettability alteration was evaluated for restored samples coated with the SY surfactant in the absence of nanoparticles to determine the difference between the contact angles obtained and the

Figure 3. Theoretical scheme to study the wettability alteration by molecular dynamics.

represented through three circle types and two drop sections are identified. The red circles with horizontal fill lines correspond to the liquid molecules located near the solid surface in which the adhesion energies overcome the cohesive energies between the liquid molecules. The cutoff radius defines space where the surface is interacting with the liquid molecules, which was defined in 12 Å from an evaluation C



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above the wall potential that represents the wetting state of the restored sample, and it was replicated six times in the x- and ydirections. Then, the monolayer coverage was obtained using an NPT ensemble with periodic conditions in the x- and ydirections, while, in the z-direction, fixed conditions were defined with the wall potential in a lower plane and reflective conditions on the upper plane (which guarantee the number of molecules remaining constant in the simulation box). The whole coverage was relaxed using an NPT ensemble (1 atm and 298 K) for 10 ns, with a time step of 1 fs, keeping constant the z length while the x and y dimensions varied until a configuration close to a self-assembled monolayer (SAM) was obtained. In this way, from the final coverage configuration, the area occupied by the coating was determined (Axy), since the lateral interactions between the SY-functionalized nanoparticles have reached equilibrium, obtaining the closest possible approach between them. From this step, the surface densities (mg/m2) were obtained to represent each concentration of SY-functionalized nanoparticles in the nanofluids. Finally, to represent the brine and n-decane droplet formation on the restored sample coated with the SYfunctionalized nanoparticles, the molecules of liquid (brine and n-decane) were added on the restored sample after coating. For this, 5832 molecules of both brine and n-decane were added at 7 Å above the restored sample coated with SYfunctionalized nanoparticles for each surface coverage density. The simulations of the droplet formation were carried out using an NVT ensemble (at 298 K) during 10 ns with a time step of 1 fs. From this, 7 ns was defined as the equilibration time, while the last 3 ns was used as the sampling time for calculating the contact angles and the interactions energies. The same boundary conditions defined in the third step were used. Both the simulation time and the number of liquid molecules defined were previously tested,36−38 obtaining a proper representation of the wettability alteration by molecular dynamics. Relaxing time was used as a criterion to define when the system reaches equilibrium and guarantee that the droplet is completely formed. Relaxing time is defined as the time in which the system reaches 90% of the total potential energy of the equilibrated system. As shown in Figure S2, the relaxing time is around 0.3−0.5 ns, which is in agreement with values reported in the literature (0.3026 and 0.1534 ns)37,67 for similar systems. In all cases evaluated, for times larger than the relaxing time, the variation coefficient (ratio of the standard deviation to the average) is not higher than 3%. Therefore, it is guaranteed that 10 ns of simulation time is enough to secure that the droplets are completely formed and, in this way, to obtain reliable measurement of the contact angles. Also, in this step, the interaction energies between molecules of liquid (brine or n-decane) and the SY surfactant molecules were calculated (discriminated in two atom groups: polar head and fluorocarbon chain). The fluorocarbon chain (FC) group corresponds to the (CF2)nCF3 section of the surfactant molecule, while the polar head (PH) was defined as the remaining atoms of the surfactant molecule. The interaction energies were obtained from the sum of van der Waals interaction and electrostatic energies (nonbonding interaction energies) between all atoms in the group. For example, in the calculation of brine−CF interactions, the group “brine” corresponds to the atoms of the water molecules and the K+ and Cl− ions dissolved, while the CF group is composed by the (CF2)nCF3 section as mentioned above. Hence, the brine−CF

where the contact angles of water droplets were measured using a cutoff radius of 12 and 16 Å (Figure S1 in the Supporting Information). The blue circles represent the liquid molecules, which do not interact with the solid surface, indicating that the cohesive energies are predominant. These circles are classified into two types, the liquid molecules located at the bulk (inclined lines fill) and the liquid molecules located in the liquid−air interface (square fill), represented by a liquid−vacuum interface. Hence, a proper representation of the interactions of these circle types is needed to guarantee a suitable description of the wetting state of a solid surface.59,60,62−64 Further, the interfacial tension for water and ndecane was calculated to provide a proper representation of the cohesion energies of the liquid, using the model based on the formulation of the Gibbs interfacial tension,34,65,66 as written in terms of pressures, as shown in eq 1: ÉÑ Ä Ñ i L yÅÅ 1 γ = jjj z zzzÅÅÅÅPzz + (Pxx + Pyy)ÑÑÑÑ ÑÖ Å 2 k 2 {Ç

(1)

On the other hand, to represent the adhesion energies, a tuning procedure was made36 to estimate the excess energy of the surface59,60 using the experimental contact angle of the brine droplet (123°). Therefore, the wettability state of the restored sample was represented properly by the wall potential. The simulations of nanoparticle functionalization with the SY surfactant were carried out reproducing the conditions of the impregnation process developed experimentally. Further, a total of 56 surfactant molecules were constructed dissolved in 1414 brine molecules (1000 of water and 14 of KCl), which represent a macroscopic concentration of the impregnation solution of SY dissolved in a brine (2 wt % KCl). This simulation setup was defined considering the experimental results obtained, in which the amount of the surfactant onto the nanoparticle was measured (20 wt %) at 298 K. Also, this theoretical representation is based on the assumption that the functionalization process by the incipient wetness technique promotes a homogeneous distribution of the surfactant molecules on all nanoparticles. Thus, just one nanoparticle is necessary for the proper description of the functionalized material and the coating of the restored sample. The simulations of the nanoparticle functionalization with the SY surfactant were carried out during 10 ns with a time step of 1 fs using an NVT ensemble at 298 K and 1 atm. Also, with the aim of understanding the configuration of the nanoparticle functionalized with the SY surfactant, the radial distribution function was calculated between the silica nanoparticles and two groups of atoms of the SY surfactant, labeled as the polar head (PH) and the fluorocarbon chain (FC). To represent the restored sample coated with the SYfunctionalized nanoparticles, the above result was used to obtain different degrees of the surface coverage with the coating, replicating in x- and y-directions. Three degrees of rock surface coverage were defined to represent the amount of functionalized nanoparticles on the surface of the restored samples after the coating with the SY-functionalized nanoparticles at the different concentrations (0.3, 0.5, and 0.7 wt %). The first of them was obtained assuming a monolayer coverage, while the other two correspond to less SYfunctionalized nanoparticles attached to the restored surface. Thus, different surface densities (surfactant amount per surface area unit) were obtained. To simulate a monolayer of SYfunctionalized nanoparticles, the material was located at 7 Å D



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morphs mainly,72−74 in which a silicon atom is bound to four oxygen atoms and each oxygen is bound to two silicon atoms. Thus, regular tetrahedra of oxygen atoms are formed with the silicon atom in the center. Regarding the surface chemistry, the silica functionalities are mainly surface silanol groups (SiOH), which interact with the brine molecules through H-bonds.72,73 Therefore, the OH density on the nanoparticle surface defines the surface energy and in consequence its wettability state. In this study, a silanol density of 8 OH per nm2 was used according to the quantitative measurement of silanol and water content on various commercially available silica nanoparticles.73 A 10-4-3 wall potential75,76 (eq 2) was employed to represent the restored sample through an energy parameter tuning. As has been previously reported,36−39 this potential represents the solid as an infinitely extended and infinitely thick surface that interacts with the liquid phase through the parameters obtained by a mixing rule, as shown in eqs 3 and 4, which represent the solid−fluid interactions ÄÅ ÉÑ ÅÅ ÑÑ ÅÅ ÑÑ 10 4 ÅÅ 2 i σsf y ÑÑ 2 iσ y ÑÑ U(rij) = 2πϵsf ÅÅÅÅ jjj zzz − jjj sf zzz − 3Ñ ÑÑ ÅÅ 5 k z { z z 0.61 k { ÑÑ ÅÅ 3 + ÑÑ ÅÅÇ 2 σsf (2) ÑÖ

interaction corresponds to the average of nonbonding between each atom of the “brine” group that is interacting with all atoms of the “CF” group. In this way, the brine−FC, brine− PH, n-decane−FC, and n-decane−PH interactions are calculated for each system evaluated. These calculations were carried out during an additional nanosecond of simulation, with a time step of 1 fs, after the 10 ns for the droplet formation were concluded. In the case of the wettability alteration evaluation in the absence of nanoparticles, a similar procedure was followed by treating the restored sample just with the SY surfactant in the absence of nanoparticles. A detailed description of the methodology implemented can be found elsewhere.36,37 It is worth mentioning that the methodology described in this section has been widely tested on wettability alteration studies on mineral surfaces (as sandstone)36−38 and even metal surfaces (as gold).39 The results reported show a proper reproduction of the experimental contact angles by molecular dynamics.

4. MOLECULAR MODELS The consistent valence force field (CVFF)67 was used to model the fluorocarbon surfactant (Figure 2), representing the intermolecular interactions, van der Waals and electrostatic, by a Lennard-Jones (12−6) model and Coulombic model, respectively. The intramolecular interactions (bonds, angles, and dihedrals) were represented using harmonics models. A large number of species and their properties have been represented by CVFF, especially for nonionic surfactants with fluorocarbon structure,36,37 obtaining a suitable description of the adsorption energy and the surface concentration of a fluorocarbon surfactant over silica surfaces, as well as the proper calculation of contact angles of water and n-decane droplets on the restored samples with this coating. In the simulations of the droplet formation to reproduce the experimental measurements, three atomistic models were used to represent the n-decane and aqueous phases. The n-decane molecule was modeled using the transferable potentials for the phase equilibria-united atom force field (TraPPE-UA).68 To represent the aqueous phase (brine, 2 wt % of KCl), two models were needed, the extended simple point charge potential (SPC-E)69 and CVFF67 to model the water molecules and ions dissolved (K+ and Cl−), respectively. It is worth mentioning that, due to the nonpolar nature of the ndecane molecules, no electrostatic interactions were calculated. The intramolecular forces were not calculated for water molecules, since the SPC-E model considers a rigid structure,69 while the intramolecular interactions of n-decane molecules were represented by harmonic models the same as surfactant modeling for bonds and angles flexion, while the dihedral angle interactions were described by the model proposed by Watkins and Jorgensen,70 as defined for TraPPE-UA.68 Intermolecular and intramolecular parameters for the surfactant, n-decane, and brine can be found in the Supporting Information (Tables S1, S2, and S3, respectively). In the atomistic construction of the silica nanoparticles, two main aspects were considered for a suitable representation: the nanoparticle size and the surface chemistry.71−73 Hence, the experimental measurement of the nanoparticle diameter (7 nm) was reproduced in the computational representation. For spherical geometry, the atom numbers needed were used to guarantee an adequate nanoparticle size. Typically, the structures of silica surfaces correspond to crystalline poly-

(

σsf =

1 (σs + σf ) 2

ϵsf = (εsεf )1/2

)

(3) (4)

where σ and ϵ are the Lennard-Jones length and energy parameters for the solid (s), fluid (f), and solid−fluid (sf) interaction, respectively. Figure S1 (in the Supporting Information) shows that by varying the energetic parameter of the wall potential (ϵs) it is possible to reproduce different wettability states of a solid surface. Also, a suitable representation of the physical system was guaranteed through an appropriate reproduction of the adsorption energy of water on silica surfaces36 and the amount of fluorocarbon surfactant adsorbed at the surface.36,37 It is worth mentioning that this tuning process has been used to represent the wettability states of sandstones previously.36−38 For brine droplets, the dimensions of the simulation box were 438 × 433 × 440 Å, which contains 5832 water molecules, 60 KCl ions, 2016 SY molecules, and 36 silica nanoparticles. Since the same coating was used for n-decane droplets at each treatment concentration, the same dimensions of the simulations box and number of molecules of SY surfactant and nanoparticles were employed in the formation of n-decane droplets. The Fan and Cagin77 model was used to calculate the contact angles on each simulation of droplet formation on the restored sandstone surface, for both coated and uncoated surfaces in the presence and absence of nanoparticles. The contact angle (θ) calculation was based on the geometric measures, height (h) and radius (r), of the droplet formed by molecular dynamics simulations, as shown in eqs 5−7. We have previously employed this method for the contact angle measurement of asymmetrical droplets obtained by MD simulations.36−39 cosθ = 1 − E

h R

(5) DOI: 10.1021/acs.jced.8b00910 J. Chem. Eng. Data XXXX, XXX, XXX−XXX

Journal of Chemical & Engineering Data S = πr 2 R=

h S + 2 2πh

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(6)

(7)

To capture correctly the liquid drop asymmetry, the height and radius were measured at three different times after equilibrium was reached (at 8, 9, and 10 ns), and for each one of them, four planes perpendicular to the surface were selected to obtain more accurate stats of the contact angle measurement. Therefore, at each time selected for the contact angle calculation, four contact angles were measured (by each perpendicular plane), obtaining the average and standard deviation of the mean for each contact angle. Hence, the contact angles obtaining by MD simulations describe the average wetting state of each system, while the standard deviation of the mean gives an idea of uncertainty due to the droplet asymmetry. It is worth mentioning that, due to the significant difference of size between the water or n-decane molecules and the nanoparticles, different atom radii for the functionalized nanoparticles and the liquid molecules (water or n-decane) were used. The above was conducted to illustrate in a better way the contact angle obtained by MD simulations. All MD simulations were conducted in the LAMMPS software,78 with parallel computing. The temperature and pressure were controlled by the Nosé−Hoover thermostat and barostat, respectively. Lorentz−Berthelot mixing rules were used to define the cross interaction parameters between atoms of different species. The long-range electrostatic interactions were calculated by the particle−particle−particle−mesh79 method. A cutoff radius of 12 Å for the van der Waals and electrostatic interactions was defined.

Figure 4. Normalized FTIR spectra for SiO2 nanoparticles before and after functionalization with 20 wt % of the Silnyl FSJ (SY) fluorocarbon surfactant, as well as the difference spectrum between both materials.

OH− with the content of fluorocarbon surfactant on the nanoparticle surface shows that a higher number of OH− groups on the surface of SiO2 nanoparticles can be replaced with fluorinated groups. Further, from the difference spectrum, it can be observed that the main bands related to the SiO2 support are subtracted and that bands corresponding to the SY surfactant at 2950, 2890, 1450, 1360, and 1130 cm−1 are exposed. 5.2. Experimental and Theoretical CAM Results. Figure 5 shows the SY surfactant density results as a function

5. RESULTS AND DISCUSSION 5.1. Nanoparticle Characterization. The mean particle size (dp50) and surface area (SBET) of the nanoparticles used as support were 7 ± 1 nm and 380 m2/g, respectively. The SYfunctionalized nanoparticles showed a dp50 value of 10 ± 1 nm, close to the size obtained for the support employed. Meanwhile, the SBET is considerably reduced to 38 m2/g with the amount of SY surfactant onto the nanoparticle surface.80−82 Through TGA experiments, it was verified that the amount of SY surfactant on the surface of the nanoparticles after the functionalization process was 20 ± 0.1 wt % as a result of null desorption in the saltwater. Figure 4 shows the normalized FTIR spectra for the SiO2 nanoparticles before and after functionalization with 20 wt % of the SY surfactant, as well as the difference spectrum between both materials. Three bands representative of the SiO2 support are located at 1000−1100 cm−1 due to the asymmetric stretching vibration of Si−O−Si in the nanoparticles. Also, another band between 830 and 955 cm−1 is observed due to the presence of Si−OH. The band at 3325 cm−1 is related to free OH− stretching.83 For the modified nanoparticles, other bands have been found, for example, at 1130 cm−1 related to Si−O−C bonds, evidencing the surfactant presence. Hydrogen’s stretching assigned to symmetric and asymmetric stretching vibration of the CH3- and CH2-groups is observed in the bands between 3000 and 2800 cm−1.82,84,85 The band located at 1450 cm−1 is characteristic of C−F stretching vibration. The existence of C− F bonds in the form of CF2- or CF3-groups is also observed at 1360 cm−1. A decrease in the intensity of the band related to

Figure 5. Silnyl FSJ density as a function of the fluorocarbon chain length estimated by molecular dynamics.

of the fluorocarbon chain length (n) obtained by molecular dynamics. The experimental density reported for the surfactant (1.12 g/cm3) corresponds to a 40 wt % SY solution in water. To determine the surfactant density, we used a mix rule, as shown in eq 8 x x 1 = surfactant + water ρmix ρsurfactant ρwater (8) where x and ρ are the mass composition and density for the surfactant and water. Considering that the solution density is 1.12 g/cm3, the surfactant composition is 0.4, the water density is 1 g/cm3, and its composition is 0.6, the surfactant density was calculated (1.37 g/cm3). Therefore, a chain length of two carbon atoms was obtained (n = 2), which corresponds to a surfactant F



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density of 1.34 g/cm3, as calculated by molecular dynamics with a deviation of −1.9% concerning the experimental value. In this case, we have considered that the surfactant selfassembly in water is similar in comparison to pure surfactant, since the fluorocarbon chain is composed only by two carbon atoms. Thus, volume changes of a mixture can be negligible. Once the Silnyl FSJ structure was defined, the interaction between the SY surfactant and the SiO2 nanoparticles during the functionalization process was reproduced considering that an amount of 20 wt % was anchored over the nanoparticle surface. It is worth mentioning that the functionalization process allows significantly altering the wetting properties of the silica nanoparticles, since standalone nanoparticles promote a water-wet state,86 while the FS-functionalized nanoparticles promote a gas-wet state. Figure 6 shows a representative snapshot of the SiO2 nanoparticles functionalized with the SY fluorocarbon surfactant.

for the three nanofluids employed with contact angles higher than 90 and 50° for brine and n-decane droplets, respectively, which are consistent with the range of contact angles reported in the literature for fluorocarbon surfactants.8,19 In short, the contact angles measured experimentally evidence a wettability alteration promoted by the fluorocarbon surfactant (Silnyl FSJ), from an oil-wetting state to a gas-wetting state, for both free SY surfactant and SY-functionalized nanoparticles. Figure S1 (in the Supporting Information) shows that an energetic parameter of ϵs* = 0.38 kcal/mol allows representing the wetting state of the restored sample. Also, the results do not show a significant deviation between the curves evaluated for the two cutoff radii (16 and 12 Å). Thus, the region of influence of the solid surface can be represented by a cutoff radius of 12 Å, which is consistent with previous results.36,87 Figure S4 in the Supporting Information shows the results of the densities and the interfacial tensions (IFT) for n-decane and water. Average results of the densities were 0.72 and 1.02 g/cm3 for the n-decane and water, respectively, and the IFT results obtained were 26.69 and 70.77 mN/m for the n-decane and water, respectively. Hence, it can be concluded that the molecular potentials employed allow the proper representation of the cohesion energies for the n-decane and water. Further, a proper reproduction of the experimental wetting state of the restored sample was obtained, through a suitable representation of the adhesion and cohesion energies, whereby the wall potential with the tuned energetic parameter (ϵs*) will be denominated as the restored sample. Table 2 shows the theoretical results of the coating process of the restored sample with the SY-functionalized nanoparticles Table 2. Surface Coverage Densities of the Surface Coated with Silica Nanoparticles Functionalized with Fluorocarbon Surfactant

Figure 6. Snapshot of SiO2 nanoparticles functionalized with 20 wt % of Silnyl FSJ surfactant. For clarity, water molecules and the ions dissolved (K+ and Cl−) are not shown. Carbon atoms are depicted in gray, hydrogen in white, oxygen in red, fluorine in cyan, and silica in yellow.

Table 1 shows the contact angles measured experimentally for brine and n-decane on the restored samples before and after Table 1. Experimental Contact Angles for Water/Rock/Air and n-Decane/Rock/Air Systems before and after Coating with Free Silnyl FSJ (SY) Fluorocarbon Surfactant and 0.3, 0.5, and 0.7 wt % of SY-Functionalized Nanoparticles at 298 K system no coated NP-free 0.3 wt % of nanoparticles 0.5 wt % of nanoparticles 0.7 wt % of nanoparticles

brine contact angle (deg) 123 116 111 90 102

± ± ± ± ±

0.4 0.4 0.9 0.4 0.4

± ± ± ±

Axy (Å2)

surface coverage density (mg/m2)

0.3 0.5 0.7

84486 72930 61510

4.71 5.45 6.46

(20 wt % of SY surfactant), obtained by molecular dynamics simulations. The surface densities were obtained by varying the number of SY-functionalized nanoparticles on the same area of the restored sample (represented by a wall potential). Further, a monolayer (ML) coverage was represented as described in the literature,36−38 which corresponds to the coverage density obtained with the nanoparticle concentration (0.3, 0.5, and 0.7 wt %). From ML results, two different surface densities were used, which were obtained reducing the number of SYfunctionalized nanoparticles needed for treating the same surface area. All coatings show heterogeneities, as is shown in Figure S5 in the Supporting Information. This behavior is due to different orientations of the fluorocarbon chain (perpendicular or inclined regarding the nanoparticle surface) and due to some regions of the nanoparticle that were not coated by the surfactant. Therefore, the coating exhibits a heterogeneous interaction with the liquid molecules (brine or n-decane). Figure 7 shows the contact angles for brine/restored sample/vacuum systems, before and after the coating with the SY-functionalized nanoparticles, calculated by molecular dynamics simulations for (a) restored sample (oil-wet state), (b) restored sample coated with the SY surfactant in the

oil contact angle (deg) 0 51 70 58 71

nanoparticle concentration (wt %)

1.3 0.9 0.9 0.4

soaking with the SY-functionalized nanoparticles. The images of the estimated contact angles can be found in Figure S3 of the Supporting Information. In the case of the restored samples before coating, the n-decane was completely imbibed into the porous media, and the brine droplet showed a contact angle of 123°, corroborating that the samples are strongly oilwetted. For the restored samples coated with the SYfunctionalized nanoparticles, similar behaviors were obtained G



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Figure 8. Contact angles for n-decane/restored sample/air systems: (a) restored sample before coating, (b) restored sample coated with the Silnyl FSJ (SY) surfactant in the absence of nanoparticles, and restored sample coated with the SY-functionalized SiO2 nanoparticles at different concentrations of (c) 0.3, (d) 0.5, and (e) 0.7 wt %. Contact angle results from molecular dynamics simulations (θMD) are compared to those estimated experimentally (θEXP). Carbon atoms are depicted in gray, hydrogen in white, oxygen in red, fluorine in cyan, silica in yellow, CH3 in orange, and CH2 in ocher.

Figure 7. Contact angles for brine/restored sample/air systems: (a) restored sample before coating, (b) restored sample coated with the Silnyl FSJ (SY) surfactant in the absence of nanoparticles, and restored sample coated with the SY-functionalized SiO2 nanoparticles at different concentrations of (c) 0.3, (d) 0.5, and (e) 0.7 wt %. Contact angle results from molecular dynamics simulations (θMD) are compared to the those estimated experimentally (θEXP). The brine is a 2 wt % solution of KCl in deionized water. Carbon atoms are depicted in gray, hydrogen in white, oxygen in red, fluorine in cyan, and silica in yellow.

through molecular dynamics simulations are in excellent agreement with the ones measured experimentally. In this case, a significant difference between the contact angles before and after the coating process was observed from a strong oilwetting state (a monolayer on the restored sample) to a moderate lipophobic surface. The most lipophobic state was reached on the surface coated with 0.7 wt % of SYfunctionalized nanoparticles, followed by the systems with 0.3 and 0.5 wt %, and the SY surfactant in the absence of nanoparticles. Interaction energies were calculated to obtain a deeper insight into the wettability alteration mechanisms promoted by addition of the SY surfactant and SY-functionalized SiO2 nanoparticles. Table 3 shows the results of the nanoparticle− liquid, SY−liquid, and liquid−liquid interactions obtained for the five systems evaluated, where “liquid” refers to the interactions of the brine or n-decane molecules. The results are reported in kcal/mol units, where “mole” refers to the total number of molecules in the simulation box. Therefore, the total molecule number is defined as the sum of the liquid molecules (brine or n-decane), the surfactant molecules, and the nanoparticles (each nanoparticle is taken as individual molecule). In this way, it can be guaranteed that the energies evaluated are intensive; i.e., if more liquid molecules are simulated, the energies reported in Table 3 will remain almost constant. For a standalone surfactant system (nanoparticles free), it is evidenced that the interaction energy between the fluorocarbon surfactant and the brine (−0.0792 kcal/mol) is lower in comparison for the standalone nanoparticle system

absence of nanoparticles, and restored sample coated with the SY-functionalized nanoparticles at different concentrations of (c) 0.3, (d) 0.5, and (e) 0.7 wt %. A total of six contact angles were calculated, and the reported one corresponds to an average of the obtained results, evidencing a suitable approximation concerning the experimental measurements summarized in Table 1. In all cases, hydrophobic surfaces were observed, with the highest contact angle for the restored sample before the coating process, followed by the restored sample after being coated with the SY surfactant in the absence of nanoparticles, and followed by the restored samples coated with the nanofluids in the order 0.3, 0.7, and 0.5 wt %. Results indicate that the SY surfactant addition, under both free and functionalized onto SiO2 nanoparticles conditions, leads to a decrease of the brine contact angle. Nevertheless, the low affinity for the aqueous phase remained, contrary to results obtained by the addition of solely SiO2 nanoparticles that leads to strong water-wetting conditions.86,88 Figure 8 shows the contact angles for n-decane/restored sample/vacuum systems before and after the coating process calculated by molecular dynamics simulations for (a) restored sample before coverage, (b) restored sample coated with the SY surfactant in the absence of nanoparticles, and restored sample coated with the SY-functionalized SiO2 nanoparticles at concentrations of (c) 0.3, (d) 0.5, and (e) 0.7 wt %. From Figure 8, it can be observed that the contact angles calculated H



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Table 3. Nanoparticle-Liquid, Silnyl FSJ (SY)-Liquid, and Liquid−Liquid Interaction Energies for Brine and n-Decane Dropletsa n-decane (kcal/mol)

brine (kcal/mol) coating NP-free 0.3 wt % of nanoparticles 0.5 wt % of nanoparticles 0.7 wt % of nanoparticles

nanoparticle−liquid

SY−liquid

liquid−liquid

−0.0863 −0.0323 −0.0282

−0.0792 −0.0051 −0.0398 −0.0479

−12.2464 −11.5249 −11.2113 −11.2592

nanoparticle−liquid

SY−liquid

liquid−liquid

−0.4235 −0.4699 −0.4816

−0.7121 −0.0919 −0.7284 −0.0989

−8.2905 −8.4194 −8.9115 −8.6828

a

NP-free refers to the absence of nanoparticles.

surfactant molecule as the atoms that compose the polar head (PH) and the fluorocarbon chain (FC). Figure 9 shows the

(surfactant free), which has a strong interaction energy (1.02 kcal/mol)36 that describes a hydrophilic surface state, typical in a process where standalone silica nanoparticles are added.86 Therefore, the functionalization process allows the wetting properties of the silica nanoparticles to be altered significantly. The results show the liquid−liquid interaction energies, which represent the cohesion energies, were stronger than the adhesion energies (SY−liquid) as a consequence of the coating with the SY-functionalized nanoparticles. The difference obtained was of 3 orders of magnitude for the brine contact angles and of 2 orders of magnitude for n-decane droplets. These findings are in agreement with the contact angles obtained both experimentally and theoretically, since in all evaluations the brine contact angles were higher than the ndecane contact angles. For brine droplets, a reduction of the adhesion energy was obtained for the coating with the SY surfactant in the absence of nanoparticles regarding the employed nanofluids and could be due to the hindering of some SY functional groups that are interacting with the nanoparticle surface. It was also observed that the interaction energies of the liquid phase and the SYfunctionalized SiO2 nanoparticles are highest for a dosage of 0.3 wt % due to there being less packing in comparison with 0.5 and 0.7 wt %, leading to more nanoparticle surface atoms exposed for interacting with the brine molecules. Although this packing difference also alters the SY−liquid interactions, no trend was identified due to the amphiphilic properties of the surfactant evaluated. Therefore, the highest interaction energy corresponds to a configuration in which the head polar group is located closer to the brine molecules (0.3 wt %). The reduction of the SY−brine interaction is due to the adsorption configuration favoring the interaction between the fluorocarbon chain and the brine molecules. In the energetic evaluation of the n-decane droplets, a similar trend to the one for brine systems was obtained. A reduction of the interaction energies between the nanoparticles and the ndecane molecules was observed as the packing increases. The surfactant−n-decane interactions changed due to the difference of the surface densities of the nanoparticles with the surfactant. Again, no clear trend was identified for SY−liquid interactions. Thus, the variations were associated with the difference in the interaction between the n-decane molecules with the head and fluorocarbon chain of the surfactant. In both cases, a minor variation of the nanoparticle−n-decane and SY−n-decane interactions was obtained and could be due to the nonpolar nature of the n-decane molecules, since the variations of the interaction energies are an exclusive consequence of the van der Waals-type weak interactions. To understand the effect of the surfactant adsorption over the nanoparticle surface on the wettability alteration, the radial distribution function was calculated between the liquid (brine and n-decane) molecules and the surfactant, discriminating the

Figure 9. Radial distribution functions of (a) brine and (b) n-decane with the Silnyl FSJ (SY) surfactant molecules discriminated as polar head (PH) and fluorocarbon chain (FC) for concentrations of 0.3, 0.5, and 0.7 wt % of SiO2 nanoparticles functionalized with 20 wt % of SY. The brine is a 2 wt % solution of KCl in deionized water.

radial distribution functions calculated pairwise for the surfactant with (a) the brine and (b) n-decane for the three cases evaluated. Results evidence that the brine molecules are closer than the n-decane molecules to the surfactant chains, since the first peaks for brine g(r) are located close to 2 Å, while for n-decane g(r) are located close to 3 Å. This trend could be due to the heterogeneities of the coating with the functionalized nanoparticles (Figure S5 in the Supporting Information). Thus, the water molecules can occupy an uncoated surface while n-decane molecules cannot, since they are larger than water molecules. In addition, the results show two clear trends for liquid−FC and liquid−PH. It can be observed from Figure 9 that for both brine−FC and n-decane− FC a change of slope occurs at approximately 5 Å. Also, in the case of n-decane−FC curves, a valley between 7 and 8 Å is observed, suggesting stronger adhesion energy for n-decane systems than brine systems as well as a higher number of I



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not vary appreciably for the systems with and without nanoparticles, indicating that the nanoparticles act as a wettability modifier that helps the fluorocarbon surfactant to promote a gas-wetting surface. Second, although the nanoparticles have the same fluorocarbon surfactant amount adsorbed, the nanoparticle−liquid interactions vary depending on the surface coverage density with the SY-functionalized nanoparticles. A clear trend was identified in the nanoparticle− brine and nanoparticle−n-decane interactions, in which the presence of silica nanoparticles promoted a reduction of the adhesion energy. Therefore, the configuration of surfactant adsorption on the nanoparticles determines how the nanoparticles are deposited over the restored sample. Finally, the surfactant−liquid interactions do not evidence any clear trend, since the interactions between the liquid molecules and the surfactant (polar head or fluorocarbon chain) are significantly different due to the amphiphilic properties of the fluorocarbon surfactant.

neighbors, which is consequent with the contact angles measured (smaller contact angles for n-decane than for brine droplets). Meanwhile, for liquid−PH, no changes in the slope were observed. In all cases, the liquid−FC curves pairwise evidence a higher number of neighbors than liquid−PH curves for each nanoparticle concentration, indicating that the SY surfactant is functionalized onto the nanoparticle by the polar head while the fluorocarbon chain is exposed toward the liquid phase (brine or n-decane). Also, these results depict that the configuration of the SY adsorption on the nanoparticle is a key parameter for the variations in the interaction energies between the SY surfactant and the liquid (brine or n-decane) summarized in Table 3. Hence, after a complete experimental and theoretical evaluation of the wettability alteration of an oil-wetting surface to a gas-wet state, it can be said that the nanoparticles act as a wettability modifier that helps the SY surfactant in the wettability alteration process. In technical terms and considering that the contact angle of the liquid was the only evaluation parameter, the addition of nanoparticles does not have a significant effect on the increase of the contact angles of brine and n-decane droplets. However, valuable results were found, since the addition of nanoparticles allows a significant reduction of the fluorocarbon surfactant amount necessary to promote a gas-wetting surface, showing a promising alternative to reduce the operating costs in EOR projects.

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jced.8b00910. Tuning curve of wall potential (Figure S1), potential and temperature equilibration for brine and n-decane droplets (Figure S2), experimental contact angles (Figure S3), molecular dynamics results of the densities and interfacial tensions for n-decane and water (Figure S4), snapshots for functionalized nanoparticle coatings (Figure S5), and interaction parameters of the fluorocarbon surfactant (Table S1), n-decane (Table S2), and brine (Table S3) (PDF)

6. CONCLUSIONS An experimental and theoretical evaluation of wettability changes of sandstone samples (oil-wetting restored sample) to a gas-wet state with fluorocarbon-functionalized SiO2 nanoparticles was made. SiO2 nanoparticles were functionalized with 20 wt % of Silnyl FSJ (SY) surfactant, and three nanofluids at 0.3, 0.5, and 0.7 wt % in a 2 wt % KCl brine were prepared. In total, five systems were evaluated including the restored sample before the coating process, samples coated with the SY surfactant without nanoparticles, and three systems composed by the restored samples coated with the prepared nanofluid (0.3, 0.5, and 0.7 wt %). The contact angles measured experimentally were properly reproduced with a deviation lower than 7%, indicating that molecular methods and models allowed a suitable representation of the wettability alteration process. It is worth mentioning that the suitable representation of the experimental contact angles is due to the proper representation of the cohesive and adhesive energies. In this sense, the adequate selection of the molecular potential to represent the interaction between the liquid molecules in the droplet and the interactions between the liquid molecules and the functionalized nanoparticles plays a key role. In addition, the tuning of the surface potential allowed obtaining a reliable description of the interaction between the surface (restored rock), the functionalized nanoparticles, and the liquid molecules to reproduce the experimental contact angles. In the simulations of the surface coating with the SYfunctionalized nanoparticles, different surface densities were obtained. The results show a significant reduction of at least 52% of the surfactant amount necessary to promote a gaswetting surface, showing a promising alternative to reduce the operational costs in EOR projects. Further, three main conclusions were raised in this study. First, both the experimental and theoretical results evidence that the contact angles of the brine and n-decane droplets do

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AUTHOR INFORMATION

Corresponding Authors

*Phone: +57 (4) 4255137. E-mail: [email protected]. *Phone: +57 (4) 4255137. E-mail: [email protected]. ORCID

Ivan Moncayo-Riascos: 0000-0002-1601-3493 Camilo A. Franco: 0000-0002-6886-8338 Farid B. Cortés: 0000-0003-1207-3859 Author Contributions

The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The authors acknowledge the National Hydrocarbons Agency (ANH) and Colciencias for the financial support through the Agreement 273 of 2017. The authors also thank the Universidad Nacional de Colombia − Sede Medelliń for allowing simulations in the advanced numerical computation unit (UNICA). Ivan Moncayo-Riascos is also thankful for the scholarship provided by Colciencias in the call for proposals 727-2016. J



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