Surfactant concentration and pH effects on the zeta potential values of alumina nanofluids to inspect stability

Colloids and Surfaces A 583 (2019) 123960

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Surfactant concentration and pH effects on the zeta potential values of alumina nanofluids to inspect stability

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⁎

Karen Cacuaa,b, , Fredy Ordoñezb, Camilo Zapatab, Bernardo Herrerab, Elizabeth Pabóna, Robison Buitrago-Sierrab a b

Universidad Nacional de Colombia, Sede Medellín, Advanced Material Science Group, Calle 59A 63-20, Medellín, Colombia Instituto Tecnológico Metropolitano, Advanced Materials and Energy Group, Faculty of Engineering, Calle 54A No 30-01, Medellín, Colombia

G R A P H I C A L A B S T R A C T

A R T I C LE I N FO

A B S T R A C T

Keywords: Nanofluids stability zeta potential Alumina nanofluids Isoelectric point

Nanofluids are complex fluids, mainly proposed to improve the efficiency of thermal systems. However, their poor stability, caused by the agglomeration and sedimentation of nanoparticles over time, has limited their practical application. A common technique to increase the stability of nanofluids is to add surfactants, which produce electrostatic or steric repulsion between nanoparticles, thus avoiding their agglomeration. This work evaluated the effects of surfactants and their concentration on the zeta potential and hydrodynamic diameter at different pH values as an indicator of nanofluids stability. Commercial alumina nanoparticles (0.1 wt.%) were dispersed in deionized water using two surfactants (cetyltrimethylammonium bromide, CTAB and sodium dodecylbenzenesulfonate, SDBS) at different concentrations, and the pH values were varied (2–12) by adding hydrochloric acid and sodium hydroxide. The results show the importance of the critical micelle concentration value in the nanofluids stabilization by electrostatic repulsion between nanoparticles and indicate that SDBS at a concentration of 0.064 wt.% (critical micelle concentration) offers the best dispersion conditions according with their zeta potential values, allowing high stability regardless of the pH value of the suspension.

Abbreviation: SDBS, sodium dodecylbenzenesulfonate; CTAB, cetyltrimethylammonium bromide; SDS, sodium dodecyl sulfate; DI, deionized; CMC, critical micelle concentration; IEP, isoelectric point; UV-vis, ultraviolet visible; DLS, dynamic light scattering; DLVO, Derjaguin, Landau, Verwey and Overbeek ⁎ Corresponding author at: Instituto Tecnológico Metropolitano, Medellín, Advanced Materials and Energy Group, Calle 54A 30-01, Medellín, Colombia. E-mail address: [email protected] (K. Cacua). https://doi.org/10.1016/j.colsurfa.2019.123960 Received 19 July 2019; Received in revised form 8 September 2019; Accepted 10 September 2019 Available online 11 September 2019 0927-7757/ © 2019 Elsevier B.V. All rights reserved.

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1. Introduction

Al2O3 and water-CuO nanofluids. In turn, the optimal values of SDBS to produce high stability were 0.1 wt.%(pH≈8) and 0.07 wt.%(pH≈9.5), respectively. Xia et al. [25] used sodium dodecyl sulfate (SDS) and polyvinylpyrrolidone (PVP) as surfactants to improve the stability of alumina nanofluids (1 wt.%). Thus, they obtained stable nanofluids for 48 h; however, nanoparticle sedimentation was evident with SDS concentrations above 2 wt.%. Additionally, the thermal conductivity was found to decrease with the addition of surfactant. In another work, Saleh et al. [36] dispersed titanium dioxide nanoparticles (1% vol.) using three types of surfactant: CTAB, SDS, and Span 80. As a result, the thermal conductivity of the nanofluid was further enhanced by up to approximately 4.7% compared to titanium dioxide nanofluid without surfactant. In the same way, other studies report that nanofluid stability depends on the concentration of the surfactant [19,43,44] and the pH of the nanofluid [45]. The literature mentioned above enables to conclude that nanofluids stability have a dependence of surfactant concentration and the pH value, these factors modifies the surface charge of the nanoparticles looking for an electrostatic repulsion between them. In this way, zeta potential value allows to identify the nanoparticle surface charge and associate this value with the nanofluids stability. Zeta potential values of −30 or +30 mV have been used as a criterion to have nanoparticles dispersed over time [46]. Zeta potential is defined as the electrical potential developed at the solid-liquid interface in response to the relative motion of solid particles and liquid [14]. Reportedly, in order to achieve stable nanofluids, pH values should be kept away from the iso-electric point (IEP) [47]. At such point, the zero zeta potential is found at an specific pH value where the attraction between particles is maximized [43]. Shifting the pH or surfactant concentration will alter the electrical charge density on the nanoparticles’ surface and promote repulsive forces between them [38]. This study evaluates the relation between surfactant concentration and pH values in the zeta potential values as an indicator of Al2O3 nanofluids stability. In a first stage nanofluids stability was evaluated using conventional methods UV–vis absorbance and visual inspection and after, the most stable and less stable nanofluids were used to determine the zeta potential values in function of surfactant concentration and pH value. Also, hydrodynamic diameter was measured simultaneously to associate the particle size with agglomerates formation.

Since nanofluids introduction [1–3], numerous researches to study their thermophysical properties and their behavior in diverse heat transfer systems has been achieved. Thermal conductivity increases up to 100% [4,5] are generally reported with nanoparticle addition to common base fluids. Nevertheless, other properties such as dynamic viscosity and density are increased as nanoparticle concentration increases, which increases the power consumption in pumping systems and this becomes a disadvantage for nanofluids use [6–9]. It is necessary to found and optimal concentration that allow increase the heat transfer capabilities using nanofluids without high penalties in pump systems. In this way, Asadi [10] presented a methodology compose by three steps (step 1, measuring of thermophysical properties; step 2, use Prasher [11] and Mouromtseff [12] figures-of-merit; step 3, if the requirements of figures-of-merit are meet, use heat transfer equations to estimate the heat transfer coefficients) to evaluate a nanofluid as a potential heat transfer fluid. Nevertheless, total understanding of nanofluids behavior in different thermal devices where are used is not complete yet due mainly to stability issues. Preparing stable nanofluids is one of the main challenges in the field of nanofluids [4,8,13–19] because stability is highly dependent on the surface forces acting between particles. Interactions between repulsive and attractive forces define the formation of nanoparticle agglomerates [20]. In addition, the rate of aggregation of nanoparticles is known to be determined by the frequency of collisions caused by Brownian motion and the probability of cohesion between nanoparticles [21]. Nanofluids can be obtained by one-step and two-step methods. In one-step method, nanoparticles are made and dispersed into the base fluid simultaneously. On the contrary, in the two-step method, nanoparticles are produced first and then they are dispersed in a subsequent stage. Two-step method is the most common method used to prepare nanofluids [22–26]. In this method, nanoparticles are agglomerated before the dispersion and ultrasonic power is commonly applied to break these agglomerates and to disperse them in the base fluid [10,27]. Optimal ultrasonication times at specific powers are necessary depending on the nanoparticle type and the base fluid in order to obtain a good dispersion and then long-term stability [28–31]. However, after dispersion using only ultrasonic power, nanoparticles remain with a high surface energy, which promotes their agglomeration over time and then the nanofluid will be unstable [20,32]. Therefore, this dispersion technique is commonly combined with other stabilization techniques such as steric or electrostatic repulsion to obtain long-term stable nanofluids [33]. The most common technique to improve nanoparticle dispersion in several base fluids is electrostatic stabilization, which modifies the surface charge of nanoparticles using surfactants or varying the pH [25,33,34] Such surface-active agents (generally called surfactants) are amphipathic molecules composed of a non-polar portion attached to a (hydrophilic) polar or ionic portion. The hydrophilic portion can be anionic, cationic, non-ionic, or zwitterionic [35]. Due to their amphiphilic structure, surfactants adsorb at interfaces, thus modifying properties such as surface tension and wettability; moreover, surfactants can alter the thermophysical properties of nanofluids. Thermal conductivity increases [36,37] or decreases [25,38] have been found with surfactant addition. Viscosity generally increases with surfactant addition [37–41]. Selection of the type and concentration of the surfactant in different heat transfer systems should attempt to a balance between stability and the effect on these important properties. In this regard, Li et al. [42] evaluated the dispersion behavior of Cu nanoparticles in water (0.1 wt.%) using CTAB, SDBS, and polyoxyethylene (10) nonyl phenyl ether (TX-10) as stabilizers. They found their optimal mass fractions to be 0.43, 0.05, and 0.07 wt.%, respectively, at a pH of 9.5. In another work, Wang et al. [34] studied the effect of using SDBS and pH variations on the stability and thermal conductivity of water-

2. Materials and methods Alumina (Al2O3) nanoparticles (< 50 nm, from Sigma-Aldrich) were used to prepare the nanofluids (0.1 wt.%) employing DI water (< 0.1 MΩ. cm resistivity) as the base fluid. Alumina nanoparticles were used due to their availability and because it is one of the most extensively used and characterized material to prepare nanofluids [22,45,48–50]. All the nanofluids were set by triplicate to ensure reproducibility. The results are reported as the mean value with the standard deviation of all the measured values. Anionic sodium dodecylbenzenesulfonate (SDBS, Sigma-Aldrich) and cationic cetyltrimethylammonium bromide (CTAB, ≥98% Sigma-Aldrich) were used as surfactants at two different concentrations in terms of critical micelle concentration (0.5 CMC and 1 CMC). Surfactant quantities (for CMC concentration) to prepare the nanofluids (20 mL) were 0.064 g and 0.036 g for SDBS and CTAB, respectively. Nanofluids were prepared by the two-step method and the nanoparticles were dispersed using a Qsonica Q500 Sonicator operated at 20 kHz. The ultrasonication time and amplitude were 20 min and 30%, respectively. The pH values (Lab 850, SI Analytics) were varied between 2 and 12 by adding hydrochloric acid (HCl, 0.1 M) and sodium hydroxide (NaOH, 0.1 M). Table 1 presents the list of abbreviated names used in this work to refer to different combinations of nanofluid, surfactant, and critical micelle concentration. 2

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Table 1 Nomenclature of the nanofluids. Fluid

Symbol

DI Water Al2O3-Water Al2O3-SDBS-0.5 CMC Al2O3-SDBS-1.0 CMC Al2O3-CTAB-0.5 CMC Al2O3-CTAB-1.0 CMC

W A A-S-0.5 A-S-1.0 A-C-0.5 A-C-1.0

2.1. Stability evaluation In a first stage nanofluids stability was inspected using UV–vis spectroscopy (Agilent 8453) and dynamic light scattering (DLS; NanoPlus HD). Absorbance and hydrodynamic average diameter variation were monitored for more than 20 days. Additionally, a Samsung ST200 F 1280 × 720 digital camera was utilized for the visual inspection and a qualitative analysis of the nanoparticle sedimentation process. Absorbance was measured at the maximum absorption wavelength experimentally determined for alumina nanofluids: 288 nm. Subsequently, the most stable and the less stable nanofluids were selected to evaluate the effect of surfactant concentration and pH value in the zeta potential values. An additional concentration of 0.2 CMC was evaluated to inspect their effect in the zeta potential value. Also, hydrodynamic diameter was measured in each point to compare the average diameter of particles disperse with the zeta potential value as nanofluids stability criteria (−30 or +30 mV). pH values (Lab 850, SI Analytics) were varied between 2 and 12 by adding hydrochloric acid (HCl, 0.1 M) and sodium hydroxide (NaOH, 0.1 M). Zeta potential and hydrodynamic average diameter were measured using an analyzer (Nanoplus HD, micromeritics).

3. Results Fig. 1 illustrates the absorbance variation of alumina nanofluids without surfactant as well as with SDBS and CTAB. The high absorbance at the beginning of the experiment is related to a higher amount of nanoparticles dispersed in the fluid; nevertheless, a sharp decrease can be observed in all the cases before five days have passed. Although all the nanofluids presented sedimentation and some dispersed nanoparticles over time, the nanofluid with SDBS at 1 CMC and that with CTAB at 0.5 CMC achieved the lowest and highest absorbance variation, respectively. Fig. 2 is a series of pictures of the nanofluids taken on different days. Alumina-SDBS 1 CMC exhibited a lower rate of sedimentation compared to its alumina and alumina-CTAB counterparts. However, the sedimentation rate of alumina-CTAB 0.5 CMC was higher,

Fig. 2. Visual inspection of the nanofluids.

thus confirming the absorbance results (Fig. 2). Furthermore, the alumina nanofluids without any added surfactant show good dispersion, even better than those that contain surfactants at concentrations below the CMC. This is due to the fact that, in polar liquids, alumina is able to develop a significant amount of surface charge that can enhance dispersion stability by electrostatic repulsion [51]. In the case of alumina nanoparticles with SDBS at 1 CMC, the improved dispersion behavior was caused by the positive surface charge of alumina in an aqueous medium and its strong affinity for anionic groups—in this case, the phenyl sulfonic group formed by the dissociation of SDBS [34]. Conversely, CTAB is a cationic surfactant and, hence, its head group experiences a natural repulsion to the positivelycharged alumina surface destabilizing the nanofluid [52]. Additionally, at a critical micelle concentration, a maximum alumina surface coverage by the surfactant is obtained by micelle formation and a better surface coverage [51]. This result is in agreement with other works, Khairul et al. [38] and Zawrah et al. [43], where SDBS was found to have optimal concentrations of 0.1 wt.% and 1 wt.% respectively, for alumina nanofluids—both concentrations exceeding the CMC. Additionally, surfactant concentrations below the CMC are not

Fig. 1. Absorbance variation of alumina nanofluids. 3

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Fig. 3. Nanoparticle-size distribution obtained by DLS.

The nanofluid without surfactant reveals a low-intensity peak in the range of diameters under 50 nm, indicating the presence of nanoparticles. The distribution behavior of the nanofluids without surfactant and with SDBS 1 CMC (the most stable) was similar; however, the intensity of the compound with CTAB 0.5 CMC (the most unstable) was lower even after 24 days, suggesting a low presence of nanoparticles and nanoclusters. The final average diameter of all the particles in the nanofluids prepared in this study, after agglomeration and sedimentation, was below 123 nm, i.e., larger than the primary nanoparticles (< 50 nm). This could be explained by the fact that, during dispersion, several layers are produced by hydration/solvation and the ions present in the fluid can be adsorbed by the surface of nanoparticles or nanoclusters, thus increasing their hydrodynamic diameter. Commonly, the surface chemistry of the particles evaluated by DLS is different from those originally synthesized [53]. However, in both cases the addition of surfactant generates and smaller mean size at the first day of preparation, in comparison with the nanofluid without surfactant.

enough to generate strong repulsive forces according to the DLVO theory [35] because they fail to cover the nanoparticles completely, which creates a charge misbalance and produces the aggregation and sedimentation of alumina nanoparticles. Fig. 3 details the particle size distribution of alumina in the nanofluid without surfactant (a), with SDBS 1 CMC (b), and with CTAB 0.5 CMC (c) measured on the day of preparation and 24 days afterward. The three nanofluids show the same tendency: a broad distribution on day 1 followed by a reduction of the same at the end of the measurements. Also, the polydispersity index (PI) was under 0.3 and the mean particle sizes were between 115 and 120 nm. This behavior can be explained by two phenomena. On the one hand, the energy applied during the sonication processes may have not been enough to break the initial clusters of alumina and some big agglomerates remain after sonication. On the other hand, there is a surface charge misbalance at the start of the experiment and the Brownian motion produces collisions that result in a quick agglomeration. Over time, the agglomeration of nanoparticles causes larger clusters to sediment and the hydrodynamic average diameter of the nanoparticles decreases as a result.

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experimental results, its zeta potential was below +30 mV, thus confirming its low stability identified in the absorbance results. With pH values lower than 6, the nanofluid can be stable according to zeta potential criteria; nonetheless, fluids with low pH values should not be recommended for heat transfer systems due to corrosion problems [21]. These results of average diameter are in good agreement with the zeta potential measures because the size of the clusters increases significantly if the values are near the IEP. Conversely, the particle size was approximately 123 nm with zeta potential values near or above +/-30 mV. This finding confirms that zeta potential value is a good indicator to evaluate the stability of nanofluids. 4. Conclusions Stability of alumina nanofluids was evaluated experimentally using UV–vis absorbance and visual inspection after using two surfactant types at two concentrations. The UV-absorbance of all the nanofluids evaluated decreased over time, indicating agglomeration and sedimentation of nanoparticles agglomerates. However, the variation was slight for alumina nanofluids using SDBS at 1 CMC as surfactant. Also, a critical micelle concentration resulted in better stability for all the surfactants examined in this work. Zeta potential and hydrodynamic diameter measures allowed to confirm the stability results obtained by UV–vis absorbance and visual inspection. In the case of SDBS at 1 CMC, the nanofluids were stable regardless of pH value; nevertheless, with CTAB and the surfactant concentrations previously evaluated, stability was possible with pH values below 6. Finally, zeta potential value is a good indicator of nanofluid stability. Zeta potential values above or below 30 mV indicates strong repulsion forces and therefore a good stability is insured.

Fig. 4. Zeta potential measures with different SDBS concentrations and pH values.

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements

Fig. 5. Zeta potential measures of alumina 0.1 wt.%-DI water as a function of different CTAB concentrations and pH values.

The authors gratefully acknowledge the financial support of COLCIENCIAS – Colombia (1118-669-46092 CTO: 126-2015), Universidad Nacional de Colombia, and Instituto Tecnológico Metropolitano de Medellín – Colombia.

3.1. Zeta potential Fig. 4 is a plot of the zeta potential values and hydrodynamic diameter of nanoparticles as a function of pH values with different SDBS concentrations. In particular, a pH of 8.6 was found to be the isoelectric point (IEP) of the alumina nanofluid without surfactant. When SDBS was added at a low concentration (0.2 CMC) the IEP was slightly moved to the left; nevertheless, the zero potential for concentrations above this value (0.5 and 1 CMC) was not found. SDBS at 1 CMC was found to enable zeta potentials values near or under -30 mV, far from the IEP and independent of the pH value that was established. This result is in line with the findings mentioned above for this SDBS concentration in the nanofluid without pH modifications. Moreover, the pH value for this surfactant concentration was 8.62 ± 0.02, thus enabling its use in heat transfer devices without important corrosion problems [21]. The hydrodynamic average diameters could not be measured at a pH value of 12, likely due to a high number of ions present in the solution caused by the addition of NaOH. A large quantity of ions generates a compression of the electrical double layer and a decrease in the absolute value of the zeta potential. These circumstances lead to the agglomeration and sedimentation of nanoparticles [45]. On the other hand, Fig. 5 reports the results for the alumina nanofluid with CTAB, which is unstable at a concentration of 0.5 CMC. The initial pH value of such nanofluid was 6.75 ± 0.022 and, according to

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