SiO2 Nanoparticles-Assisted Ultrasound

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Fossil Fuels

Effect of the NiO/SiO2 Nanoparticles-Assisted Ultrasound Cavitation Process on the Rheological Properties of Heavy Crude Oil: Steady State Rheometry and Oscillatory Tests Daniel Montes, Esteban A. Taborda, Mario Minale, Farid B. Cortés, and Camilo A. Franco-Ariza Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.9b02288 • Publication Date (Web): 06 Sep 2019 Downloaded from pubs.acs.org on September 6, 2019

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Effect of the NiO/SiO2 Nanoparticles-Assisted Ultrasound Cavitation Process on the Rheological Properties of Heavy Crude Oil: Steady State Rheometry and Oscillatory Tests Daniel Montes1, Esteban A. Taborda1, Mario Minale2, *, Farid B. Cortés1, and Camilo A. Franco1,* 1. Grupo de Investigación en Fenómenos de Superficie – Michael Polanyi, Facultad de Minas, Universidad Nacional de Colombia – Sede Medellín. 2. Department of Engineering, University of Campania Luigi Vanvitelli, via Roma 29, 81031 Aversa (CE), Italy.

*Corresponding authors: [email protected]; [email protected]

Abstract This manuscript has the primary objective of demonstrating the changes in the rheological behavior of heavy crude oils (HO) in response to the application of ultrasound cavitation assisted with NiO-functionalized SiO2 nanoparticles (SiNi1). A HO with asphaltene mass fraction of 17.0 % was used for the tests which were carried out at 25 °C and 1 atm with fixed ultrasound frequency and power of 37 kHz and 400 W, respectively. The viscosity measurements were performed on four different samples: the HO in the absence of nanoparticles and ultrasound irradiation (sample A), the HO alongside ultrasound irradiation (sample B), the HO with the addition of nanoparticles (sample C), and finally, the HO in the presence of the mentioned nanomaterial and ultrasound irradiation (sample D). It was observed that a single treatment, whatever it is, only slightly changed the original HO rheology, while the cooperative action of ultrasound cavitation and nanoparticles addition induced several measurable differences with respect to the HO: The viscosity was reduced

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up to 50%-60%, depending on the applied shear rate; the power per unit of volume dissipated during a hysteresis cycle was decreased of about the 70%; the sample elasticity was measurably reduced and accordingly the relaxation time measurable for the original HO was not detectable anymore. These findings can be explained by hypothesizing that the original HO viscoelastic microstructure is broken down by the proposed combined treatments as the asphaltenes may stably adsorb on the nanoparticles and the subsequent size reduction process of the asphaltene aggregates is enhanced by the ultrasound irradiation.

Keywords: Asphaltenes; nanoparticles; thixotropy; ultrasound cavitation; viscoelastic moduli; viscoelastic network.


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1. Introduction Nowadays, the heavy oil (HO) production and transportation are significantly increased to compensate the depletion of light oil reservoirs.1, 2 However, the physicochemical properties of these fluids, such as high density, high asphaltene content, and high viscosity, lead to low efficient operations with non-cost-effective results.3 In heavy oils, the high content of asphaltenes and resins leads to the formation of complex hierarchical microstructures4 that may also arrange to form a viscoelastic network,5 which results in extra-high oil viscosity, which is an essential parameter for production and transportation designing.6 Hence, several investigations are focused on the crude oil dilution for adjusting its viscosity to pipeline standards.6-9 Nonetheless, the addition of solvents tends to worsen transportation or production operations because, depending on the solvents chemical nature, it may induce an undesired modification of the crude oil microstructure that can drive even to the precipitation of asphaltenes.4 Moreover, the complex heavy crude oil matrix also affects other HO rheological properties, and often, both thixotropy10 and viscoelasticity11, 12 are observed. Viscoelasticity induces to a fluid a behavior in between an elastic solid, able to recover an imposed strain when the applied stress is removed, and a purely viscous fluid, able to dissipate all the energy accumulated during a deformation. Thixotropy is defined as: “The continuous decrease of viscosity with time when flow is applied to a sample that has been previously at rest and the subsequent recovery of viscosity in time when the flow is discontinued”.13 The transient behavior of a fluid can be investigated to study thixotropy and in particular, the hysteresis technique, introduced by Green and Weltman,14 can be used. It consists in increasing and decreasing the applied shear rate from zero to a maximum value. When the stress is plotted vs. the shear rate, typically a hysteresis loop is detected. The loop dimension will depend on


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the rate at which the shear rate is varied and on the resting time.15, 16 This effect may be also related to an irreversible microstructure modification that induces a plastic deformation, usual in solids,17 which is associated to an energy loss. The study of the HO thixotropy is essential during the designing of transport operations to avoid overestimations of the amounts of diluents and the temperature needed to reach pipeline standards or to avoid possible underestimations that could affect equipment integrity.18 Mortazavi-Manesh et al.18 studied the thixotropic behavior of Maya crude oil using hysteresis loop tests concluding that thixotropy is reduced upon temperature increases. With dynamic experiments, Wardhaugh et al.12 characterized the viscoelasticity of waxy crude oils to investigate how it affects the yield point. They found that the 3D internal microstructure of the investigated oils induces a solid-like behavior with conventional elastic, creep, and fracture properties. Ghannam et al.16 evaluated the HO rheological properties with the addition of light hydrocarbons, concluding that the samples were shear thinning and showed time dependency related to thixotropy, which decreases with the addition of light hydrocarbons. Moreover, Taborda et al.,19 studied the HO internal structure alteration caused by nanoparticles addition through steady state and dynamic rheological tests. They found that the addition of nanoparticles significantly reduces the oil viscosity, yield stress and elasticity. In recent years, cavitation has been exploited as a technique capable of reducing a fluid viscosity.20,

21

Rahimi et al.,22 studied the combined effect of ultrasonic irradiation and

heating on the HO viscosity showing that the viscosity reduction induced by cavitation increases with the temperature. Furthermore, also the addition of nanoparticles to an HO improves the effect of cavitation on the viscosity reduction thanks to their high dispersibility, high surface-area-to-volume-ratios, high asphaltenes selectivity and adsorptive capacity.23-26 Askarian et al.,27 employed metal nanoparticles for this purpose, obtaining a final viscosity


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reduction of 20% due to the enhancement of the viscoelastic network disruption. Lately, hybrid nanoparticles of supported hygroscopic salts (SHS) showed excellent asphaltene adsorptive capacities,28-32 making them suitable for enhancing the ultrasound induced viscosity reduction. According to the authors, in the literature, the coupled effect of cavitation and nanoparticles addition on both the HO viscosity and elasticity has never been investigated. To the best of our knowledge, only Montes et al.33 showed some preliminary results on the sole heavy oil viscosity reduction induced by the use of nanoparticles (NiO-functionalized SiO2: SiNi1) coupled with ultrasound cavitation. The authors investigated the effect of both the cavitation time and the nanoparticles concentration concluding that after 90 min of exposure with 2000 mg∙L-1 of SiNi1 nanoparticles, the viscosity of the HO at a shear rate of 10 s-1 was reduced of 44%. This result is achieved due to the HO internal microstructure modification induced by cavitation coupled to the asphaltenes adsorption on the nanoparticles. The aim of this paper is assessing the preliminary results of Montes et al.33 by evaluating the effect of the proposed combined treatments on the rheological properties of the heavy oil. The steady state behavior and the dynamic response of the material are investigated before and after the functionalized nanoparticles-assisted ultrasound cavitation. Also, the HO thixotropy is investigated through hysteresis loop tests. Since rheology is a very sensitive tool to investigate the microstructure of complex fluids, like the heavy oils,34 it is expected to understand the microstructure modification induced by cavitation combined with nanotechnology treatments so that this study might open a broader landscape about the impacts of nanotechnology in the production and transportation of heavy oils.

2. Materials and methods


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2.1. Materials Nickel oxide nanocrystals functionalized over 7 nm fumed silica nanoparticles (SiNi1) were synthesized following the procedure described in a previous study.33 More information about the characterization of the nanoparticles is reported in previous papers.29-31 The HO used has a density corresponding to 13 °API and approximately 40% of emulsified water. SARA measurement was carried out through a micro deasphalting technique coupled with thin layer chromatography following the IP 469 standard 35 and using a TLC-FID/FPD Iatroscan MK6 (Iatron Labs Inc, Tokyo, Japan). This characterization results showed that mass fractions of saturates, aromatics, resins, and asphaltenes are 18.2 %, 23.1 %, 41.7 %, and 17.0 %, respectively. Four different samples are investigated: A) HO, B) HO with nanoparticles, C) sonicated HO, D) HO with the addition of nanoparticles and sonicated. (Table 1).

Table 1. Investigated Samples A

Heavy Oil

B

Heavy Oil + 2000 mg∙L-1 SiNi1 nanoparticles

C

D

Heavy Oil + Sonication for 90 min 400W/37 kHz

Heavy Oil + 2000 mg∙L-1 SiNi1 nanoparticles + Sonication for 90 min 400W/37 kHz


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2.2. Methods 2.2.1. Asphaltenes characterization and aggregates size measurements The asphaltenes were characterized by their chemical composition, and aggregation kinetics were also measured for confirming the existence of the viscoelastic network. Firstly, the asphaltenes were extracted from the evaluated crude oil following the method described in previous works.24, 32 Concisely, certain HO volume was diluted with n-heptane in a 40:1 crude oil/diluent ratio. The mixture was sonicated for 2 h and further stirred for 20 h at 300 rpm, then it was filtered and diluted again in a 4:1 ratio with n-heptane. The suspension was centrifuged for 30 min at 4500 rpm for obtaining the asphaltenes, which were washed with n-heptane several times until no impurities were observed in the residue. The asphaltenes chemical composition was characterized through X-ray Photoelectron Spectroscopy (XPS) with a PHOIBOS 150 1D-DLD (SPECS GmbH, Berlin, Germany) photoelectronic X-ray spectrometer (NAP-XPS) analyzer using monochromatic light of AlKα (1486.7 Ev, 13 kV, 100 W) with 100 eV and 30 eV energy steps for general and high resolution spectrum, the steps for general and high resolution spectrum were 1 eV and 0.1 eV respectively. Moreover, the asphaltenes mean aggregates size was measured through the dynamic light scattering technique (DLS) using a NanoPlus-3 (Micromeritics, GA, USA). Briefly, n-heptane/toluene (heptol) model solutions were prepared with 50 vol% of toluene and 1000 mg∙L-1 of asphaltenes, the mixture was stirred at 300 rpm for the entire duration of the experiments, and aliquots were taken for carrying out the measurements. The same procedure was applied consequently for heptol model solutions at the same conditions of Sample D, first the SiNi1 nanoparticles were added to the solutions, and then the obtained suspensions were sonicated for 90 min before measuring asphaltenes aggregation.


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2.2.2. Samples preparation The colloidal suspensions made of HO and 2000 mg∙L-1 of SiNi1 nanoparticles were prepared by hand stirring for 15 min at 30°C in order to facilitate mixing homogeneity due to the sample high viscosity, which made unfeasible the use of other mechanical methods of mixing. The ultrasound cavitation was applied for 90 min to the pure HO (sample C) and to the colloidal suspension discussed above (sample D). An Elmasonic E60H (Elma Schmidbauer GmbH, Singen, Germany) sonicator with the power of 400 W and frequency of 37 kHz was used, and the samples were monitored to avoid the temperature increase induced by the ultrasound exposure. All the samples were left at rest for 10 min before carrying out any further test.

2.2.3. Rheological measurements Prior to any rheological test, before loading, the samples were preconditioned by hand mixing for 5 min so to start from a microstructure which resembles the one encountered in real field applications more than that obtained at the end of a preconditioning steady simple shear flow, as typically done in rheometry. First, a flow curve is obtained by running a shear rate ramp soon after having loaded the sample in the rheometer. The shear rate was increased from ≈3 to ≈100 s-1 in 2 min to limit oil light tense evaporation and to obtain a flow curve characterization in a very short time, as typically required in control operations in real field applications. To compare the different samples, the degree of viscosity reduction (DVR) is estimated. It is defined as:


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   treat  DVR   HO   100   HO 

(1)

where, ηHO and ηtreat are the viscosities of the heavy oil (sample A) and of the sample after a specific treatment (samples B-D), respectively.36, 37 The viscosities in eq. (1) are measured at three characteristic shear rates during the increasing shear rate ramp. Hysteresis loop tests were performed to investigate the material thixotropy on freshly loaded samples. The shear rate was first increased from ≈3 to ≈100 s-1 in 2 min, as in the flow curve determination, and then it was decreased from ≈100 to ≈3 s-1 always in 2 min. In the increasing shear rate ramp, the sample viscosity change can be associated with the internal microstructure breakdown, while in the decreasing shear rate ramp, a microstructure buildup can occur.15, 38-40 Each whole experiment lasted about only 4 min. To characterize the sample hysteresis the area enclosed by the loop (WL), in a stress vs. shear rate plot, was evaluated.13 WL is the power per unit of volume dissipated by the sample in the loop test:

WL 

 min

 

BD

  BU  d

(1a)

 min

where σBD and σBU are the shear stresses in the increasing and decreasing shear rate ramp, respectively.  min and  max are the minimum and maximum shear rate in the hysteresis loop test. The thixotropy index is also estimated. It is defined as the normalized area enclosed by the loop in a viscosity vs. shear rate plot:  min

 BD  BU   100  Thixotropy index    BD 

 

 min

BD

  BU  d   100

 min



BD

(2)

d 

 min


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where BD and BU represent the areas under the breakdown and build-up curves respectively, and ηBD and ηBU, the viscosities during the increasing and decreasing shear rate ramp, respectively.41 Finally, the viscoelasticity of the samples was characterized by dynamic experiments run on fresh samples. A frequency sweep test, from 0.63 to 250 rad/s, at a constant strain of 3% was performed. Amplitude sweep tests allowed to verify that with the chosen applied strain (3%) the samples are in the linear regime,33 and the torque of the rheometer is significantly higher than the lower limit of the instrument.42, 43 All the rheological measurements were carried out using a Kinexus Pro+ (Malvern, UK) rheometer equipped with a peltier cell to control the temperature with a precision of 1x10-2 °C. With multiphase fluids wall slip44 may occur and to prevent or limit it a serrated parallel plate-plate geometry with a diameter of 20 mm is used. It is equipped with a solvent trap to limit light tense evaporation, and a fixed gap of 0.3 mm is used for all the experiments. Such a small gap was chosen so to have the possibility to exploit high shear rates. We checked the instrument alignment by measuring the viscosity at different gaps with the serrated plates.45 We found that the shear rate is independent of the gap for gaps larger than 0.5 mm, while it decreases for lower gaps. The observed behavior is due to an unavoidable intrinsic misalignment of the instrument and to a residual wall slip induced by the flow through the geometry roughness.46 For gaps below 0.5 mm, the viscosity will be consequently underestimated and the data might be post-processed to correct the experimental values.46, 47 However, the residual wall slip will affect all the investigated samples in the same way 46 and consequently the viscosity will be identically underestimated. Since the goal of the paper is only to compare the behavior of different samples, as long as the data are taken at the same gap, the comparison consistency will not be affected by the wall slip. Thus, for the sake of


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simplicity, we will report in the following the data as they are measured without a postprocessing. All the tests were run at 25°C and 1 atm. All experiments were carried out by triplicate, so to be sure that the initial conditions obtained with the manual mixing followed by the sample loading are actually reproducible; the uncertainties are presented as error bars, and it is worth mentioning that maximum a 3% error is recorded among the different replicates in all the rheological test that we run. This small error demonstrates the accuracy in the sample preparation and in the measurement procedure, as well as it guarantees the tests repeatability.

3. Results and Discussion The results reported in this study are mainly divided into four sections: I) asphaltenes chemical composition characterization and aggregation tests, II) the evaluation of the viscosity reduction due to the addition of nanoparticles, the ultrasound cavitation and the combination of the two, III) preliminary investigation of the thixotropy of the samples with a single hysteresis loop experiment and IV) assessment of the treatment effects by dynamical mechanical experiments.

3.1. Asphaltenes chemical composition characterization and aggregation tests It has been mentioned throughout this manuscript that the HO microstructure is formed by the crude oil heavy fractions such as asphaltenes and resins.48 Particularly, the asphaltenes in means of their chemical structure including heteroatoms (oxygen, nitrogen sulfur),49, 50 have a self-association trend fomented by different mechanisms such as Van der Waals forces, Hbonding and π-π stacking interactions,51 leading the aggregation of these molecules, which causes the formation of clusters.52


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It is well known that in light crude oils, this behavior prompts the asphaltenes precipitation/deposition at certain pressure conditions. However, in the HO cases, its microstructure is usually configured in a viscoelastic network.49 The viscoelastic network existence is driven by two particularly important factors, a high amount of resins which stabilize the asphaltenes in the oil matrix, and the asphaltenes content that must be higher than a mass fraction of 5 %.53, 54 It can be said from the asphaltenes content in the evaluated HO that the existence of a viscoelastic network is more than possible. Nevertheless, detailed analyses were carried out for obtaining some more insights over this matter. In Table S1 of the Supporting Information Document it can be observed the chemical composition for the asphaltenes characterized through the XPS technique. The presence of the mentioned heteroatoms could be an indicator of asphaltenes-asphaltenes interaction forces.51 Hence, the asphaltenes clusters formation was studied through aggregation kinetics, and are shown in Figure S1 of the Supporting Information Document, where it can be observed an initial aggregates size growth and a reduction until reaching a stabilized system after 230 min. This phenomenon is explained by the effect of the mixture shearing in the asphaltenes interactions and clusters configuration, which is a similar behavior of that observed in the HO microstructure breakdown after subjecting the fluid to shearing. Similar results have been obtained previously,37 corroborating that the HO microstructure is formed by asphaltenes clusters that are configured in a viscoelastic network. On the other hand, in Figure S1 it is also seen the asphaltenes aggregation kinetics for the asphaltenes in the presence of nanoparticles and ultrasound irradiation. It is observed that both mechanisms have an important effect on the formation of the clusters as these have a lower size and a faster stabilization in comparison with the system without treatment.


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From these results, it can be deduced that the application of ultrasound alongside nanoparticles would have an important effect over HO microstructure. In this sense, this phenomenon was studied by rheological tests for identifying changes in the fluid rheological properties.

3.2. Viscosity reduction evaluation Figure 1 shows the viscosity of the four investigated samples (Table 1) vs. the shear rate as measured during the breakdown (BD) ramp, i.e., while increasing the shear rate. All the samples show a shear thinning behavior, where the viscosity decreases with the shear rate. This is probably due to a shear induced microstructure reorganization, more than to a purely viscoelastic effect. The viscosities of the four samples seem to tend to a zero-shear plateau as the shear rate is decreased, though the plateau value cannot be clearly estimated from the data at hand. A high shear plateau seems to be approached by samples A, B, and C, but not by sample D. Thus, from a practical and engineering point of view, the data can be interpolated with the Cross model [35a], eq. 3, which accounts for both a zero shear and a high shear plateau and that in previous studies involving nanoparticles-heavy-oil systems well interpolated the experimental data.37

   

0   

1   

(3)

m

where, η is the viscosity, α a characteristic relaxation time above which the system shows a shear thinning behavior,  the shear rate, m a constant, η0 the zero shear viscosity and η∞ the viscosity plateau at high shear rates. The predictions of Cross equation, eq. 3, are also shown in Figure 1 as solid gray lines passing through the data. The best-fit parameters are


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reported in Table 2 for the four samples, together with the coefficient of determination, R2. Notice that for sample D we imposed η∞ = 0, since the data do not show even only the trend towards a faraway plateau at high shear rates. Data in Figure 1 clearly show that the sole addition of nanoparticles and the sole sonication are able to similarly decrease the HO viscosity, without however qualitatively changing the rheological behavior of the treated samples with respect to the native HO. Indeed, a tendency towards both the zero shear and high shear plateau can be guessed from the data of samples A, B, and C, as well as their shear thinning behavior is very similar, being the coefficient m (Table 2) of Cross equation almost the same. Conversely, when both functionalized nanoparticles addition and ultrasound cavitation treatment are applied to the HO a significant rheological difference is observed: First, the viscosity is more than halved at each shear rate; the tendency towards a high shear plateau is not observable anymore, last but not least, the shear thinning behavior is changed and a terminal behavior with power law index n = 0.04 (eq. 4) can be identified:   k  n1

(4)

where k is the so-called consistency index. Such a pronounced shear thinning resembles very much that of suspensions.55 Notice that by comparing eq. (4), firstly proposed by Ostwaldde Waele model 56-58 and valid for power law fluids,59, 60 with eq. (3) with η∞ = 0, it is readily obtained: n = 1-m; k = η0 α-m.


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200

100 80

Viscosity [Pa.s]

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

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60 50 40 30 Sample A: HO

20

Sample B: HO + SiNi1 Sample C: HO + Ultrasound Sample D: HO + SiNi1+Ultrasound

10 2

3

4

5

6

8

10

20

shear rate [s

30 -1

40 50 60

80 100

]

Figure 1. Viscosity vs. shear rate of the four samples of Table 1 as measured during the increasing shear rate ramp (BD). A) Heavy oil (HO), B) HO with nanoparticles, C) sonicated HO, D) HO with the addition nanoparticles and sonicated. Error bars are ± the standard deviation of three sets of data. Lines are the predictions of Cross equation, eq. (3) obtained with the best-fit parameters of Table 2. Gray regions highlight the data taken to evaluate the degree of viscosity reduction (DVR). Table 2. Best-fit parameters of Cross equation, eq. 3. The uncertainties are the standard error of the estimated parameter, and R2 is the regression coefficient of determination.

Sample A Sample B Sample C Sample D

R2

η0 [Pa.s]

η∞ [Pa.s]

α [s]

m [-]

0.999986 0.999996 0.999997 0.999931

131.5±5.5 113.5±1.9 102.9±1.4 70.4±3.9

26.4±2.2 32.1±0.6 30.7±0.4 0

0.061±0.004 0.067±0.002 0.063±0.002 0.054±0.007

1.29±0.12 1.57±0.06 1.67±0.06 0.96±0.04

To better quantify the viscosity reduction induced by each treatment and by the combination of the two, the viscosity reduction index, DVR, eq. 1, is calculated at the three shear rates highlighted with the gray shadows in Figure 1. The lowest value, 3.7 s-1, is in the region where the trend toward the zero shear plateau can be observed, the highest values, 70.3 s-1, is in the region where samples A, B, and C are approaching the high shear plateau, and finally the intermediate value, 19.7 s-1 is very close to the value of 20 s-1 at which the viscosity is


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conventionally measured to characterize the fluid rheology in pipeline transportation.8 Figure 2 shows the viscosities and DVR of the four samples. It can be seen that by adding the functionalized nanoparticles to the HO (sample B), a viscosity reduction of about 11% is achieved at the two lowest shear rates and a significantly smaller reduction of 2.7% at the highest shear rate. This can be attributed to the high asphaltenes selectivity and adsorption capability of the used nanoparticles 23, 24 that were both enhanced by assembling active sites of nickel oxide over the support surface.32,

61, 62

According to several studies, the adsorption phenomenon is identified as a potential first mechanism of HO viscosity reduction,19,

37, 63

as it can modify the internal fluid

microstructure,19 disrupting the asphaltene viscoelastic network, or reducing the dimensions of the asphaltene macro-clusters,4 which are the primary causes of the high viscosity of heavy oils. Similarly, the application of ultrasound cavitation to the heavy oil (sample C) induces a viscosity reduction of about 18% at   3.7 s1 , of 16% at 19.7 s-1 and of 8.3% at 70.3 s-1. This can be mainly due to the ultrasound-induced weakening of the asphaltenes-asphaltenes interactions,22 causing a size reduction of their aggregates.64 For the employed nanoparticles concentration and ultrasound irradiation time conditions, it is observed that the sole ultrasound cavitation seems to be more effective than the sole addition of nanoparticles, which is in accordance with the results obtained in a previous study.33 Nevertheless, it is worth to mention that in these preceding results, it was obtained that a dosage of 1000 mg∙L-1 of nanoparticles had a better performance in viscosity reduction than the sole ultrasound irradiation, while by using 2000 mg∙L-1 of SiNi1 with


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90 min of ultrasound irradiation, the process is enhanced due to a better synergy between both mechanisms. Remarkably, the viscosity reduction measured at the highest shear rate in both cases, the sole nanoparticles addition, and the sole ultrasound irradiation, is significantly smaller than those measured at smaller shear rates. This is due to the fact that the high shear rate plateau of the HO seems to be practically unaffected by the single treatment, either nanoparticles addition or ultrasound cavitation, see Figure 1 and Table 2. The dispersing action exerted by the flow results thus comparable to those induced either by the nanoparticles or by the ultrasound cavitation. The two treatments actually promote the asphaltene macro-clusters dispersion, or the asphaltene network disruption, obtained mechanically by the flow, to lower shear rates. Finally, the combination of the two treatments, i.e., the application of ultrasound cavitation in the presence of the functionalized nanoparticles, significantly enhances the viscosity reduction at any shear rate obtaining a DVR of 50% at 3.7 s-1, of 53% at 19.7 s-1 and of 62.5% at 20.3 s-1. As discussed above, the rheology is significantly modified as the high shear plateau is not observable anymore and this leads to the very significant viscosity reduction gained at the highest shear rate. This can be explained considering that a much finer microstructure reorganization is induced by the coupled treatments, and that the obtained fine microstructure results more stable than that of samples B and C. Although the synergistic effects of the two treatments are now proven, it is needed a further investigation of the rheological changes induced by the treatments to assess the mobility and the flow capacity improvements of the crude oil and to understand the mechanisms underneath these improvements. In the following, for the sake of brevity, we will focus only on samples A and D that show the most relevant rheological differences.


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Figure 2. Viscosity (histogram) and DVR (line-symbol plot) calculated at three different shear rates of the four samples of Table 1: A) Heavy oil (HO), B) HO with nanoparticles, C) sonicated HO, D) HO with the addition nanoparticles and sonicated. The error bars are the standard deviation of three sets of data. 3.3. Hysteresis loop tests Crude oils can often show a thixotropic behavior, and a fast way to investigate it is to run hysteresis loop tests.10,

18

The hysteresis loop may highlight the difference between the

dynamics of the material internal microstructure breakdown and build-up in response to an imposed increasing shear rate, or a decreasing one, respectively.15, 38 Results are shown in Figure 3, where the hysteresis loop areas are shadowed. In Figure 3a the viscosity of the BD and BU curves are shown for both samples A and D, while in Fig. 3b the stress vs. shear rate is plotted. In the last case, the shadowed area represents WL (eq. 1a), i.e., the power per unit of volume dissipated by the sample in the loop test. It is clear that WL of HO is much larger than that of sample D. To quantify the observed difference, WL is calculated by first smoothing the data with a cubic spline and then by numerically evaluating the integrals. The results are summarized in Table 3, and it is found that the dissipated power per unit volume by Sample D amounts to about only the 29% of that dissipated by Sample


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A. Also the thixotropy index, eq. 2, is calculated by numerically evaluating the viscosity integrals after having smoothed the data with a cubic spline, and the results are shown in Table 3.

Figure 3. Hysteresis loop tests: a) viscosity vs. shear rate; b) shear stress vs. shear rate. Sample A) Heavy oil (HO), Sample D) HO with the addition of nanoparticles and sonication. Full symbols refer to the increasing shear rate ramps or breakdown (BD) curves, and hollow symbols to the decreasing shear rate ones or build-up (BU) curves. The BD viscosity curves are the same in Figure 1. Error bars are ± the standard deviations of three sets of data. Table 3. Hysteresis loop parameters of the untreated heavy oil (Sample A) and of the heavy oil with the addition of nanoparticles and after sonication (Sample D). WL is the dissipated power per unit of volume; the thixotropy index is defined in eq. (2). Thixotropy Index WL -1 [%] [Pa s ] 5 Sample A 2.9×10 28.3 4 Sample D 8.3×10 15.8 The large difference between both WL and the thixotropy index of the two samples suggests that the original heavy oil shows a thixotropy behavior more pronounced than that of the same oil once treated with both the addition of nanoparticles and ultrasound cavitation. Moreover, it can be noticed that the first points of BU curve of sample A (at the largest shear rates) are slightly larger than the last points of the BD curve, because once at rest the


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microstructure starts to re-buildup, as it always happens in a thixotropic material. The same is not observed for Sample D. Besides this, it is worthwhile noticing that the BU viscosity curve of sample A shows essentially a Newtonian behavior. This can be explained assuming that the flow breaks down the oil microstructure that is not reconstituted in the BU curve while rapidly decreasing, in only 2 min, the shear rate from 100 s-1 to 3 s-1. If the microstructure remains unaltered during the BU curve, accordingly the viscosity does not vary with the shear rate. Conversely, in Sample D the HO original microstructure was already broken down by the synergistic action of asphaltene adsorption on the nanoparticles and ultrasound cavitation, and thus the initial configuration is characterized by a more dispersed system. Probably the shear thinning behavior, in this case, is not due to a further breakdown of the microstructure, but by a geometrical reorganization of it, which is reverted when the shear rate is decreased in the BU curve.

3.4. Viscoelastic moduli To further investigate if the different rheological behavior of samples A and D is due to a change of microstructure, the dynamic moduli of the two samples are measured. The elastic modulus G’, also known as storage modulus, is the modulus of the stress component in phase with the strain, while the viscous modulus G”, also known as loss modulus, is the modulus of the stress component in phase with the shear rate. Hence, G’ accounts for the elastic response of the material and thus for the elastic energy stored during the deformation, while G” accounts for the viscous, plastic, response of the fluid and thus for the energy dissipated during the deformation. In Figure 4 G’ and G” are plotted vs. the imposed frequency. A clear fluid behavior, where G” is significantly larger than G’, is exhibited by both samples, though the low-frequency


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limit of linear viscoelasticity, where G” is proportional to the frequency and G’ to the frequency to the power of two, is not reached in the investigated frequencies. The loss moduli of the two samples almost coincide, while small differences are observable in G’ moduli where that of Sample D is slightly smaller than that of Sample A, at any frequency. This suggests that the differences between the two samples are mainly related to their different elasticity, more than to their different viscous behavior.

Figure 4. G’ (full symbols) and G” (hollow symbols) vs frequency. Circles are for Sample A: Heavy oil (HO), diamonds for Sample D: HO with the addition nanoparticles and sonicated. To better highlight the differences between the two samples, in Figure 5 both the complex viscosity (a) and the phase angle (b) are plotted vs. the frequency. These data can be calculated from the moduli: In materials like polymer melts or polymer solution, the complex viscosity can be directly compared to the viscosity, while the phase angle highlights the relative contribution of the elastic behavior with respect to the viscous one, being 90° for purely viscous materials and 0° for purely elastic ones.65


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The complex viscosity of the two samples is comparable and measurable differences are observed at low frequencies, which correspond to low shear rates, in the region approaching the zero shear plateau. In this region, Sample D appears less viscous than Sample A, in agreement with the viscosity data discussed in Section 3.1.

Figure 5. A) complex viscosity vs. frequency and B) phase angle vs. frequency of Sample A (full symbols): Heavy oil (HO), and Sample D (hollow symbols): HO with the addition nanoparticles and sonicated. The phase angles of the two samples are measurably different, and that of Sample A is always smaller than that of Sample D, confirming that the latter sample is less elastic than the former one. The phase angles are always larger than 45° because G” is always larger than G’ and, as discussed above, the materials exhibit a fluid behavior.

3.5. Relaxation spectra


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A viscoelastic fluid has a behavior in between that of a purely viscous fluid and a purely elastic material; this implies that this material can dissipate part of the energy stored during the deformation with different relaxation mechanisms, each of them with a characteristic relaxation time. Thus, to better analyze the different elasticity of the two samples, their relaxation spectra are here calculated. The relaxation spectrum allows identifying the characteristic relaxation times of the sample, if the last ones lie within the investigated frequencies. The relaxation spectra are calculated from the elastic modulus, G’, of Figure 4 with the approximated equation, eq. (5), of the second order proposed by Tschoegl66 and also from the loss modulus G” with the approximated equation, eq. (6), of the second order of Schwarzl and Staverman:66 2 1 H  t   dG  / d ln   d 2G  / d  ln   2 1/ t/

(5) 2

2 H  t    2 /   G   d 2G  / d  ln     1/ t

(6)

where H (t) is the relaxation spectrum, ω is the frequency expressed in rad s-1 and t is the time expressed in s. To calculate the spectra from the moduli, data of Figure 4 are first smoothed with a third order Bezier polynomial, so to get rid of false results that may come from the scatter of the data, then eqs. (5,6) are applied. The results are shown in Figure 6, where solid lines refer to Sample A, and dashed ones to Sample D. Moreover, black lines are for the spectra calculated from G’, eq. (5), and red lines are used for the spectra calculated from G”, eq. (6). The characteristic relaxation times are identified as the abscissas of the relative maxima of the spectra. Sample A shows a single relaxation time equal to 1×10-2 s, if estimated from the spectrum calculated from G’ (black solid line), and equal to 8×10-3 s, if


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estimated from the spectrum calculated from G” (red solid line). Conversely, both relaxation spectra of Sample D are monotonous and thus no relaxation time is identifiable. This implies that if a relaxation time of Sample D exists, it must lie outside the time range here exploited with the dynamic moduli, and thus it must be shorter than 4×10-3 s. The relaxation spectrum is a material function, thus, in principle, that calculated with eq.(5) should coincide with that calculated with eq. (6). This seldom happens because of two reasons; first, the two equations are approximated, second, the data are affected by an unavoidable experimental error that propagates into the calculated spectra. However, the results that we obtained are quite robust because the relaxation times of Sample A estimated with the two different procedures are in acceptable agreement, and both relaxation spectra calculated for Sample D are monotonous. The existence of a relaxation time is in accordance with the existence of a 3D microstructure formed by the aggregates of asphaltenes that causes the viscoelastic behavior of the HO, which then shows a more pronounced elasticity and a larger viscosity with respect to the treated Sample D. Sample D, in agreement with this, shows the absence of a relaxation time, at least in the time range corresponding to the frequencies at which the experiments were carried out. This suggests that the original viscoelastic 3D network of the HO is disrupted by the addition of the functionalized nanoparticles coupled to the ultrasound cavitation. These results agree with those reported by several authors in the literature, e.g., Dickinson et al.,67 Soo and Woo,68

Behzadfar et al.42 found that bitumens and heavy oils have

characteristic relaxation times associated to the presence of a 3D internal microstructure.


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Figure 6. Relaxation spectra vs. time estimated from the elastic modulus G’ (black lines) and from the loss modulus G” (red lines) of Figure 4. The spectra of the untreated HO, Sample A, are plotted as solid lines, while those of the HO in the presence of 2000 mg∙L-1 of SiNi1 after 90 min of ultrasound cavitation, Sample D, are plotted as dashed lines.

4. Conclusions A novel process involving ultrasound cavitation assisted by nickel oxide nanoparticles functionalized over nanoparticulated silica support was applied to increase the heavy oil mobility at reservoir conditions, and/or to improve the heavy oil flow capacity at surface and transportation conditions. The adopted method led to a viscosity reduction ranging from 50% to more than 63%, by increasing the applied shear rate. We proved that the sole addition of nanoparticles, or the ultrasound cavitation irradiation, is not capable of modifying the HO rheology significantly. A small viscosity reduction is achieved in both cases, while the combination of the two treatments not only reduces the viscosity much more than every single treatment but also modifies qualitatively the HO flow curve. Indeed, the high shear plateau, which starts to be approached by the HO for shear rates larger than 70 s-1, disappears for Sample D where the nanoparticles are added to the HO, and the obtained suspension is subsequently irradiated. Moreover, the response of the two samples to a hysteresis loop test


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is also significantly different as the HO has a power per unit volume dissipated during the test 3.5 times larger than that of Sample D. This last result indicates that the original HO microstructure once broken down by the flow needs a long time to re-buildup, conversely the microstructure of Sample D is so dispersed that either it cannot be broken down by the flow or it is able to reconstitute itself very quickly. Furthermore, the dynamic data in the linear regime show that Sample D is less elastic than the HO and this is corroborated by the estimates of their relaxation spectra that highlight the existence of a relaxation time only for the HO, Sample A. This last result implies that the microstructure of HO is either a viscoelastic network of asphaltenes or it is made of large asphaltenes clusters that can elastically deform, while that of Sample D is probably a suspension-like one. The combined treatments consisting of the addition of nanoparticles with the subsequent ultrasound cavitation of the resulting suspension is then able to break the original HO microstructure. We hypothesize that the asphaltenes stably adsorb on the nanoparticles and that the size reduction of the asphaltenes is clearly enhanced by the ultrasound irradiation. Although further studies are needed to better investigate the mechanisms involving the heavy oil microstructure modification, this paper does not only prove the suitability of the application of this technology to increase the HO flow capacity, but it also demonstrates its enhanced performance by possibly providing a better and more efficient HO production and transportation designing.

5. Acknowledgments The authors would like to acknowledge COLCIENCIAS and Agencia Nacional de Hidrocarburos (ANH-Colombia) for their support provided in Agreement 272 of 2017. They


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would also like to recognize the Universidad Nacional de Colombia for logistical and financial support.

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