Tuning Nanoparticle–Micelle Interactions and Resultant Phase

Dec 4, 2017 - Small-angle neutron scattering (SANS) and dynamic light scattering data show that the surfactant micelles adsorb on the surface of the n...
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Tuning Nanoparticle−Micelle Interactions and Resultant Phase Behavior Debes Ray,† Sugam Kumar,† Vinod Kumar Aswal,*,† and Joachim Kohlbrecher‡ †

Solid State Physics Division, Bhabha Atomic Research Centre, Mumbai 400 085, India Laboratory for Neutron Scattering, Paul Scherrer Institut, CH-5232 PSI Villigen, Switzerland

‡

S Supporting Information *

ABSTRACT: The evolution of the interaction between an anionic nanoparticle and a nonionic surfactant and their resultant phase behavior in aqueous solution in the presence of electrolyte and ionic surfactants have been studied. The mixed system of anionic silica nanoparticles (Ludox LS30) with nonionic surfactant decaethylene glycol monododecylether (C12E10) forms a highly stable clear phase over a wide concentration range of surfactant. Small-angle neutron scattering (SANS) and dynamic light scattering data show that the surfactant micelles adsorb on the surface of the nanoparticle, resulting in micellar-decorated nanoparticle structures. With the addition of a small amount of electrolyte into this system, the stability gets disturbed substantially and turns to a two-phase (turbid) system. The evolution of interaction in this system has been examined, and it was found that micelle-induced long-range depletion attraction (modeled by a double Yukawa potential) between nanoparticles leads to their aggregation. Interestingly, the addition of anionic surfactant sodium dodecyl sulfate (SDS) in this two-phase system transforms it to a transparent one-phase state, suppressing the depletion-mediated aggregation of nanoparticles. This is attributed to the formation of anionic C12E10−SDS mixed micelles, and it is their repulsive micelle−micelle interaction that disrupts the depletion phenomenon. On the other hand, the addition of cationic surfactant dodecyl trimethylammonium bromide (DTAB) to the turbid LS30−C12E10 electrolyte system shows no change in the turbidity arising from an aggregated nanoparticle system. The driving interaction, in this case, is different from that of the surfactant-mediated depletion attraction; it is due to the attraction between the nanoparticles mediated by the presence of oppositely charged DTAB micelles between them, resulting in a charge-driven bridging aggregation of nanoparticles. Each of these multicomponent systems has been investigated using contrast variation SANS measurements for different contrast conditions where the role of individual components (nanoparticle or surfactant) in the mixed system has been selectively studied. These results thus show that nanoparticle−surfactant micelle interactions can be tuned by the presence of electrolyte and/or choice of surfactant combination.

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INTRODUCTION

and hence can modify their properties synergistically, which governs the self-assembly and interfacial processes.10−12 A surfactant molecule is amphiphilic by nature and can be ionic (anionic/cationic), zwitterionic, or nonionic. These molecules in aqueous solution self-assemble to form micelles where lipophobic parts of the surfactants form the interior (micellar core) while lipophilic parts face the solvent.13,14 The presence of surfactant micelles in a nanoparticle solution can either enhance its stability or destabilize the solution. The degree of interactions between nanoparticles and surfactants, and thus their resultant phase behaviors, as well as resultant structures can be tuned by varying the charge state of the surfactant.18−20 In the case of similarly charged nanoparticles and surfactants, they do not interact directly and remain

In recent times, the demand for nanoparticle−macromolecule conjugates involving several macromolecular nanostructures such as proteins, polymers, and surfactants to formulate application-specific functional complexes has grown considerably. The interaction of these macromolecules with nanoparticles is utilized for applications associated with colloidal stability, preferential targeting, drug delivery, cosmetics, functional interfaces, etc. 1−5 The interaction of the two components, which is a cumulative form of a number of interplaying forces (e.g., electrostatic, covalent, hydrophobic interactions, hydrogen bonding, etc.), strongly depends on the physicochemical properties (size, shape, surface chemistry, charge density, solution conditions, etc.) of the nanoparticles as well as the macromolecules used.6−9 Also, depending on the system conditions, the presence of nanoparticles may induce structural transitions in the macromolecules or their conjugates © XXXX American Chemical Society

Received: September 30, 2017 Revised: December 4, 2017 Published: December 4, 2017 A

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data in the scattering vector Q [= 4π sin θ/λ, where λ is the wavelength of the incident neutrons and 2θ is the scattering angle] range of 0.006−0.25 Å−1. Freshly prepared samples were held in quartz cells having thicknesses of 2 mm, and the temperature was kept constant at 30 °C during the measurements. The data were corrected and normalized at absolute scale using a standard procedure. All nanoparticle−surfactant systems were studied with the three contrast conditions: (i) no component is contrast-matched, (ii) silica nanoparticles are contrast-matched, and (iii) surfactants are contrastmatched. A multicomponent system can be simplified to study its constituents by selectively contrast-matching them with the solvent. The fact that the scattering length densities of H2O and D2O are very different from each other allows the contrast-match point to be obtained by mixing them in a ratio where the scattering length density of an H2O/D2O mixed solvent matches with the particular component to be contrast-matched (see Table ST1 in the Supporting Information). The contrast-match point depends on the chemical composition of the constituents. The contrast-match point of silica nanoparticles is around 62 vol % of D2O in a D2O/H2O mixed solvent, whereas in the case of C12E10 or SDS micelles, the value of the contrast-match point is around 13 vol % D2O.22 Small-Angle Neutron Scattering Analysis. In SANS measurements, the differential scattering cross-section per unit volume (dΣ/ dΩ) as a function of wave vector transfer Q is measured. In the case of a system of monodisperse particles in a medium

independent in the solution. On the other hand, for oppositely charged nanoparticles and surfactants, strong attractive interaction between the nanoparticles mediated by the micelles leads to the aggregation of nanoparticles. For nonionic micelles, it is known that they get adsorbed on the nanoparticle surface. Besides this, the presence of additives in these systems also acts as an important factor. For example, the electrolyte has been seen to play a crucial role in controlling not only the nanoparticle−nanoparticle or micelle−micelle interactions but also nanoparticle−micelle interactions.21,22 The versatile nature of the nanoparticle−surfactant conjugates can accomplish the needs of a vast array of practical application areas, which include mineral and petroleum processing, biological systems, pharmaceutical sciences, personal care products, foods, and crop protection, among others.23−27 Depending on the requirements of these applications, tunability of the phase behaviors in nanoparticle−surfactant systems is crucial, and this is highly advantageous if it can be controlled in a particular nanoparticle−surfactant system with the addition of different combinations of surfactants or additives. In the present work, we have examined the interaction and resultant phase behavior of the mixed system of anionic silica nanoparticles (Ludox LS30) and nonionic surfactant decaethylene glycol monododecylether (C12E10) in the presence of electrolyte and ionic surfactants. The LS30−C12E10 system forms a transparent stable phase over a wide range of concentrations of C12E10. It turns turbid immediately, indicating aggregation of nanoparticles when a small amount of electrolyte (NaCl) is added. Surprisingly, this two-phase turbid system becomes transparent after anionic surfactant sodium dodecyl sulfate (SDS) beyond a certain concentration is added. However, nanoparticles remain in a turbid two-phase system when mixed with cationic surfactant dodecyl trimethylammonium bromide (DTAB). We have investigated the interactions responsible for these different phase behaviors and the structures coming out as a result of them. Scattering techniques, small-angle neutron scattering (SANS) and dynamic light scattering (DLS), have been used to study these multicomponent systems in terms of their intercomponent interactions and resultant structures. SANS, with the possibility to contrast-match the individual components, is an ideal technique to study such multicomponent systems. Understanding these interaction−structure relationships for tuning the properties of nanoparticle−surfactant micelle systems is required for their desired applications.

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⎛ dΣ ⎞ 2 2 ⎜ ⎟(Q ) = nV (ρ − ρ ) P(Q )S(Q ) + B p s ⎝ dΩ ⎠

(1)

where n denotes the number density of particles, ρp and ρs are, respectively, the scattering length densities of particle and solvent, and V is the volume of the particle.29,30 P(Q) is the intraparticle structure factor, and S(Q) is the interparticle structure factor. B is a constant term representing incoherent background scattering, which is mainly due to the hydrogen present in the sample. The data have been analyzed by comparing the scattering from different models to the experimental data. The calculation and modeling of different terms in eq 1 are described in detail in the Supporting Information. The silica nanoparticles have been fitted with a model of polydispersed spherical particles where radius and polydispersity are the fitted parameters. The parameters for micelles of nonionic surfactant C12E10 have been calculated using a model consisting of a spherical core attached with Gaussian chains. Micelle-decorated nanoparticles have been modeled as a combination of four contributions: two terms correspond to the scattering from nanoparticles and micelles, a cross-term between the adsorbed micelles and the nanoparticles, and a cross-term between different adsorbed micelles on the nanoparticle surface. The evolution of the interaction of nanoparticles has been studied from analyzing the structure factor of a double Yukawa potential, where both the attractive and repulsive interactions in the system are taken care of. The nanoparticles undergoing aggregation have been analyzed using the models of the fractal structure, mass fractal, or surface fractal. Throughout the data analysis, the corrections were made for instrumental smearing, where the calculated scattering profiles smeared by the appropriate resolution function to compare with the measured data. The fitted parameters in the analysis were optimized using the nonlinear least-squares fitting program to the model scattering.31−33

EXPERIMENTAL SECTION

Materials. Electrostatically stabilized 30 wt % colloidal suspensions of silica nanoparticles (Ludox LS30) and surfactants C12E10, SDS, and DTAB were purchased from Sigma-Aldrich. Distilled deionized water from a Millipore Milli-Q unit and 99.9% pure D2O were used for the sample preparation. Samples were prepared by dissolving a weighed amount of silica nanoparticles and surfactants in a mixed D2O/H2O solvent in the absence or presence of an electrolyte (NaCl). The solvents H2O and D2O provide different contrasts for the constituents because of the very different neutron scattering lengths for H and D. Methods. Small-angle neutron scattering experiments were performed at the SANS-I instrument at the Swiss spallation neutron source, SINQ, Paul Scherrer Institut, Switzerland.28 The mean wavelength (λ) of the incident neutron beam was 8 Å, with a wavelength resolution of approximately 10%. The scattered neutrons were detected using a 96 × 96 cm2 detector. The experiments were performed at two sample-to-detector distances, 2 and 8 m, to cover the

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RESULTS AND DISCUSSION Phase Behavior of the Nanoparticle−Micelle Systems. The phase behavior of a system is an important feature to study the system under varying parameters. It is indicated by phase separation, order/disorder transitions (gas/fluid or fluid/crystal transitions), solution turbidity, change in solution color, gel formation, etc. In colloidal systems, the common variables that induce a change in phase behavior are temperature, solute concentration, particle size/shape, osmotic pressure, additives, B

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Figure 1. (a) Phase behavior of 1 wt % LS30 silica nanoparticles with varying C12E10 concentrations and possible models of the resultant structures. Inset: Possible models for LS30−C12E10 interactions. (b) Phase behavior of 1 wt % LS30 with 1 wt % C12E10 in the presence of varying NaCl concentrations.

ionic strength, etc.34−38 The phase behavior of a nanoparticle− nonionic surfactant system and the role of the addition of electrolyte and ionic surfactant have been investigated in Figure 1. Figure 1a shows the phase behavior of 1 wt % LS30 silica nanoparticles in the presence of varying C12E10 concentrations. The phase behavior studies were carried out by measuring the intensity of transmitted light (λ = 532 nm) through the samples. The system of nanoparticles with C12E10 is transparent and one-phase, having a percent transmission of almost 95% throughout the surfactant concentration range. This may be happening because either there is no physical interaction between nanoparticle and surfactant or some conjugate structure (e.g., core−shell structure) is getting formed that does not change the scattering much (inset of Figure 1a). However, with the addition of a small amount of electrolyte (NaCl) into the system, the sample transparency starts decreasing continuously with increasing salt concentration. This is evident from Figure 1b, where the transmission measurements clearly show that beyond a certain electrolyte concentration (∼0.01 M) the percent transmission starts falling with increasing electrolyte concentration, and the system becomes completely turbid around 0.1 M. This is an indication of the formation of large structures (e.g., aggregation) when electrolyte is present in the system. It should be mentioned that electrolyte alone in the respective silica nanoparticle or nonionic micellar solution does not show any such aggregation.22 This suggests that the presence of electrolyte gives rise to a synergistic effect on interactions of nanoparticles and surfactant micelles in the solution. This phase behavior shows an interesting change when the ionic surfactant is added into the above nanoparticle−surfactant system, as shown in Figure 2. The turbid solution of LS30− C12E10 in electrolyte solution transforms to be transparent and single phase upon the addition of anionic surfactant SDS. This transparent phase is similar to that is seen when LS30 nanoparticles interact with an anionic surfactant over a wide concentration range. In this case, similarly charged (anionic) nanoparticles and surfactant micelles are known to be physically noninteracting and remain as individual components.15−18 Also, no depletion interaction or its consequences are seen in this system. On the other hand, LS30−C12E10 in an electrolyte solution shows no change in its turbid phase upon the addition of cationic surfactant DTAB. This turbid phase is identical to

Figure 2. Phase behavior of 1 wt % LS30 with 1 wt % C12E10 in the presence of varying SDS and DTAB concentrations in 0.1 M NaCl solution.

that experienced in a system of LS30 interacting with a cationic surfactant, where bridging by oppositely charged micelles leads to the aggregation of nanoparticles.18 These results thus suggest that the phase behavior of nanoparticle−micelle interactions can be tuned through a selective combination of nonionic and ionic surfactants. Further, scattering techniques have been utilized to look into the evolution of interactions and structures in order to understand this phase behavior. Evolution of Interaction and Structure in the Nanoparticle−Nonionic Micelle System. To start, the LS30− C12E10 system was studied using contrast-matching SANS experiments under three different contrast conditions: in D2O, 13 vol % D2O (contrast match point of C12E10), and 62 vol % D2O (contrast match point of silica nanoparticles), and the corresponding data are shown in Figure 3a−c, respectively. From the analysis of the data in D2O using a polydispersed spherical particle model (eq S2), the mean radius of the spherical nanoparticles was found to be 82 Å, whereas spherical micelles of C12E10 are of core radius of 17.5 Å with an aggregation number of 60. The form factor for C12E10 has been calculated using a model for micelles consisting of a spherical core attached with Gaussian chains.39 The radius of C

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Figure 3. SANS data of 1 wt % LS30 silica nanoparticles in the presence of 1 wt % C12E10 under three different contrast conditions: (a) D2O, (b) 13 vol % D2O (surfactant micelles are contrast-matched), and (c) 62 vol % D2O (LS30 nanoparticles are contrast-matched).

ionized form (SiO−). It is to be noted that some −SiOH groups will be present that are not ionized and hence available to form hydrogen bonds with hydrophilic groups of C12E10 surfactant. However, the decrease in the number of such groups will also decrease the effective hydrogen bonding interaction for a hydrophilic chain (number of groups that interact with the nanoparticle surface) to adsorb. This effectively results in the desorption of C12E10 micelles. Next, we studied the microstructural changes occurring in this micelle-decorated nanoparticle system in the presence of electrolyte when it turns turbid, as observed in the phase diagram in Figure 1b. Figure 4 shows the SANS data of 1 wt % LS30 in the presence of 1 wt % C12E10 with the addition of varying electrolyte concentrations in the surfactant contrast-matched condition (13 vol % D2O). Initially, when the electrolyte is added to this system in small amounts, the SANS data remain almost the same except at the low-Q region, where the data lifts upward with increasing electrolyte concentration. However, above a certain electrolyte concentration (>30 mM), the overall data changes its pattern, with the appearance of a hump at 0.035 Å−1 and sharp upward linearity at the low-Q region. All of the SANS data are categorized in three different sets based on the concentration of the electrolyte. To understand this in a better way, DLS measurements were also performed in the first regime (low electrolyte concentration). When the electrolyte is added at very low concentration (5 mM) to the nanoparticle-

gyration (Rg) of the hydrophilic chain of the micelle is found to be 12.2 Å. SANS data for the mixed system of LS30−C12E10 in D2O as shown in Figure 3a has a scattering contribution both from the nanoparticles and the surfactant micelles, but the scattering is not simply additive (inset of Figure 3a), indicating the formation of a conjugated system. Contrast-matching SANS measurements were used to simplify this multicomponent conjugates. The measurements done at 13 vol % D2O show diminished scattering from C12E10 micelles, and as a result, only LS30 nanoparticles contribute to the scattering crosssection. In this case, Figure 3b shows that there is no significant change in the structure and/or interaction of the nanoparticles in the presence of micelles. On the other hand, information about the changes in the surfactant in the mixed nanoparticle− surfactant system is evidenced from the data measured in 62 vol % D2O solvent (Figure 3c). The analysis of the data (using eqs S11 and S12) confirms the formation of micellar-decorated nanoparticle structures where the C12E10 micelles rearrange themselves to get adsorbed on the surface of LS30 nanoparticles coexisting with some free micelles. The calculations show that the number of micelles adsorbed on each nanoparticle is around 52 and that about 84% of the total micelles get adsorbed. This adsorption can be understood as the formation of hydrogen bonding of the hydrophilic region of surfactant with surface silanol groups (−SiOH) of silica nanoparticles or their D

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of the interaction potentials. The parameters for the repulsive potential, K2 (related to effective charge) and Z2 (related to ionic strength), have been calculated from the data of pure silica nanoparticle solutions using the screened Coulomb potential as in eqs S9 and S10. K1 and Z1 are the parameters of the attractive potential, which are used as the fitted parameters. The calculated and fitted parameters for regimes I, II, and III are given in Table 1, parts a−c, respectively. The value of K2 Table 1. Fitted Parameters of the Interaction and Structure of 1 wt % LS30 + 1 wt % C12E10 with Varying Concentrations of Electrolyte (NaCl)a (a) low electrolyte concentration regime

Figure 4. SANS data of 1 wt % LS30 with 1 wt % C12E10 in the presence of varying electrolyte concentrations in 13 vol % D2O.

electrolyte concentration C (mM) 0 5 10 15 20 (b) medium electrolyte

decorated micellar conjugate structure of LS30−C12E10, the hydrodynamic size of the conjugate decreases considerably and is similar to that of the nanoparticles (see Supporting Information Figures S1 and S3). This can be understood by the inability of the surfactant micelles to get adsorbed on the surface of nanoparticles even in the presence of a small amount of electrolyte where Na+ ions interact with the SiOH (or SiO−) groups so strongly that the adsorption of surfactant molecules is suppressed.21,40,41 This is reflected by an increase in the hydrodynamic size when the electrolyte concentration further increases, indicating a decrease in nanoparticle repulsion. The nonadsorption of C12E10 micelles can induce depletion interaction between nanoparticles. That is why the nanoparticles start aggregating with the increase in the electrolyte concentration in the second regime of medium electrolyte concentration. In this regime, the particles undergoing aggregation coexist with the aggregated nanoparticles. The third regime (higher electrolyte concentration) with a dominant depletion interaction consists of fractal structures formed by the nanoparticle aggregates. The evolution of the interaction in regimes I and II has been determined from analysis of the structure factor S(Q) (Figure 5a) of a double Yukawa potential accounting for the attractive and repulsive interactions in the system. The structure factors of these data are obtained by dividing the scattering data by the data of the nanoparticles. The double Yukawa potential comprises four parameters, K1, K2, Z1, and Z2, which give the strength (proportional to K) and range (proportional to 1/Z)

electrolyte concentration C (mM) 25 30 35

K2

K2

Z2

K1

Z1

5.2 1.0 5.0 1.3 3.9 6.5 0.8 5.5 6.7 0.6 6.7 7.4 0.5 7.7 7.6 concentration regime Z2

K1

Z1

0.4 8.6 9.3 18.7 0.4 9.4 11.3 4.8 0.3 10.1 14.6 3.6 (c) high electrolyte concentration regime

30.0 27.4 27.0 26.2 25.0

Ds

fagg

2.8 2.8

0.37 0.82

electrolyte concentration C (mM)

Ds

fagg

40 45 50

2.4 2.3 2.3

1.0 1.0 1.0

a

The parameters K1, Z1 and K2, Z2 are the parameters of attractive and repulsive interactions between the nanoparticles, and Ds (surface fractal dimension) and fagg (fraction) are fitted parameters of aggregated nanoparticles.

decreases and Z2 increases with the increase in the electrolyte concentration. The attractive potential in pure silica nanoparticles (without any electrolyte) is fitted with the van der Waals interaction using eq S5. The value of K1 increases and Z1 decreases with the addition of electrolyte. The attractive interaction represents the induced depletion attraction in the system; as a result, the micelles become nonadsorbing with the

Figure 5. Variation of (a) structure factor and (b) corresponding total interaction potential responsible for the aggregation of 1 wt % LS30 silica nanoparticles in the presence of 1 wt % C12E10 surfactant as a function of NaCl concentration. E

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an evolution of the interaction with more and more SDS going into the LS30−C12E10−NaCl system, and the effective particle hydrodynamic size decreases, indicating a shift from the aggregated turbid phase toward a transparent phase (as in the phase diagram, Figure 2). Figure 7a−c shows the SANS data of 1 wt % LS30 in the electrolyte solution in the presence of 1 wt % C12E10 without and with 1 wt % SDS in D2O, 13 vol % D2O, and 62 vol % D2O, respectively. The scattering buildup of the corresponding SANS profiles in D2O (Figure 7a) shows a decrease in the low-Q region of the data. To look at the role of each component for this difference, the components were contrast-matched. LS30−C12E10 conjugates in the electrolyte solution upon the addition of SDS in a surfactant contrastmatched condition (13 vol % D2O) show a monotonically decreasing scattering pattern (of nanoparticles) with suppressed scattering in the low-Q region (Figure 7b). The data match the system consisting of individual nanoparticles only, with no signature for their aggregation. The inset of Figure 7b shows a comparison of nanoparticles in the mixed system with pure nanoparticles, which overlap each other. This clearly demonstrates the disruption of the nanoparticle fractal aggregates in the presence of SDS through the suppression of depletion interactions. On the other hand, Figure 7c shows data for LS30−C12E10 conjugates without and with SDS measured in 62 vol % D2O (nanoparticles contrast-matched condition), where even without SDS a fractal-like buildup of scattering intensity is observed in the low-Q region. It has been found that this build up could originate from some of the micelles trapped in the gaps between the nanoparticles in the aggregates because of the significant size difference between the nanoparticle and the micelle.22 There is a small fraction of micelles not able to exclude themselves when the nanoparticles undergo aggregation. There would have been no aggregation if the micelles were adsorbed on the nanoparticles. These trapped micelles are found to form the mass fractal structure with a fractal dimension of 2.9. In the presence of SDS, the system with C12E10 (and nanoparticles contrast-matched) behaves in an entirely different way. It is clear from the scattering profile that the surfactant micelles are neither adsorbed on the nanoparticle surface (no hump-like build up in mid-Q) nor trapped between nanoparticles (no sharp increase in the scattering in low-Q). The inset of Figure 7c shows that the addition of individual scattering contributions of C12E10 and SDS is very different from the scattering data of their mixed system (1 wt % C12E10 + 1 wt % SDS). The analysis reveals that C12E10−SDS mixed micelles get formed in this system.43 These mixed micelles having a semimajor axis of 27.5 Å and a semiminor axis of 19.6 Å now behave more like their ionic counterpart (anionic SDS). One of the factors on which the depletion interaction depends is the interaction among the depletants (micelles). In the presence of SDS and formation of their mixed micelles with C12E10, the electrostatic repulsion between mixed micelles (depletants) increases and results in a decrease in the depletion interaction and hence the disruption of the nanoparticle fractal aggregates, leading to a transparent single phase (Figure 2). We have seen that the turbid LS30−C12E10 system in an electrolyte solution becomes transparent in the presence of anionic surfactant SDS. However, this is not the case with the turbid phase of the LS30−C12E10 system on addition of cationic surfactant DTAB. The system remains turbid even for high concentrations of DTAB (Figure 2). The corresponding DLS data in Figure 8, measured after diluting the systems by

increase in the electrolyte concentration. As more and more micelles become nonadsorbing with the increase in the electrolyte concentration, the magnitude of the depletion interaction (K1) also increases. The depletion interaction derived from the SANS data using a double Yukawa potential is found to be closely in agreement with the theoretical model described in the literature (Figure S4).42 The evolution of the calculated interaction potential is given in Figure 5b. In regime I, the total potential still maintains stability (transparent solution). On the other hand, in regime II, the increased attractive total potential leads to nanoparticle aggregation (appearance of turbidity). The aggregates are formed when the attractive interaction at the distance of nearest approach of the nanoparticles overcomes the average thermal kinetic energy (1.5 kBT) of the nanoparticles. The variation of the fraction of aggregated nanoparticles with the electrolyte concentration is given in Table 1b. At higher electrolyte concentrations (regime III), there exist only nanoparticle aggregates (turbid solution). The slope of these data in the low-Q region is found to be between 3 and 4, suggesting the surface fractal nature of these aggregates observed in the Q-range of the measurements. The data are fitted by a power law behavior of surface fractal ∼ Q−(6−Ds) (Ds is the fractal dimension) in the low-Q region (using eq S15) along with the structure factor by employing a hard-sphere potential in the Percus−Yevick (PY) approximation for the Bragg peak. The correlation peak provides information on the packing of nanoparticles within their aggregates, and it is also found that the average distance between the nanoparticles within the aggregate is d ∼ 2π/Qp ∼ 180 Å. This value is similar to the particle diameter, suggesting a simple cubic packing of the nanoparticles within the aggregates. Role of Ionic Micelles in the Nanoparticle−Nonionic Micelle System. Figure 6 shows the DLS data of 1 wt % LS30

Figure 6. DLS data of 1 wt % LS30 silica nanoparticles with 1 wt % C12E10 in the electrolyte solution in the presence of varying SDS concentrations. The inset shows the variation of the diffusion coefficient for the corresponding systems.

in the electrolyte solution (0.1 M NaCl) in the presence of 1 wt % C12E10 with varying SDS concentrations. The data are measured after diluting the systems 100-fold. DLS data show the intensity autocorrelation function becoming narrower with the addition of increasing SDS concentration. This indicates that the corresponding diffusion coefficient (inset of Figure 6) is increasing with SDS concentration. This clearly demonstrates F

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Figure 7. SANS data of 1 wt % LS30 in electrolyte solution in the presence of 1 wt % C12E10 without and with 1 wt % SDS in (a) D2O, (b) 13 vol % D2O (surfactant micelles are contrast-matched) [the inset shows a comparison of pure nanoparticles with nanoparticles in the mixed system], and (c) 62 vol % D2O (LS30 nanoparticles are contrast-matched) [the inset shows a comparison of SANS data of the measured mixed micellar system of C12E10 and SDS and the addition of their individual scattering contributions].

of the particle aggregates for LS30−C12E10 and LS30− C12E10−DTAB in aqueous electrolyte solutions is different. For the LS30−C12E10 electrolyte system, it was confirmed that surfactant-induced depletion interaction between nanoparticles is responsible for the aggregation of nanoparticles to form the surface fractals having simple cubic packing of nanoparticles within the aggregates. For the LS30−C12E10− DTAB electrolyte system, the nanoparticles form mass fractal aggregates (fractal dimension, dm ∼ 2.6, using eq S14) whose building block radius is found to be larger than the radius of a silica nanoparticle. In this context, there are two possibilities that may be arising in the nanoparticle−surfactant system in the presence of DTAB: either (i) DTAB and C12E10 form mixed micelles and adsorption of these mixed micelles on nanoparticles mediates the aggregation or (ii) only cationic DTAB micelles adsorb on the oppositely charged nanoparticle surface, intercede, and induce nanoparticle aggregation along with the remaining fraction of it forming C12E10−DTAB mixed micelles. Furthermore, the SANS data with nanoparticles contrast-matched (in 62 vol % D2O) from these systems (Figure 9c) show significant scattering in the low-Q region. Analysis of the SANS data shows that this scattering originates from the DTAB micelles attached to the nanoparticles in the aggregates, and these attached micelles are found to form the mass fractal structure (fractal dimension, dm = 2.6) [possibility (ii)]. This can be understood as the presence of oppositely charged (cationic) DTAB micelles between and around the anionic nanoparticles mediating the attraction between them, which results in the charge-driven bridging aggregation of nanoparticles. Possibility (i) is not feasible as per the zeta potential measurements, where the charge on the C12E10− DTAB mixed micelles (+12.1 mV) is found to be less

Figure 8. DLS data of 1 wt % LS30 silica nanoparticles with 1 wt % C12E10 in the electrolyte solution in the presence of varying SDS concentrations.

100-fold, show broad autocorrelation functions, confirming the presence of larger aggregated structures throughout the varying DTAB concentrations. Contrast-matching SANS measurements were carried out to examine the role of DTAB in these systems. A comparison of the SANS profiles of the LS30−C12E10 system without and with DTAB in D2O (Figure 9a) shows different scattering characteristics at the low-Q and mid-Q regions even though both systems form a turbid phase. This suggests that the interaction responsible for the aggregation in the system in the presence of DTAB is different from the depletion attraction, which is the driving force for the aggregation without DTAB. The surfactant contrast-matched SANS data (in 13 vol % D2O) measuring the scattering only from the nanoparticles (Figure 9b) show that the fractal nature G

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Figure 9. SANS data of 1 wt % LS30 silica nanoparticles in the electrolyte solution in the presence of 1 wt % C12E10 without and with 1 wt % DTAB in (a) D2O, (b) 13 vol % D2O (surfactant micelles are contrast-matched), and (c) 62 vol % D2O (LS30 nanoparticles are contrast-matched).

and the system remains in an aggregated state. However, the driving interaction inducing the aggregation is different in this case; it is not depletion-mediated aggregation but the oppositely charged micelle DTAB-driven bridging aggregation of nanoparticles along with the formation of C12E10−DTAB mixed micelles. Contrast-variation SANS measurements were used to obtain quantitative information on these intercomponent interactions and their resultant structures. The understanding of interaction−phase behavior relationships provides better tunability in nanoparticle−surfactant micelle systems as required for their desired applications.

compared to that of DTAB micelles alone (+20.5 mV), and this could be due to the charged head groups of DTAB micelles hidden in the long hydrophilic chains of the mixed micelles. All of these results thus show that nanoparticle−surfactant interactions and the structures evolving due to these interactions can be tuned by the appropriate choice of the electrolyte and/or surfactant(s).

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CONCLUSIONS The evolution of interactions, phase behavior, and resultant structures in the mixed system of anionic silica nanoparticles and nonionic surfactant decaethylene glycol monododecylether (C12E10) in the presence of electrolyte and ionic surfactants has been studied. Anionic LS30 nanoparticles with nonionic surfactant C12E10 form a transparent single-phase stabilized by micelle adsorption on the nanoparticles. This system transforms to a turbid two-phase system with the introduction of electrolyte (NaCl). With increasing electrolyte concentration, a decrease in nanoparticle repulsion and nonadsorption of the micelles lead to the evolution of attractive depletion interactions (modeled by a double Yukawa potential), resulting in the aggregation of nanoparticles having surface fractal morphology. Interestingly, this system again transforms to a transparent single-phase when anionic surfactant (SDS) is added. Electrostatic repulsion between similarly charged (anionic) C12E10−SDS mixed micelles formed in the system, unlike the case of C12E10 micelles alone, is found to suppress the depletion interaction to transform the turbid phase system to transparent phase again. On the other hand, the addition of cationic surfactant DTAB shows no effect on the turbid phase,

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ASSOCIATED CONTENT

* Supporting Information S

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.langmuir.7b03429. Details of SANS data analysis and DLS data analysis; DLS data of LS30 silica nanoparticles without and with C12E10 in the absence and presence of NaCl; SANS data of LS30 silica nanoparticles without and with NaCl, C12E10, and C12E10 with NaCl; variation in hydrodynamic size for LS30 with C12E10 in the presence of varying NaCl concentrations; calculated neutron scattering length densities and contrast of different components of silica nanoparticles and surfactants in aqueous solution; description of the Asakura−Oosawa−Vrij (AOV) depletion potential; comparison of depletion interaction calculated from the AOV model and double Yukawa potential from SANS data (PDF) H

DOI: 10.1021/acs.langmuir.7b03429 Langmuir XXXX, XXX, XXX−XXX

Article

Langmuir

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Phone: +91 22 25594642. Fax: +91 22 25505151. ORCID

Debes Ray: 0000-0001-5564-2973 Vinod Kumar Aswal: 0000-0002-2020-9026 Notes

The authors declare no competing financial interest.

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DOI: 10.1021/acs.langmuir.7b03429 Langmuir XXXX, XXX, XXX−XXX