Surfactant controlled switching of water-in-oil wetting behaviour of porous silica films grown at oil-water interfaces

Selective permeation of oil and water across a porous medium, as in oil recovery operations, depends on the preferential wetting properties of the porous medium. We show a profound influence of surfactants in wetting of porous media and thus demonstrate a new route for the control of water-in-oil wetting of porous substrates by changing the concentration of surfactants in an aqueous sub-phase below the substrate. This strategy is employed to engineer partial reversible wetting transitions on a porous silica film. The film itself is grown and stabilized on a flat, macroscopic interface between an oil phase and an aqueous sub-phase. On increasing the surfactant (CTAB) concentration in the sub-phase, contact angle of a water drop (placed on the oil side of the film) changes from 140° to 16° in 25 min by diffusion of the surfactant across the porous film. On further replacement of the sub-phase with pure water, diffusion of the surfactant from the water drop back to the sub-phase was slower, increasing the contact angle in the process from 16° to 90° in 2 h. Wettability control by a cationic surfactant (CTAB) was found to be much faster (6 deg/min) than that offered by an anionic surfactant, SDS (0·05 deg/min). Switching of the surface wettability due to the surfactant diffusion may have implications in oil-water separation, chemical bed reactors and microfluidic devices

Nanoparticle assembly: a perspective and some unanswered questions

In early 2016, the Royal Society of Chemistry arranged a meeting on the topic 'Nanoparticle Assemblies: from Fundamentals to Applications' which was hosted at IIT-Bombay, Mumbai. The meeting brought several leading nanoscience and nanotechnology researchers to India and is only the second Faraday Discussions meeting to have been held in the country. The papers presented at the meeting and the resulting active discussions have been summarized in a Faraday Discussion issue(1). The broad range of topics discussed at the meeting led to an understanding on where we stand in the field of nanoparticle assembly, and also enunciated some of the outstanding fundamental and practical issues that remain to be resolved before these ideas can be applied to practical situations. Driven by these ideas, here we focus on four topics/questions: (i) Can we achieve function-driven design of nanoparticle assemblies? (ii) What is the minimal information needed to build a desired assembly? (iii) How complex a structure can one build? How can one make it responsive? What are the relative roles of equilibrium versus dynamics in the assembly process, and are we at a point where we can now pursue active assembly as a viable mode for creating complex assemblies? (iv) What are the applications that are being targeted and what are the barriers to implementation? In this perspective, we do not present an exhaustive survey of the vast literature in this area, but indicate overarching themes/questions that require immediate attention, largely based on the discussions at the Mumbai meeting.open

Modelling Of Precipitation In Reverse Micelles

Nanoparticles have important applications in ceramics, metal catalysts, semiconductors etc. They are normally required to be of small size (~ nm) and monodisperse. The aim of the present work is to model the formation of nanoparticles, obtained by precipitation in reverse micellar microreactors. These are dispersions of tiny water drops in a surfactant laden oil medium. Two systems were investigated: (i) Reverse micelles, having nanometer sized spherical water droplets in the micellar core and (ii) Water-in-oil emulsions, having micron-sized aqueous drops. Two modes of precipitation, namely, gas-liquid (g-1) and liquid-liquid (1-1) were studied. In each case, the models could predict the number, average size and size distribution of the particles reported in literature. Two groups have obtained widely divergent number and size of CaCO3 nanoparticles, formed by g-1 precipitation in reverse micelles. These particles are used as a fine suspension in lube-oil additives, where they serve to neutralize acid produced during combustion in engines. Kandori et al. (J. Colloid Interface Sci, 122,1988, 78) obtained particles of about 100 nm size, by passing CO2 through a reverse micellar solution, containing dissolved Ca(OH)2 in the micellar core. Roman et al. (J. Colloid Interface Sci., 144,1991, 324), instead of using lime solution; added micron-sized solid lime particles in the oil and generated the reverse micelles by in situ reaction. This is a commercial process known as overbasing. It led to a higher amount of lime in the micelles as well as unreacted lime particles in oil, at the beginning of the experiment Upon passing CO2, they got particles of only 6 nm in size, compared to 100 nm reported by Kandori et al.. Furthermore, while Kandori et al. found that one particle formed from 108 micelles, Roman et al. got one particle out of only ten micelles. We have modelled the two processes in a common framework to explain the reported disparity in particle characteristics. A time scale analysis of CO2 mass transfer, reaction, collision-fusion of micelles, nucleation, and growth of particles was carried out It showed that, in the experiments of Kandori et al., the rate limiting steps are nucleation and fusion. The analysis also indicates that the contents of a particular micelle are well mixed and reaction of lime and incoming CO2 can be treated as instantaneous. In the process of Kandori et al., the amount of lime taken initially being very small, the average number of product molecules in a micelle is well below one. Rapid Brownian coalescence and exchange of micellar contents leads to Poisson distribution of CaCO3(l) molecules formed by reaction. The low occupancy therefore suggests that most of the micelles are empty. Nucleation in a particular micelle is much slow and occurs when it has a critical number of molecules. Thus only very few micelles can nucleate. Comparison of nucleation and growth time scales - both intrinsic growth in a micelle and growth during fusion of nucleated and non-nucleated micelles - show that growth is much faster than both nucleation and collision. Hence a micelle can have only one nucleus, with subsequent growth during collisions. A population balance equation (PBE) is written involving the above steps. Solution of the moments of the distribution yields the number of CaCO3 particles, its size, coefficient of variance (COV) etc. The model not only predicts the ratio of number of micelles to particles, obtained experimentally as 108, but also captures the maxima in this quantity with increasing micellar size. The increase in average particle size with micellar size is also predicted well. The process of of Roman et ai, in addition, involves the time scale of solubilization of solid lime into micelles. Its comparison with other time scales demarcates their experiments into two distinct phases. Phase I consists of reaction of lime initially present in micelles. Time scale analysis also suggests that, as the lime content in the micelles is large, a high degree of supersaturation is rapidly generated. This results in a burst of nuclei. The other conclusions, like, well-mixed micelle, Poisson distribution of CaCO3(l) molecules, instantaneous growth and mono-nucleated micelles are found to hold good. Once the pre-existing lime is finished, relative time scales indicate that, further precipitation is controlled entirely by fresh solubilization of lime. This marks the beginning of phase II. However, solubilization being the slowest step, CaCO3(l) in micelles never builds up for any further nucleation. Phase II thus consists of pure growth of the particles formed in phase I. On developing more general PBEs and with solution of resulting moment equations - written separately for the two phases - the experimental data on number of particles and temporal evolution to the final particle size of 6 nm could be predicted very well. The model also captures the qualitative trend in COV of particle radius with time. Thus within the same framework we could successfully predict both the results, differing by seven orders of magnitude. The above analysis indicates that relative rates of nucleation, fusion-growth and mass transfer of gas controls the carbonation process. We further simplify the process and obtain an analytical solution in the limit of instantaneous mass transfer. The solution gives close first estimates for both the experiments and also indicates the smallest panicle size that could be obtained for a given experimental condition. In contrast to g-1 mode, precipitation in 1-1 mode - using two reverse micellar solutions having two reactants- occurs only on coalescence of two micelles. To obviate the solution of multivariate PBEs, we have developed a general Monte Carlo (MC) simulation scheme for nanoparticle formation, using the interval of quiescence technique (IQ). Starting with a fixed number of micelles, we conduct each coalescence-redispersion and nucleation events in this population, in the ratio of their relative frequencies. Our simulation code is much more general and realistic than the scheme of Li and Park (Langmuir, 15,1999, 952). Poisson distribution with realistic micellar occupancies of reactants, binomial redispersion of solutes after fission, a nucleation rate with critical number of molecules and Brownian collision-fusion rates were used. These considerations are based on our earlier findings in g-1 precipitation and those known in the literature too. The simulation of Li and Park then becomes a special case of our code. Our simulation code was then used to predict experimental data on two systems. The results of Lianos and Thomas (Chem. Phys. Lett. 125, 1986, 299 and /. Colloid Interface 5c/., 117, 1987, 505), on number of molecules per CdS particle, as a function of micelle size and reactant concentrations have been predicted very well. For the Fe(OH)3 nanoparticles, our simulation provides a better prediction of the experimental particle size range, than that of Li and Park. Finally, 1-1 precipitation on mixing two emulsions, having respectively the two reactants, has been simulated. Here, large reactant amount leads to multiple nucleation in a single drop and renders growth rate to be finite. This requires solving a PBE for particle population in each drop. Moreover, emulsions have a drop size distribution due to independent coalescence and breakage. The IQ technique was used for handling these events. Thus a composite model of PBE and MC for a drop population was developed. Simulation of particle size distribution in MgCO3 precipitation shows that nearly monodisperse nanoparticles can be produced in emulsions. Furthermore, average particle size can be controlled by changing reactant concentration in a drop. The findings of the thesis have provided new issues to be addressed in modelling nanoparticle formation. It points out the importance of finding models for coalescence efficiency and critical nuclear size in micelles. Extension of our model and simulation to precipitation in other organized surfactant assemblies can be done by starting from appropriate time scale analysis

Simulation of precipitation reactions in reverse micelles

Precipitation involving mixing of two sets of reverse micellar solutions-containing a reactant and precipitant respectively-has been analyzed. Particle formation in such systems has been simulated by a Monte Carlo (MC) scheme (Li, Y.; Park, C. W. Langmuir 1999, 15, 952), which however is very restrictive in its approach. We have simulated particle formation by developing a general Monte Carlo scheme, using the interval of quiescence technique (IQ). It uses Poisson distribution with realistic, low micellar occupancies of reactants, Brownian collision of micelles with coalescence efficiency, fission of dimers with binomial redispersion of solutes, finite nucleation rate of particles with critical number of molecules, and instantaneous particle growth. With the incorporation of these features, the previous work becomes a special case of our simulation. The present scheme was then used to predict experimental data on two systems. The first is the experimental results of Lianos and Thomas (Chem. Phys. Lett. 1986, 125, 299, J. Colloid Interface Sci. 1987, 117, 505) on formation of CdS nanoparticles. They reported the number of molecules in a particle as a function of micellar size and reactant concentrations, which have been predicted very well. The second is on the formation of Fe(OH)(3) nanoparticles, reported by Li and Park. Our simulation in this case provides a better prediction of the experimental particle size range than the prediction of the authors. The present simulation scheme is general and can be applied to explain nanoparticle formation in other systems

Modeling of precipitation in reverse micellar systems

A model of the precipitation process in reverse micelles has been developed to calculate the size of fine particles obtained therein. While the method shares several features of particle nucleation and growth common to precipitation in large systems, complexities arise in describing the processes of nucleation, due to the extremely small size of a micelle and of particle growth caused by fusion among the micelles. Occupancy of micelles by solubilized molecules is governed by Poisson statistics, implying most of them are empty and cannot nucleate of its own. The model therefore specifies the minimum number of solubilized molecules required to form a nucleus which is used to calculate the homogeneous nucleation rate. Simultaneously, interaction between micelles is assumed to occur by Brownian collision and instantaneous fusion. Analysis of time scales of various events shows growth of particles to be very fast compared to other phenomena occurring. This implies that nonempty micelles either are supersaturated or contain a single precipitated particle and allows application of deterministic population balance equations to describe the evolution of the system with time. The model successfully predicts the experimental measurements of Kandori et al.3 on the size of precipitated CaCO3 particles, obtained by carbonation of reverse micelles containing aqueous Ca(OH)2 solution

Predicting Complete Size Distribution of Nanoparticles Based on Interparticle Potential: Experiments and Simulation

Solution-based synthesis of nanoparticles does not yield monodisperse particles, but rather a well-defined particle size distribution (PSD). There is currently no simple means to anticipate or model these size distributions, which critically affect the properties of the resulting nanomaterials. We simulate the temporal evolution of the PSD in the framework of a nucleation and growth model, with the critical postulate that the coagulation efficiency between two nanoparticles is quantitatively determined by the known, interparticle potential energy. Our simulation based on this ansatz, not only <i>a priori</i> predicts experimentally obtained complete PSDs of uncoated or coated (with poly­(acrylic acid)­or dextran) iron oxide nanoparticles but also accurately captures the influence of surface coverage of a coating agent on the resulting PSD

Modelling of CaCO<SUB>3</SUB> nanoparticle formation during overbasing of lubricating oil additives

A framework of population balance equations has been developed to model formation of CaCO3 nanoparticles during overbasing of lubricating oil. The process involves carbonation of a reverse micellar solution containing lime, present both in the micelles and as a suspension of lime particles in the oil. The mechanism leading to CaCO3 nanoparticles in this setup consists of a number of elementary events such as CO2 transport from gas to reverse micelles through the organic phase, reaction in the reverse micellar core, nucleation of CaCO3, particle growth, and Brownian collisions leading to material exchange, both among reverse micellar drops and between drops and lime particles. A time scale analysis of these steps permits simplification and enables us to divide the whole process into two stages. The first consists of reaction of existing lime in micelles and a burst of nucleation of very short duration, wherein some reverse micelles beget a single nucleus each. The number of such nucleated reverse micelles depends on the relative rates of mass transfer, nucleation, and growth by intermicellar Brownian collisions. This is followed by a slow growth phase of these initial particles through Brownian collisions between nucleated reverse micelles and lime particles. The model predicts the data of Roman et al. (J. Colloid Interface Sci. 1991, 144, 324.), where on average only 10 initial reverse micelles contribute to form a CaCO3 nanoparticle. A simplified version of the model, obtained in the limit of instantaneous gas transfer, is also able to approximately predict the results of Kandori et al. (J. Colloid Interface Sci. 1988, 122, 78.) where, in contrast, a huge number of 108 reverse micelles contribute to form one particle. The model is quite general and can be used for other gas-liquid micellar precipitation systems wherein similar relative orders of time scales are involved

Janus silica film with hydrophobic and hydrophilic surfaces grown at an oil-water interface

We report a new methyltrimethoxysilane (MTMS) based route to growing a Janus silica film at the oil-water interface, which upon drying shows anisotropic wetting by water on its two surfaces. The contact angle of water on the surface grown in contact with the oil-side is found to be ~150°, but it is much smaller, ~65°, on the side which grew in contact with the aqueous phase. This large difference in the contact angle is found to be primarily because of two reasons: (i) orientation of hydrophobic methyl groups towards the oil-side of the film as confirmed by micro-Raman spectroscopy, and (ii) microstructural differences in the oil and water-side surfaces of the film. The inherently hydrophobic silicacluster network on the oil-side surface also exhibits larger pores that provide an air cushion for the water droplet and engenders a large contact angle. Effects of oil-water interfacial tension on the film growth and on its wetting and microstructural properties are also investigated by addition of cationic and anionic surfactants in the aqueous subphase. Static and dynamic wetting properties of the oil-side surface indicate that these do not change significantly due to variations in either the microstructure or chemical nature of the surface alone, but is a combined effect of both. Interestingly, the Janus films showing asymmetric surface properties can also be grown directly and thus integrated with a variety of porous surfaces like cotton, paper, hydrogel and ceramic substrates by having these surfaces straddle an oil-water interface