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Complex layering observed in high internal phase emulsions at a silicon surface by neutron reflectometry
Journal of Colloid and Interface Science 364 (2011) 539–545
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Journal of Colloid and Interface Science www.elsevier.com/locate/jcis
Complex layering observed in high internal phase emulsions at a silicon surface by neutron reflectometry Philip A. Reynolds ⇑, Mark J. Henderson, Johann Zank 1, John W. White Research School of Chemistry, Australian National University, Canberra, ACT 0200, Australia
a r t i c l e
i n f o
Article history: Received 9 June 2011 Accepted 21 August 2011 Available online 28 August 2011 Keywords: Neutron reflectivity Emulsions Lamellae Surface layers
a b s t r a c t The neutron reflectivity profiles from the interface between silicon and aqueous phase-in-oil high internal phase emulsions of steadily increasing surfactant hydrophilicity, are reported for two isotopic contrasts for each surfactant. Layered models are required to fit the structured reflectivity profiles that demonstrate that the oxidised top layer of the silicon is always covered by a surfactant monolayer. Interposed between the surfactant monolayer and the bulk emulsion is a layer of oil – a geometric effect caused by reorganisation of the aqueous droplets. As the surfactant hydrophilicity increases, alternating aqueous and oil + surfactant layers are inserted between this topmost oil layer and the oxide attached surfactant monolayer. The resulting structures have compositions and layer spacings suggestive of sections from lamellar phases. This increase in layer ordering with increasing surfactant hydrophilicity is expected. The bulk emulsions are observed to exhibit lamellar or sponge phases increasingly as surfactant hydrophilicity increases. Ó 2011 Elsevier Inc. All rights reserved.
1. Introduction The purpose of this paper is to understand the structure of an emulsion–solid surface interface as a function of the hydrophilic– hydrophobic balance of the emulsifying surfactant. In practical systems the emulsion stability depends, at least partly, on the nature of this interface since emulsions are often mixed with powdered solids to form a slurry. Lamellar ordering of other isotropic fluids at the air–fluid and solid–fluid interfaces is not uncommon, and is more fully discussed elsewhere [1–4]. The extent of ordering may range from a few layers up to micron scale. Previously we found a simple surfactant monolayer interface between a high internal phase emulsion and a silicon surface (with some secondary dispersed droplet reorganisation in the emulsion) when a hydrophobic surfactant is used to stabilise the emulsion [5]. Also a micron scale lamellar phase is present at the aqueous–oil interface for a pure high internal phase emulsion stabilised by a much more hydrophilic surfactant [6]. In related work we have previously examined aqueous-in-oil emulsions by Small Angle Neutron Scattering (SANS) [7–14], slurries of these emulsions containing powdered solids by SANS [15], and the silicon–emulsion interface by neutron reflectometry [5]. Here, by using a series of surfactants of increasing hydrophilicity, we suggest that the transition from ⇑ Corresponding author. Fax: +61 02 6125 4903. E-mail address: [email protected] (P.A. Reynolds). Present address: Orica Mining Services, George Booth Drive, Kurri Kurri, NSW 2327, Australia. 1
0021-9797/$ - see front matter Ó 2011 Elsevier Inc. All rights reserved. doi:10.1016/j.jcis.2011.08.053
monolayer to multilayer structures at the silicon–emulsion interface is driven by increasing surfactant hydrophilicity. All of the emulsions studied were high internal phase emulsions made from an aqueous saturated ammonium nitrate solution dispersed as highly polydisperse spheres with typical radius of a few micrometres, typically occupying a volume fraction of 90% with the remaining 10% volume occupied by a continuous oil phase. For the PIBSA surfactant where oil phase and surfactant tail are well matched in solvency the droplets are stabilised by a monolayer of adsorbed amphiphile at the aqueous oil interface using only a small fraction of the added surfactant. The remainder occurs as reverse micelles of typical radius 30–40 Å, within the oil phase; some dissolved molecules in the oil phase; and sometimes a third surfactant-rich phase aggregated at the aqueous–oil interface in micron scale blocks which are fractally linked [6–10]. At the other extreme of surfactant matching, using Pluronic L92Ò, the vast majority of surfactant is in the form of aggregate, located at the oil–droplet interface, with very few reverse micelles [6]. In the solid surface studies [5,15] the surfactant used to form the emulsion (polyisobutylene N-(2-hydroxyethyl)succinamide or PIBSA) produced simple interfaces. These consisted of a more or less complete monolayer of surfactant separating the dispersed aqueous droplets or solid particles from the continuous oil phase. In addition the solid–emulsion interface often exhibited an excess of oil above this monolayer, caused by the geometric effect in which aqueous droplets in the emulsion must be rearranged to best pack onto a planar solid surface.
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Each emulsion studied here has been examined in two isotopic variants, differently deuterated, such that in one case only the surfactant is highlighted, and in the other the surfactant together with oil are highlighted against the emulsion’s aqueous component. We show a progressively more lamellar character of the surface structure in the order (1) the previously examined PIBSA surfactant emulsions through, successively: (2) sorbitan monooleate–trioleate mixture (3) concentrated sorbitan monooleate (4) dilute sorbitan monooleate and (5) a pyridinium vinylbenzyl (butyleneoxide)31(ethyleneoxide)7 sulfate amphiphile.
2. Experimental 2.1. Experiments Silicon (1 1 1) polished face single crystal blocks were cleaned by an exposure of 1 min in a plasma chamber. The blocks were stored for future neutron reflectometry in sealed but not evacuated chambers with the hydrophilic silicon surface in contact only with air. The small air volume minimises surface contamination of the blocks [5]. Neutron reflectometry was performed 1 week later using the instrument SURF at the ISIS (UK) spallation neutron facility [16]. Measurements were recorded in three configurations (incident neutron angles 0.25°, 0.5° and 1.2°), which were combined to give the momentum transfer (Q) range 0.008–0.47 Å 1. The three sets of data splice together satisfactorily. This is a standard data acquisition setup. The data also were reduced in the standard way for SURF. The Q range typically spans the region from the critical edge in the reflectivity profile out to the incoherent scattering background caused by proton content of the sample. All runs were performed at the same SURF default resolutions for the same runtime. The hydrophilic surfaces of the silicon blocks gave complete wetting when Milli-Q™ water was used. The surface structure of a silicon block was defined by neutron reflectometry with neutrons passing through air and being reflected from the silicon block’s surface facing upward. This is denoted as the air–silicon interface. All subsequent experiments used the silicon–emulsion interface. A cell was used [17,18] in which neutrons pass through the silicon block and are reflected from fluid below the block and in contact with it. Transmission corrections for neutron absorption and scattering in the silicon block were performed. Cells were filled with various emulsions and the reflectivities measured. The cell and silicon surface were cleaned between samples by alternate washing with acetone and Milli-Q™ water. We have previously found that this procedure broke the emulsion and removed the components from a silicon block [5]. To ensure that this cleaning procedure was adequate, we measured a final set of reflectivities from cleaned cells filled with D2O. These were compared to the initial air–silicon measurements. Two checks were made to ensure that the cells were completely filled with emulsion, with no significant air bubbles remaining. First, the volume of emulsion injected by syringe was monitored at each filling. In all cases when excess emulsion emerged from the overflow tube, the volume injected corresponded to the fillable volume (measured separately), within an error of about 5%. Second, when the cells were opened, all samples appeared to have wet the silicon surface completely. The cells were opened with the minimum of sliding and twisting of the silicon against the rest of the cell. All the emulsions reported in this paper had a 90% aqueous internal volume fraction of almost saturated ammonium nitrate in D2O (53.4 wt.%). The amphiphiles used to stabilise the emulsions were sorbitan monooleate (Aldrich) at two concentrations
(denoted SMOCONC and SMODIL); a 50/50, by volume, mixture of sorbitan monooleate and sorbitan trioleate (Aldrich)(denoted SMOSTO); and the polymer diblock surfactant of approximate formula pyridinium vinylbenzyl (butyleneoxide)31(ethyleneoxide)7 sulfate (Dow P-31:7)(denoted P31:7). These can be compared to our previous experiments using a polydisperse mixture of polyisobutylene N-(2-hydoxyethyl) succinamide of median molecular weight about 1100, which we denote PIBSA. The oil used was nhexadecane (Aldrich) in all cases, except for the P31:7 amphiphile emulsions. The P31:7 surfactant emulsions used a 50/50 hexadecane/toluene mix because the amphiphile was not sufficiently soluble in hexadecane alone to form an emulsion. Each emulsion was prepared in two isotopically substituted variants, at constant volume fraction. The first contained hydrogenous oil with no deuterated oil. Thus the neutron scattering shows strong contrast only between the oil phase and the partially deuterated aqueous droplets. We denote this contrast unmatched (UM). The second used oil in which hydrogenous and deuterated oils were mixed so that the calculated oil phase scattering length density (SLD), assuming all the surfactant is dispersed in the oil phase, is the same as the partially deuterated aqueous ammonium nitrate phase. Here the scattering contrast in neutron reflectometry is between surfactant structures and the rest of the emulsion, oil plus aqueous components. For example reverse micelles in the oil phase and surfactant adsorbed at the oil/aqueous droplet interface will both be highlighted. We denote this contrast matched (CM). Reflectograms, normalised to unity by use of the fitted scale factor, and the curves fitted to these are shown in Figs. 1 and 2. The emulsions were prepared in 10 mL batches by adding the aqueous components to the amphiphile predissolved in the oil phase, while shearing the mixture with a snug fitting propeller, driven by an electric motor at a nominal 1900 rpm, for 5 min, in a closed Teflon container at 80 °C. The emulsion compositions are presented in Table 1, together with self-explanatory nomenclature for later reference to the emulsions.
Fig. 1. Normalised reflectivity from contrast matched emulsions at silicon interface, profiles offset for clarity. PIBSA (h), SMOSTO (j) 10, SMOCONC (+) 102, SMODIL (d) 103, P31:7 (s) 104. The continuous lines are the results from the model fitting.
P.A. Reynolds et al. / Journal of Colloid and Interface Science 364 (2011) 539–545
Fig. 2. Normalised reflectivity from contrast unmatched emulsions at silicon interface, profiles offset for clarity. PIBSA (h), SMOSTO (j) 10, SMOCONC (+) 102, SMODIL (d) 103, P31:7 (s) 104. The continuous lines are the results from the model fitting.
Table 1 Emulsion compositions (g) and nomenclature. Name
Surfactant
C16H34
PIBSA-UM PIBSA-CM SMOSTO-UM SMOSTO-CM SMOCONC-UM SMOCONC-CM SMODIL-UM SMODIL-CM P31:7-UM P31:7-CM
.21 .21 .18 .18 .18 .18 .06 .06 .075 .073
.85 .11 .63 .11 .63 .11 .75 .18 .36 .08
C16D34
C7H8
C7D8
Sat AN-D2O
.32
11.84 11.83 11.83 11.83 11.83 11.83 11.83 11.83 11.84 11.83
.87 .62 .62 .63 .32
.40 .11
2.2. Model choice and analysis strategy The reflectivity data were analysed by the optical transfer method using the program CXMULF [19,20]. The complete interface is modelled as a series of layers between the bulk silicon and bulk emulsion. Each layer has a thickness and SLD associated with it, and a roughness between it and the layer below (or above for air–silicon geometry). After the experimental resolution function was convolved with this model, appropriately constrained, it was simultaneously fitted to reflectivity data from both UM and CM emulsion samples. These models still have large numbers of variables, even after physical constraints are applied. In principle, it is possible to eliminate well-fitting models with unphysical results or interpretations – such as highly negative SLDs or apparent oil layers next to aqueous or other hydrophilic surfaces, with no mediating amphiphile layer. Starting from simple physical models, however, allows descent into physically realistic minima in goodness-of-fit, v2, with interpretable parameters. Attempts to achieve similarly low v2 by refining from unphysical starting models – such as a stack of identical slabs – sometimes dropped into one of the ‘physical’ models, but equally often produced unphysical results with
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slightly higher v2. Thus, our refined results do not give unique models and we must, as is often the case with reflectivity measurements, apply further physical criteria to choose the correct model. CXMULF can be forced to descend into a local minimum by use of Levenberg–Marquardt minimisation. When simulated annealing methods are used, minima more likely to be global can be accessed and explored. We have therefore adopted the strategy of testing a set of three ‘standard’ models. We start with completely unconstrained modelling and simulated annealing followed by Levenberg–Marquardt minimisation to obtain a minimum in v2. The resulting parameters mostly have large errors due to large correlations between parameters. But we have noticed, by fixing various parameters and re-refining the data, that the variation of SLD with distance through the interface is much more stable than the parameter values themselves. In the discussion we will therefore discuss these profiles rather than the actual values of the parameters. In the most complex case (P31:7) we require 29 parameters to describe the two reflectivity profiles without any constraints. The profiles contain significant structure, which allowed modelling to be guided by considering the inflection points and other information content in both profiles. We now turn to the model parameters and constraints in more detail. For all refinements the value of a flat background was refined for each of the UM and CM patterns. Most sources of background are relatively unstructured (e.g. incoherent scattering) but SANS from lamellar structures in the bulk emulsion would vitiate our model. SANS experiments on emulsions, which contain all these surfactants at various concentrations, have been performed and show no lamellar phase in the bulk [9 and unpublished data]. Only the normal aqueous droplet plus micellar scattering, which is not highly structured has been observed. Complications in the specular reflected intensity can arise from lateral height–height correlations and ‘‘off-specular’’ scattering [5], This layer roughness requires refinement of a scale factor for both UM and CM patterns and will be discussed in Section 3.2 below. Parameter numbers can be reduced by constraints. A general constraint we have used is to fix roughnesses involving the oxide surface at 3 Å, and all other fluid–fluid interfaces at 10 Å. An exception to this is the topmost oil–emulsion interface, which we have found necessary to refine, as it reaches large roughness values. These roughness values may reach up to half the (large) thickness of the oil layer – often 200 Å and 400 Å respectively. This is close to the limit of validity of the slab/roughness model. The parameters pertaining to the silicon oxide layer (SLD and thickness) were fixed at values obtained from the refinement of the emulsion free silicon–air reflectivity profile in this and all subsequent refinements. The oxide SLD was fixed at the value for cristobalite. Because of limited resolution at this low thickness, SLD and thickness are highly correlated. We choose the SLD of cristobalite although it is quite possible that the oxide surface could be lower due to porosity. A factor militating against this is the stability of the oxide layer in air. Lastly, in most cases we have restricted the data fitted to that with Q values greater than about 0.01 Å 1. The reason for this is that, except for two profiles, all our models are very poor fits in the lowest Q regions. We believe this is due to irregularities (height–height correlations) in the adsorbed in-plane structures at the silicon face, which we will discuss in Section 3.2 below. The three models for emulsion structuring at the silicon interface involve layering of surfactant, water, oil, or surfactant–oil mixtures. In each case, the bulk silicon is capped by a thin oxide layer. In the ‘1-LAYER’ model the oxide has an amphiphile monolayer adsorbed on it, while above this is an oil layer tailing off into bulk emulsion SLD. In the ‘2-LAYER’ model we have two surfactant–oil layers separated by an aqueous layer, before the oil layer is encountered. In the ‘3-LAYER’ model we have three
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surfactant–oil layers above the oxide, each separated by an aqueous layer, before the final oil layer is reached. In the infinite layer limit this would be a lamellar phase. Listing the model layers explicitly, we have for the UM samples
In Table 2 we have listed v2 and parameter number (N) for each model type for each emulsion set, together with similar data in Table 3 for the best constrained models. 3. Results and discussion
‘1-LAYER’ bulk silicon silicon oxide surfactant rich monolayer oil rich thick layer due to droplet reorganisation bulk emulsion ‘2-LAYER’ bulk silicon silicon oxide surfactant rich monolayer aqueous salt layer surfactant rich layer, possibly containing some oil oil rich thick layer due to droplet reorganisation bulk emulsion ‘3-LAYER’ bulk silicon silicon oxide surfactant rich monolayer aqueous salt layer surfactant rich layer, possibly trilayer (surfactant/oil/ surfactant) aqueous salt layer surfactant rich layer, possibly containing some oil oil rich thick layer due to droplet reorganisation bulk emulsion
SLD fixed SLD and thickness fixed SLD and thickness refined thickness, SLD and topmost roughness refined SLD refined SLD SLD SLD SLD SLD
fixed and thickness and thickness and thickness and thickness
fixed refined refined refined
thickness, SLD and topmost roughness refined SLD refined SLD fixed SLD and thickness fixed SLD and thickness refined SLD and thickness refined average SLD and thickness refined SLD and thickness refined SLD and thickness refined thickness, SLD and topmost roughness refined SLD refined
For the CM data the topmost oil layer is removed because oil and aqueous components of the emulsion have the same SLD, removing any contrast. We initially refined each pair of UM and CM profiles together in the 1-LAYER model, with the roughness and oxide layer constraints already outlined. The 2-LAYER model was refined using the results from the 1-LAYER model for the similarly placed layers. The extra layers inserted between 1-LAYER and 2-LAYER models were given starting values for the SLDs appropriate to their content, and thickness values from their nature. For example monolayer thicknesses for surfactant layers. The initial refinement was only of the values for these ‘new’ parameters. Subsequently the values for all layers were allowed to refine freely. Similarly, the 3-LAYER models were refined using values suggested by the results of the 2-LAYER refinement. This hierarchical method of model development ensured stable refinements, insensitive to precise starting values, and gave physically interpretable and sensible results. We subsequently applied more constraints to the models. Successively 1) we constrained equivalent layer thicknesses to be equal in both UM and CM cases; 2) we then constrained all aqueous layer SLD’s to be the same for the 3-LAYER model. Other obvious constraints were tried, but degraded the fit significantly. In particular the constraint making surfactant layer SLDs the same between UM and CM, and/or between different surfactant layers in CM or UM individually showed that differences in surfactant and oil content in the layers are significant.
3.1. Reliability of the modelling Table 2 shows that we can distinguish between the 1, 2 and 3 layer models and readily choose the best model on the basis of its v2. Comparison of the v2 values of Table 3 and the preferred models in Table 2 show that our constraints are not only physically reasonable but do not significantly degrade the fits. They are clearly worthwhile –a reduction of 8 parameters from 29 for the P31:7 surfactant provides reassurance in the interpretation of the fitted data. Further checks are provided by the refined values of the bulk emulsion SLDs given in Table 3. The expected values calculated from the emulsion compositions are about 4.5 1014 m 2 for the contrast matched (CM) emulsions and about 3.9 1014 m 2 for the unmatched (UM) emulsions, with only small variations due to change of surfactant. We obtain fitted values close to these but significantly different. These bulk SLDs are defined by the critical edge in the reflectivity. This occurs at Q values corresponding to distances of several 100 Å. This is perhaps an indication that our model is neglecting, or not perfectly fitting, some lateral surface structures on this scale. This is also signalled by the reduction in scale factors. These are far less than one, indicating much off-specular or SANS scattering, and will be explored in Section 3.2 below. In Fig. 3a–e the fitted values for the SLDs through the interface are plotted against distance above or below the silicon–silicon dioxide interface, defined as 0 Å in the distance scale. A last physical constraint is the requirement that SLDs remain between about 0.5 1014 m 2 and about 4.6 1014 m 2, which are the two extreme values for the added emulsion components. Examination of Fig. 3a–e shows that this is broadly so. The deviations reflect some model shortcoming. One shortcoming is probably inaccuracies or inadequacies in the roughnesses of the interfaces. Another
Table 2 Fits (v2), and parameter number (N) for various unconstrained models. Name
PIBSA SMOSTO SMOCONC SMODIL P31:7
1-LAYER Unconstrained
2-LAYER Unconstrained
3-LAYER Unconstrained
v2
N
v2
N
v2
N
3.0 26.1 28.0 22.2 111.0
13 13 13 13 13
11.6 4.0 2.3 2.3 11.4
26 21 21 22 26
2.5 5.1 7.1 6.1 2.2
29 29 29 29 29
Table 3 Goodness of fit (v2), parameter number (N), scale factors and fitted SLDs (1014 m for the bulk emulsions for best constrained models. Name
PIBSA SMOSTO SMOCONC SMODIL P31:7
Model
1LAYER 2LAYER 2LAYER 2LAYER 3LAYER
v2
N
Scale factors
SLD emulsion
CM
UM
CM
UM
3.0
13
0.143(5)
0.080(3)
4.96(6)
3.30(2)
4.1
16
0.104(1)
0.0185(3)
4.59(1)
4.28(1)
2.2
17
0.109(1)
0.0259(4)
4.59(3)
4.16(1)
2.2
21
0.0120(2)
0.0134(2)
4.93(1)
4.23(1)
2.5
21
0.0090(1)
0.0215(3)
4.71(1)
4.38(1)
2
)
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Fig. 3. Scattering length density profiles as we traverse through the silicon–emulsion interface. Bulk silicon to the left, emulsions to the right. (a) PIBSA (b) SMOSTO (c) SMOCONC (d) SMODIL (e) P31:7 based emulsions. The solid line is the model for the contrast unmatched emulsion, the dotted for the contrast matched.
is the correlation between parameters for oxide and first surfactant monolayer. Limited resolution causes this, since both layers are narrow. While the oxide layer is fixed in the modelling, the first surfactant layer can vary from 0.5 1014 m 2 to boost or depress oxide SLD in the plot due to layer overlap (or roughness). Thus the first surfactant layer minimum varies from 2.0 1014 m 2 to 0.4 1014 m 2, while the ‘oxide’ maximum changes from 3.2 1014 m 2 to 4.7 1014 m 2.
These various post-facto physical checks on the modelling increase our confidence in the SLD profiles, but indicate that we should only interpret the results in terms of the trends and gross magnitudes of SLDs revealed in the range of surfactants studied here. We should not present any highly quantitative interpretations of the results, such as attempts to quantify layer compositions. The model parameters are too highly correlated to place that degree of reliance on them. However, the correlation does
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Table 4 Neutron scattering length densities for materials relevant to these experiments ( 1014 m Silicon D2O D2O almost saturated with NH4NO3 CM emulsion
2.07 6.36 4.57 4.5
2
).
Silicon dioxide (cristobalite) C16H34 Surfactants UM emulsion
indicate that the TOTAL SLD curves are not significantly affected by these coupled parameter changes.
3.49 0.44 0.2 to 0.6 3.9
H2O C16D34 Air
0.56 6.74 0.0
dependence on Q could be modelled, using the instrument characteristics and with a suitable patchiness model, but this is outside the scope of this paper.
3.2. Lateral non-uniformity of adsorbed layers 3.3. Specular scattering results and discussion Before discussing the specular scattering results and the derived SLD profiles perpendicular to the silicon surface, we will make some qualitative remarks connecting in-plane inhomogeneities in the various layers to features in the observed scattering profiles. These features are not rich in information, and a properly quantitative investigation of lateral structure requires other experiments, such as extensive off-specular scattering data. The features that we observe that suggest off-specular or SANS scattering are: (a) A scale factor of less than unity, often much less, which decreases from PIBSA to P31:7. The scale factor for UM samples is generally less than the CM samples. (b) Sharper and less rounded critical edge for the CM samples, than that for UM samples. (c) Reflectivity below the critical edge mostly decreases with decrease in Q. (d) SLDs for the bulk emulsion phases from the fit are larger than those calculated from the emulsion composition. (e) When the fits are extrapolated to the lowest observed Q values the reflectivities are distinctly larger than those of the very low Q observed data (which have been excluded from the fit). (f) The 0.5° and 1.2° sections of each reflectivity when modelled separately give very similar scale factors and good fits. The 0.25° section gives a lower scale factor and a poor overall fit. All these features can be explained if we postulate patches of adsorbed material which vary in structure or thickness, on the micron scale, as we move laterally across the silicon surface. Because the lateral coherence length of the neutrons in this instrument is many microns, this patchiness will reduce the specular scattering, giving scale factors less than one. The effect will be more pronounced for P31:7 than PIBSA, if the thicker and more complex P31:7 surface structure is more variable and rougher than the thinner simpler PIBSA surface structure. Similarly the UM samples will be apparently rougher than the CM, because the neutrons respond to the contrasting oil layer in addition to the surfactant layers. This oil layer is caused by ordering of micron scale droplets and the finer grained capillary waves at the droplet surface. It is reasonable to assume, given this lumpy structure, that this layer is rougher than those surfactant rich layers below, nearer the silicon surface. This extra roughness also causes rounding of the reflectogram at the critical edge. As Q is decreased the data derived from longer wavelength neutrons are more affected by lateral lumpiness than data from neutrons of lower wavelengths. This decrease in the apparent scale factor when low Q values are reached will increase the fitted values for bulk emulsion SLDs, and also cause the lowest, 0.25°, data section to have a lower scale factor. We are thus observing a situation where the fractional specular scattering (scale factor) is relatively constant at higher Q values, with a distinct collapse as the lowest values are reached. This is why we have excluded the lowest Q data from the model fits. This scale factor
A list of calculated SLDs for pure component materials is given in Table 4 to assist in interpretation of SLD profiles. The air–silicon interface reflectivity profiles (not shown) are fitted well by a single slab model in which a thin layer of oxide caps the silicon surface. The oxide layer thickness parameter, 9 Å, and the SLD’s of the layer, about 3.5 1014 m 2, are highly correlated because the Q range of SURF cannot resolve layers of this thinness. Therefore only the total amount of oxide is well defined, i.e., the product of the two parameters. Thus we can say nothing about any porosity in this oxide layer. The final D2O–silicon interface profiles agreed well with the initial air–silicon measurements in oxide layering – if a small correction is made for deuteration of surface O–H bonds on the oxide. The pairs of SLD profiles of the silicon–emulsion interfaces for CM and UM emulsions shown in Fig. 3a–e can be interpreted as interfacial layering steadily increasing in complexity. In all cases there is a narrow peak due to oxidised silicon at the solid–fluid interface where the SLD rises from the silicon value of 2.07 1014 m 2 to higher values characteristic of an oxide layer. Above this oxide layer there are further emulsion derived structures. Fig. 3a shows two SLD profiles for PIBSA based emulsions. Table 1 explains the emulsion terminology. These profiles have been presented previously [5]. The dotted line is that for the CM emulsion. This is deuterated to highlight the surfactant only. The PIBSA has an SLD close to zero, while the aqueous and oil phases within the emulsion have the same SLD close to 4.6 1014 m 2. We have obvious indication of a 20 Å thick monolayer of surfactant above the oxide. The solid line of the UM profile indicates further structure. The UM profile has low values for the SLD where either surfactant or oil are concentrated. Only the aqueous phase has a high SLD. Again just above the oxide we see SLD values characteristic of the surfactant monolayer observed in the CM profile, but above this is a further region of low SLD, which we must ascribe to an oil layer. This oil layer is about 150 Å thick and gradually blends into the bulk emulsion. We have previously intepreted this oil layer as resulting from a geometrical effect where the aqueous droplets are reorganised to accommodate the planar solid surface. This reorganisation necessarily requires the presence of an oil excess above the surfactant monolayer. Fig. 3b shows the SLD profiles from the SMOSTO emulsions. As for PIBSA the CM emulsion shows a monolayer of surfactant above the oxide, but now we see a further incomplete surfactant monolayer about 60–70 Å above the oxide. This is separated from the oxide-adsorbed surfactant monolayer by a region of high SLD. The UM contrast shows that this intervening layer is aqueous, because only the aqueous phase has high SLD in the UM contrast. The UM contrast also again indicates an oil layer above the second surfactant grading into the bulk emulsion over 300–400 Å. Fig. 3c and d show similar structures. However as we progress from SMOSTO through SMOCONC to SMODIL the second surfactant layer becomes a more complete monolayer.
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Finally Fig. 3e shows that we have developed a third surfactant layer with the P31:7-based emulsion. We can see from the CM contrast that the layers become less complete monolayers as we leave the oxide surface. The difference between UM and CM further shows a complementary increasing oil content in the layers. The two aqueous layers, separating the three oil + surfactant layers, are distinctly different, with the top aqueous layer being thicker. These profiles and structures follow a trend. The PIBSA is the most hydrophobic, followed by the SMOSTO, then SMO, with P31:7 being the most hydrophilic surfactant. The more hydrophilic the surfactant used, the greater the buildup of layered structure on the oxide surface. The layered structure of alternating aqueous and oil + surfactant regions begins to resemble in thickness and content the known lamellar phases. In these lamellar phases surfactant layers separate alternating oil and aqueous layers [6]. This may be occuring here, but we cannot resolve our single surfactant + oil layer (sandwiched between the two aqueous layers in the 3-LAYER model) into three layers of surfactant then oil then surfactant. However we do know that if there is progression to an even more hydrophilic surfactant, Pluronic L92, SANS on emulsions shows that in addition to aqueous droplets in a continuous oil-based phase a third lamellar bulk phase of just this type develops [6].
4. Conclusions Lamellar ordering of the surfactant in complex isotropic fluids at the air–fluid and solid–fluid interface has been observed before [1–4 and references therein]. This ordering can be from just a few lamellae, up to almost bulk reordering, with layer ordering on the micron scale. We have previously found a simple surfactant monolayer interface between a high internal phase emulsion and a silicon surface when a hydrophobic surfactant is used to stabilise the emulsion [5]. We have also found a micron scale thickness bulk lamellar phase is present at the aqueous–oil interface in a pure high internal phase emulsion stabilised by a much more hydrophilic surfactant [6]. In this paper, by using a series of surfactants of increasing hydrophilicity, we have shown that the transition from monolayer to multilayer structures at the silicon–emulsion interface is driven by increasing surfactant hydrophilicity. These structures not only develop some layers reminiscent of bulk lamellar phases perpendicular to the silicon surface, but also become
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increasingly rough parallel to the silicon surface. The adsorbed structure‘s surface becomes increasingly uneven. Acknowledgments The authors thank Dr. Stephen Holt and Dr. Steve King of the Rutherford-Appleton Laboratory, ISIS facility, for experimental assistance, and Dr. Steven Mork of Dow Chemical Co. for the gift of a P31:7 sample. Travel grants through the Australian Government ISTAC/ANSTO Access to Major Research Facilities programme are gratefully acknowledged. This work was financed by the Australian Research Council, under SPIRT and SRF awards jointly with Orica Ltd and ICI UK Ltd. We thank the referees for their helpful comments leading to a clarified paper. References [1] D.J. McGillivray, R.K. Thomas, A.R. Rennie, J. Penfold, D.S. Sivia, Langmuir 19 (2003) 7719. [2] J. Penfold, D.S. Sivia, E. Staples, I. Tucker, R.K. Thomas, Langmuir 20 (2004) 2265. [3] C. Åberg, E. Sparr, K.J. Edler, H. Wennerstrom, Langmuir 25 (2009) 12177. [4] S.E. Friberg, C. Solans, Langmuir 2 (1986) 121. [5] P.A. Reynolds, M.J. Henderson, S.A. Holt, J.W. White, Langmuir 18 (2002) 9153. [6] J. Zank, P.A. Reynolds, A.J. Jackson, K.J. Baranyai, A.W. Perriman, J.G. Barker, M.H. Kim, J.W. White, Physica B 385 (2006) 776. [7] P.A. Reynolds, E.P. Gilbert, J.W. White, J. Phys. Chem. B 104 (2000) 7012. [8] P.A. Reynolds, E.P. Gilbert, J.W. White, J. Phys. Chem. B 105 (2001) 6925. [9] P.A. Reynolds, E.P. Gilbert, M.J. Henderson, D.J. McGillivray, J.W. White, J. Phys. Chem. B 113 (2009) 12231. [10] P.A. Reynolds, E.P. Gilbert, M.J. Henderson, D.J. McGillivray, J.W. White, J. Phys. Chem. B 113 (2009) 12243. [11] P.A. Reynolds, D.J. McGillivray, J.P. Mata, P.N. Yaron, J.W. White, J. Colloids Interface Sci. 349 (2010) 544. [12] K.J. Baranyai, PhD Thesis, Australian National University, 2011. [13] P.N. Yaron, P.A. Reynolds, J.P. Mata, D.J. McGillivray, J.W. White, J. Phys. Chem. B 114 (2010) 3500. [14] P.N. Yaron, A.J. Scott, P.A. Reynolds, J.P. Mata, J.W. White, J. Phys. Chem. B 115 (2011) 5775. [15] P.A. Reynolds, M.J. Henderson, J.W. White, Colloids Surf. A 232 (2004) 55. [16] J. Penfold, R.M. Richardson, A. Zarbakhsh, J.R.P. Webster, D.G. Bucknall, A.R. Rennie, R.A.L. Jones, T. Cosgrove, R.K. Thomas, J.S. Higgins, P.D.I. Fletcher, E. Dickinson, S.J. Roser, I.A. McLure, R. Hillman, R.W. Richards, E.J. Staples, A.N. Burgess, T.D. Blake, J.W. White, J. Chem. Soc., Faraday Trans. 93 (1997) 3899. [17] A. Zarbaksh, J. Bowers, J.R.P. Webster, Meas. Sci. Technol. 10 (1999) 738. [18] S.A. Holt, P.A. Reynolds, J.W. White, Phys. Chem. Chem. Phys. 2 (2000) 5667. [19] J. Penfold, in: P. Lindner, Th. Zemb (Eds.), Neutron X-Ray and Light Scattering, Elsevier, Amsterdam, 1991, p. 223. [20] A.S. Brown, S.A. Holt, P.A. Reynolds, J. Penfold, J.W. White, Langmuir 14 (1998) 5532.
Contents lists available at SciVerse ScienceDirect
Journal of Colloid and Interface Science www.elsevier.com/locate/jcis
Complex layering observed in high internal phase emulsions at a silicon surface by neutron reflectometry Philip A. Reynolds ⇑, Mark J. Henderson, Johann Zank 1, John W. White Research School of Chemistry, Australian National University, Canberra, ACT 0200, Australia
a r t i c l e
i n f o
Article history: Received 9 June 2011 Accepted 21 August 2011 Available online 28 August 2011 Keywords: Neutron reflectivity Emulsions Lamellae Surface layers
a b s t r a c t The neutron reflectivity profiles from the interface between silicon and aqueous phase-in-oil high internal phase emulsions of steadily increasing surfactant hydrophilicity, are reported for two isotopic contrasts for each surfactant. Layered models are required to fit the structured reflectivity profiles that demonstrate that the oxidised top layer of the silicon is always covered by a surfactant monolayer. Interposed between the surfactant monolayer and the bulk emulsion is a layer of oil – a geometric effect caused by reorganisation of the aqueous droplets. As the surfactant hydrophilicity increases, alternating aqueous and oil + surfactant layers are inserted between this topmost oil layer and the oxide attached surfactant monolayer. The resulting structures have compositions and layer spacings suggestive of sections from lamellar phases. This increase in layer ordering with increasing surfactant hydrophilicity is expected. The bulk emulsions are observed to exhibit lamellar or sponge phases increasingly as surfactant hydrophilicity increases. Ó 2011 Elsevier Inc. All rights reserved.
1. Introduction The purpose of this paper is to understand the structure of an emulsion–solid surface interface as a function of the hydrophilic– hydrophobic balance of the emulsifying surfactant. In practical systems the emulsion stability depends, at least partly, on the nature of this interface since emulsions are often mixed with powdered solids to form a slurry. Lamellar ordering of other isotropic fluids at the air–fluid and solid–fluid interfaces is not uncommon, and is more fully discussed elsewhere [1–4]. The extent of ordering may range from a few layers up to micron scale. Previously we found a simple surfactant monolayer interface between a high internal phase emulsion and a silicon surface (with some secondary dispersed droplet reorganisation in the emulsion) when a hydrophobic surfactant is used to stabilise the emulsion [5]. Also a micron scale lamellar phase is present at the aqueous–oil interface for a pure high internal phase emulsion stabilised by a much more hydrophilic surfactant [6]. In related work we have previously examined aqueous-in-oil emulsions by Small Angle Neutron Scattering (SANS) [7–14], slurries of these emulsions containing powdered solids by SANS [15], and the silicon–emulsion interface by neutron reflectometry [5]. Here, by using a series of surfactants of increasing hydrophilicity, we suggest that the transition from ⇑ Corresponding author. Fax: +61 02 6125 4903. E-mail address: [email protected] (P.A. Reynolds). Present address: Orica Mining Services, George Booth Drive, Kurri Kurri, NSW 2327, Australia. 1
0021-9797/$ - see front matter Ó 2011 Elsevier Inc. All rights reserved. doi:10.1016/j.jcis.2011.08.053
monolayer to multilayer structures at the silicon–emulsion interface is driven by increasing surfactant hydrophilicity. All of the emulsions studied were high internal phase emulsions made from an aqueous saturated ammonium nitrate solution dispersed as highly polydisperse spheres with typical radius of a few micrometres, typically occupying a volume fraction of 90% with the remaining 10% volume occupied by a continuous oil phase. For the PIBSA surfactant where oil phase and surfactant tail are well matched in solvency the droplets are stabilised by a monolayer of adsorbed amphiphile at the aqueous oil interface using only a small fraction of the added surfactant. The remainder occurs as reverse micelles of typical radius 30–40 Å, within the oil phase; some dissolved molecules in the oil phase; and sometimes a third surfactant-rich phase aggregated at the aqueous–oil interface in micron scale blocks which are fractally linked [6–10]. At the other extreme of surfactant matching, using Pluronic L92Ò, the vast majority of surfactant is in the form of aggregate, located at the oil–droplet interface, with very few reverse micelles [6]. In the solid surface studies [5,15] the surfactant used to form the emulsion (polyisobutylene N-(2-hydroxyethyl)succinamide or PIBSA) produced simple interfaces. These consisted of a more or less complete monolayer of surfactant separating the dispersed aqueous droplets or solid particles from the continuous oil phase. In addition the solid–emulsion interface often exhibited an excess of oil above this monolayer, caused by the geometric effect in which aqueous droplets in the emulsion must be rearranged to best pack onto a planar solid surface.
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Each emulsion studied here has been examined in two isotopic variants, differently deuterated, such that in one case only the surfactant is highlighted, and in the other the surfactant together with oil are highlighted against the emulsion’s aqueous component. We show a progressively more lamellar character of the surface structure in the order (1) the previously examined PIBSA surfactant emulsions through, successively: (2) sorbitan monooleate–trioleate mixture (3) concentrated sorbitan monooleate (4) dilute sorbitan monooleate and (5) a pyridinium vinylbenzyl (butyleneoxide)31(ethyleneoxide)7 sulfate amphiphile.
2. Experimental 2.1. Experiments Silicon (1 1 1) polished face single crystal blocks were cleaned by an exposure of 1 min in a plasma chamber. The blocks were stored for future neutron reflectometry in sealed but not evacuated chambers with the hydrophilic silicon surface in contact only with air. The small air volume minimises surface contamination of the blocks [5]. Neutron reflectometry was performed 1 week later using the instrument SURF at the ISIS (UK) spallation neutron facility [16]. Measurements were recorded in three configurations (incident neutron angles 0.25°, 0.5° and 1.2°), which were combined to give the momentum transfer (Q) range 0.008–0.47 Å 1. The three sets of data splice together satisfactorily. This is a standard data acquisition setup. The data also were reduced in the standard way for SURF. The Q range typically spans the region from the critical edge in the reflectivity profile out to the incoherent scattering background caused by proton content of the sample. All runs were performed at the same SURF default resolutions for the same runtime. The hydrophilic surfaces of the silicon blocks gave complete wetting when Milli-Q™ water was used. The surface structure of a silicon block was defined by neutron reflectometry with neutrons passing through air and being reflected from the silicon block’s surface facing upward. This is denoted as the air–silicon interface. All subsequent experiments used the silicon–emulsion interface. A cell was used [17,18] in which neutrons pass through the silicon block and are reflected from fluid below the block and in contact with it. Transmission corrections for neutron absorption and scattering in the silicon block were performed. Cells were filled with various emulsions and the reflectivities measured. The cell and silicon surface were cleaned between samples by alternate washing with acetone and Milli-Q™ water. We have previously found that this procedure broke the emulsion and removed the components from a silicon block [5]. To ensure that this cleaning procedure was adequate, we measured a final set of reflectivities from cleaned cells filled with D2O. These were compared to the initial air–silicon measurements. Two checks were made to ensure that the cells were completely filled with emulsion, with no significant air bubbles remaining. First, the volume of emulsion injected by syringe was monitored at each filling. In all cases when excess emulsion emerged from the overflow tube, the volume injected corresponded to the fillable volume (measured separately), within an error of about 5%. Second, when the cells were opened, all samples appeared to have wet the silicon surface completely. The cells were opened with the minimum of sliding and twisting of the silicon against the rest of the cell. All the emulsions reported in this paper had a 90% aqueous internal volume fraction of almost saturated ammonium nitrate in D2O (53.4 wt.%). The amphiphiles used to stabilise the emulsions were sorbitan monooleate (Aldrich) at two concentrations
(denoted SMOCONC and SMODIL); a 50/50, by volume, mixture of sorbitan monooleate and sorbitan trioleate (Aldrich)(denoted SMOSTO); and the polymer diblock surfactant of approximate formula pyridinium vinylbenzyl (butyleneoxide)31(ethyleneoxide)7 sulfate (Dow P-31:7)(denoted P31:7). These can be compared to our previous experiments using a polydisperse mixture of polyisobutylene N-(2-hydoxyethyl) succinamide of median molecular weight about 1100, which we denote PIBSA. The oil used was nhexadecane (Aldrich) in all cases, except for the P31:7 amphiphile emulsions. The P31:7 surfactant emulsions used a 50/50 hexadecane/toluene mix because the amphiphile was not sufficiently soluble in hexadecane alone to form an emulsion. Each emulsion was prepared in two isotopically substituted variants, at constant volume fraction. The first contained hydrogenous oil with no deuterated oil. Thus the neutron scattering shows strong contrast only between the oil phase and the partially deuterated aqueous droplets. We denote this contrast unmatched (UM). The second used oil in which hydrogenous and deuterated oils were mixed so that the calculated oil phase scattering length density (SLD), assuming all the surfactant is dispersed in the oil phase, is the same as the partially deuterated aqueous ammonium nitrate phase. Here the scattering contrast in neutron reflectometry is between surfactant structures and the rest of the emulsion, oil plus aqueous components. For example reverse micelles in the oil phase and surfactant adsorbed at the oil/aqueous droplet interface will both be highlighted. We denote this contrast matched (CM). Reflectograms, normalised to unity by use of the fitted scale factor, and the curves fitted to these are shown in Figs. 1 and 2. The emulsions were prepared in 10 mL batches by adding the aqueous components to the amphiphile predissolved in the oil phase, while shearing the mixture with a snug fitting propeller, driven by an electric motor at a nominal 1900 rpm, for 5 min, in a closed Teflon container at 80 °C. The emulsion compositions are presented in Table 1, together with self-explanatory nomenclature for later reference to the emulsions.
Fig. 1. Normalised reflectivity from contrast matched emulsions at silicon interface, profiles offset for clarity. PIBSA (h), SMOSTO (j) 10, SMOCONC (+) 102, SMODIL (d) 103, P31:7 (s) 104. The continuous lines are the results from the model fitting.
P.A. Reynolds et al. / Journal of Colloid and Interface Science 364 (2011) 539–545
Fig. 2. Normalised reflectivity from contrast unmatched emulsions at silicon interface, profiles offset for clarity. PIBSA (h), SMOSTO (j) 10, SMOCONC (+) 102, SMODIL (d) 103, P31:7 (s) 104. The continuous lines are the results from the model fitting.
Table 1 Emulsion compositions (g) and nomenclature. Name
Surfactant
C16H34
PIBSA-UM PIBSA-CM SMOSTO-UM SMOSTO-CM SMOCONC-UM SMOCONC-CM SMODIL-UM SMODIL-CM P31:7-UM P31:7-CM
.21 .21 .18 .18 .18 .18 .06 .06 .075 .073
.85 .11 .63 .11 .63 .11 .75 .18 .36 .08
C16D34
C7H8
C7D8
Sat AN-D2O
.32
11.84 11.83 11.83 11.83 11.83 11.83 11.83 11.83 11.84 11.83
.87 .62 .62 .63 .32
.40 .11
2.2. Model choice and analysis strategy The reflectivity data were analysed by the optical transfer method using the program CXMULF [19,20]. The complete interface is modelled as a series of layers between the bulk silicon and bulk emulsion. Each layer has a thickness and SLD associated with it, and a roughness between it and the layer below (or above for air–silicon geometry). After the experimental resolution function was convolved with this model, appropriately constrained, it was simultaneously fitted to reflectivity data from both UM and CM emulsion samples. These models still have large numbers of variables, even after physical constraints are applied. In principle, it is possible to eliminate well-fitting models with unphysical results or interpretations – such as highly negative SLDs or apparent oil layers next to aqueous or other hydrophilic surfaces, with no mediating amphiphile layer. Starting from simple physical models, however, allows descent into physically realistic minima in goodness-of-fit, v2, with interpretable parameters. Attempts to achieve similarly low v2 by refining from unphysical starting models – such as a stack of identical slabs – sometimes dropped into one of the ‘physical’ models, but equally often produced unphysical results with
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slightly higher v2. Thus, our refined results do not give unique models and we must, as is often the case with reflectivity measurements, apply further physical criteria to choose the correct model. CXMULF can be forced to descend into a local minimum by use of Levenberg–Marquardt minimisation. When simulated annealing methods are used, minima more likely to be global can be accessed and explored. We have therefore adopted the strategy of testing a set of three ‘standard’ models. We start with completely unconstrained modelling and simulated annealing followed by Levenberg–Marquardt minimisation to obtain a minimum in v2. The resulting parameters mostly have large errors due to large correlations between parameters. But we have noticed, by fixing various parameters and re-refining the data, that the variation of SLD with distance through the interface is much more stable than the parameter values themselves. In the discussion we will therefore discuss these profiles rather than the actual values of the parameters. In the most complex case (P31:7) we require 29 parameters to describe the two reflectivity profiles without any constraints. The profiles contain significant structure, which allowed modelling to be guided by considering the inflection points and other information content in both profiles. We now turn to the model parameters and constraints in more detail. For all refinements the value of a flat background was refined for each of the UM and CM patterns. Most sources of background are relatively unstructured (e.g. incoherent scattering) but SANS from lamellar structures in the bulk emulsion would vitiate our model. SANS experiments on emulsions, which contain all these surfactants at various concentrations, have been performed and show no lamellar phase in the bulk [9 and unpublished data]. Only the normal aqueous droplet plus micellar scattering, which is not highly structured has been observed. Complications in the specular reflected intensity can arise from lateral height–height correlations and ‘‘off-specular’’ scattering [5], This layer roughness requires refinement of a scale factor for both UM and CM patterns and will be discussed in Section 3.2 below. Parameter numbers can be reduced by constraints. A general constraint we have used is to fix roughnesses involving the oxide surface at 3 Å, and all other fluid–fluid interfaces at 10 Å. An exception to this is the topmost oil–emulsion interface, which we have found necessary to refine, as it reaches large roughness values. These roughness values may reach up to half the (large) thickness of the oil layer – often 200 Å and 400 Å respectively. This is close to the limit of validity of the slab/roughness model. The parameters pertaining to the silicon oxide layer (SLD and thickness) were fixed at values obtained from the refinement of the emulsion free silicon–air reflectivity profile in this and all subsequent refinements. The oxide SLD was fixed at the value for cristobalite. Because of limited resolution at this low thickness, SLD and thickness are highly correlated. We choose the SLD of cristobalite although it is quite possible that the oxide surface could be lower due to porosity. A factor militating against this is the stability of the oxide layer in air. Lastly, in most cases we have restricted the data fitted to that with Q values greater than about 0.01 Å 1. The reason for this is that, except for two profiles, all our models are very poor fits in the lowest Q regions. We believe this is due to irregularities (height–height correlations) in the adsorbed in-plane structures at the silicon face, which we will discuss in Section 3.2 below. The three models for emulsion structuring at the silicon interface involve layering of surfactant, water, oil, or surfactant–oil mixtures. In each case, the bulk silicon is capped by a thin oxide layer. In the ‘1-LAYER’ model the oxide has an amphiphile monolayer adsorbed on it, while above this is an oil layer tailing off into bulk emulsion SLD. In the ‘2-LAYER’ model we have two surfactant–oil layers separated by an aqueous layer, before the oil layer is encountered. In the ‘3-LAYER’ model we have three
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surfactant–oil layers above the oxide, each separated by an aqueous layer, before the final oil layer is reached. In the infinite layer limit this would be a lamellar phase. Listing the model layers explicitly, we have for the UM samples
In Table 2 we have listed v2 and parameter number (N) for each model type for each emulsion set, together with similar data in Table 3 for the best constrained models. 3. Results and discussion
‘1-LAYER’ bulk silicon silicon oxide surfactant rich monolayer oil rich thick layer due to droplet reorganisation bulk emulsion ‘2-LAYER’ bulk silicon silicon oxide surfactant rich monolayer aqueous salt layer surfactant rich layer, possibly containing some oil oil rich thick layer due to droplet reorganisation bulk emulsion ‘3-LAYER’ bulk silicon silicon oxide surfactant rich monolayer aqueous salt layer surfactant rich layer, possibly trilayer (surfactant/oil/ surfactant) aqueous salt layer surfactant rich layer, possibly containing some oil oil rich thick layer due to droplet reorganisation bulk emulsion
SLD fixed SLD and thickness fixed SLD and thickness refined thickness, SLD and topmost roughness refined SLD refined SLD SLD SLD SLD SLD
fixed and thickness and thickness and thickness and thickness
fixed refined refined refined
thickness, SLD and topmost roughness refined SLD refined SLD fixed SLD and thickness fixed SLD and thickness refined SLD and thickness refined average SLD and thickness refined SLD and thickness refined SLD and thickness refined thickness, SLD and topmost roughness refined SLD refined
For the CM data the topmost oil layer is removed because oil and aqueous components of the emulsion have the same SLD, removing any contrast. We initially refined each pair of UM and CM profiles together in the 1-LAYER model, with the roughness and oxide layer constraints already outlined. The 2-LAYER model was refined using the results from the 1-LAYER model for the similarly placed layers. The extra layers inserted between 1-LAYER and 2-LAYER models were given starting values for the SLDs appropriate to their content, and thickness values from their nature. For example monolayer thicknesses for surfactant layers. The initial refinement was only of the values for these ‘new’ parameters. Subsequently the values for all layers were allowed to refine freely. Similarly, the 3-LAYER models were refined using values suggested by the results of the 2-LAYER refinement. This hierarchical method of model development ensured stable refinements, insensitive to precise starting values, and gave physically interpretable and sensible results. We subsequently applied more constraints to the models. Successively 1) we constrained equivalent layer thicknesses to be equal in both UM and CM cases; 2) we then constrained all aqueous layer SLD’s to be the same for the 3-LAYER model. Other obvious constraints were tried, but degraded the fit significantly. In particular the constraint making surfactant layer SLDs the same between UM and CM, and/or between different surfactant layers in CM or UM individually showed that differences in surfactant and oil content in the layers are significant.
3.1. Reliability of the modelling Table 2 shows that we can distinguish between the 1, 2 and 3 layer models and readily choose the best model on the basis of its v2. Comparison of the v2 values of Table 3 and the preferred models in Table 2 show that our constraints are not only physically reasonable but do not significantly degrade the fits. They are clearly worthwhile –a reduction of 8 parameters from 29 for the P31:7 surfactant provides reassurance in the interpretation of the fitted data. Further checks are provided by the refined values of the bulk emulsion SLDs given in Table 3. The expected values calculated from the emulsion compositions are about 4.5 1014 m 2 for the contrast matched (CM) emulsions and about 3.9 1014 m 2 for the unmatched (UM) emulsions, with only small variations due to change of surfactant. We obtain fitted values close to these but significantly different. These bulk SLDs are defined by the critical edge in the reflectivity. This occurs at Q values corresponding to distances of several 100 Å. This is perhaps an indication that our model is neglecting, or not perfectly fitting, some lateral surface structures on this scale. This is also signalled by the reduction in scale factors. These are far less than one, indicating much off-specular or SANS scattering, and will be explored in Section 3.2 below. In Fig. 3a–e the fitted values for the SLDs through the interface are plotted against distance above or below the silicon–silicon dioxide interface, defined as 0 Å in the distance scale. A last physical constraint is the requirement that SLDs remain between about 0.5 1014 m 2 and about 4.6 1014 m 2, which are the two extreme values for the added emulsion components. Examination of Fig. 3a–e shows that this is broadly so. The deviations reflect some model shortcoming. One shortcoming is probably inaccuracies or inadequacies in the roughnesses of the interfaces. Another
Table 2 Fits (v2), and parameter number (N) for various unconstrained models. Name
PIBSA SMOSTO SMOCONC SMODIL P31:7
1-LAYER Unconstrained
2-LAYER Unconstrained
3-LAYER Unconstrained
v2
N
v2
N
v2
N
3.0 26.1 28.0 22.2 111.0
13 13 13 13 13
11.6 4.0 2.3 2.3 11.4
26 21 21 22 26
2.5 5.1 7.1 6.1 2.2
29 29 29 29 29
Table 3 Goodness of fit (v2), parameter number (N), scale factors and fitted SLDs (1014 m for the bulk emulsions for best constrained models. Name
PIBSA SMOSTO SMOCONC SMODIL P31:7
Model
1LAYER 2LAYER 2LAYER 2LAYER 3LAYER
v2
N
Scale factors
SLD emulsion
CM
UM
CM
UM
3.0
13
0.143(5)
0.080(3)
4.96(6)
3.30(2)
4.1
16
0.104(1)
0.0185(3)
4.59(1)
4.28(1)
2.2
17
0.109(1)
0.0259(4)
4.59(3)
4.16(1)
2.2
21
0.0120(2)
0.0134(2)
4.93(1)
4.23(1)
2.5
21
0.0090(1)
0.0215(3)
4.71(1)
4.38(1)
2
)
P.A. Reynolds et al. / Journal of Colloid and Interface Science 364 (2011) 539–545
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Fig. 3. Scattering length density profiles as we traverse through the silicon–emulsion interface. Bulk silicon to the left, emulsions to the right. (a) PIBSA (b) SMOSTO (c) SMOCONC (d) SMODIL (e) P31:7 based emulsions. The solid line is the model for the contrast unmatched emulsion, the dotted for the contrast matched.
is the correlation between parameters for oxide and first surfactant monolayer. Limited resolution causes this, since both layers are narrow. While the oxide layer is fixed in the modelling, the first surfactant layer can vary from 0.5 1014 m 2 to boost or depress oxide SLD in the plot due to layer overlap (or roughness). Thus the first surfactant layer minimum varies from 2.0 1014 m 2 to 0.4 1014 m 2, while the ‘oxide’ maximum changes from 3.2 1014 m 2 to 4.7 1014 m 2.
These various post-facto physical checks on the modelling increase our confidence in the SLD profiles, but indicate that we should only interpret the results in terms of the trends and gross magnitudes of SLDs revealed in the range of surfactants studied here. We should not present any highly quantitative interpretations of the results, such as attempts to quantify layer compositions. The model parameters are too highly correlated to place that degree of reliance on them. However, the correlation does
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Table 4 Neutron scattering length densities for materials relevant to these experiments ( 1014 m Silicon D2O D2O almost saturated with NH4NO3 CM emulsion
2.07 6.36 4.57 4.5
2
).
Silicon dioxide (cristobalite) C16H34 Surfactants UM emulsion
indicate that the TOTAL SLD curves are not significantly affected by these coupled parameter changes.
3.49 0.44 0.2 to 0.6 3.9
H2O C16D34 Air
0.56 6.74 0.0
dependence on Q could be modelled, using the instrument characteristics and with a suitable patchiness model, but this is outside the scope of this paper.
3.2. Lateral non-uniformity of adsorbed layers 3.3. Specular scattering results and discussion Before discussing the specular scattering results and the derived SLD profiles perpendicular to the silicon surface, we will make some qualitative remarks connecting in-plane inhomogeneities in the various layers to features in the observed scattering profiles. These features are not rich in information, and a properly quantitative investigation of lateral structure requires other experiments, such as extensive off-specular scattering data. The features that we observe that suggest off-specular or SANS scattering are: (a) A scale factor of less than unity, often much less, which decreases from PIBSA to P31:7. The scale factor for UM samples is generally less than the CM samples. (b) Sharper and less rounded critical edge for the CM samples, than that for UM samples. (c) Reflectivity below the critical edge mostly decreases with decrease in Q. (d) SLDs for the bulk emulsion phases from the fit are larger than those calculated from the emulsion composition. (e) When the fits are extrapolated to the lowest observed Q values the reflectivities are distinctly larger than those of the very low Q observed data (which have been excluded from the fit). (f) The 0.5° and 1.2° sections of each reflectivity when modelled separately give very similar scale factors and good fits. The 0.25° section gives a lower scale factor and a poor overall fit. All these features can be explained if we postulate patches of adsorbed material which vary in structure or thickness, on the micron scale, as we move laterally across the silicon surface. Because the lateral coherence length of the neutrons in this instrument is many microns, this patchiness will reduce the specular scattering, giving scale factors less than one. The effect will be more pronounced for P31:7 than PIBSA, if the thicker and more complex P31:7 surface structure is more variable and rougher than the thinner simpler PIBSA surface structure. Similarly the UM samples will be apparently rougher than the CM, because the neutrons respond to the contrasting oil layer in addition to the surfactant layers. This oil layer is caused by ordering of micron scale droplets and the finer grained capillary waves at the droplet surface. It is reasonable to assume, given this lumpy structure, that this layer is rougher than those surfactant rich layers below, nearer the silicon surface. This extra roughness also causes rounding of the reflectogram at the critical edge. As Q is decreased the data derived from longer wavelength neutrons are more affected by lateral lumpiness than data from neutrons of lower wavelengths. This decrease in the apparent scale factor when low Q values are reached will increase the fitted values for bulk emulsion SLDs, and also cause the lowest, 0.25°, data section to have a lower scale factor. We are thus observing a situation where the fractional specular scattering (scale factor) is relatively constant at higher Q values, with a distinct collapse as the lowest values are reached. This is why we have excluded the lowest Q data from the model fits. This scale factor
A list of calculated SLDs for pure component materials is given in Table 4 to assist in interpretation of SLD profiles. The air–silicon interface reflectivity profiles (not shown) are fitted well by a single slab model in which a thin layer of oxide caps the silicon surface. The oxide layer thickness parameter, 9 Å, and the SLD’s of the layer, about 3.5 1014 m 2, are highly correlated because the Q range of SURF cannot resolve layers of this thinness. Therefore only the total amount of oxide is well defined, i.e., the product of the two parameters. Thus we can say nothing about any porosity in this oxide layer. The final D2O–silicon interface profiles agreed well with the initial air–silicon measurements in oxide layering – if a small correction is made for deuteration of surface O–H bonds on the oxide. The pairs of SLD profiles of the silicon–emulsion interfaces for CM and UM emulsions shown in Fig. 3a–e can be interpreted as interfacial layering steadily increasing in complexity. In all cases there is a narrow peak due to oxidised silicon at the solid–fluid interface where the SLD rises from the silicon value of 2.07 1014 m 2 to higher values characteristic of an oxide layer. Above this oxide layer there are further emulsion derived structures. Fig. 3a shows two SLD profiles for PIBSA based emulsions. Table 1 explains the emulsion terminology. These profiles have been presented previously [5]. The dotted line is that for the CM emulsion. This is deuterated to highlight the surfactant only. The PIBSA has an SLD close to zero, while the aqueous and oil phases within the emulsion have the same SLD close to 4.6 1014 m 2. We have obvious indication of a 20 Å thick monolayer of surfactant above the oxide. The solid line of the UM profile indicates further structure. The UM profile has low values for the SLD where either surfactant or oil are concentrated. Only the aqueous phase has a high SLD. Again just above the oxide we see SLD values characteristic of the surfactant monolayer observed in the CM profile, but above this is a further region of low SLD, which we must ascribe to an oil layer. This oil layer is about 150 Å thick and gradually blends into the bulk emulsion. We have previously intepreted this oil layer as resulting from a geometrical effect where the aqueous droplets are reorganised to accommodate the planar solid surface. This reorganisation necessarily requires the presence of an oil excess above the surfactant monolayer. Fig. 3b shows the SLD profiles from the SMOSTO emulsions. As for PIBSA the CM emulsion shows a monolayer of surfactant above the oxide, but now we see a further incomplete surfactant monolayer about 60–70 Å above the oxide. This is separated from the oxide-adsorbed surfactant monolayer by a region of high SLD. The UM contrast shows that this intervening layer is aqueous, because only the aqueous phase has high SLD in the UM contrast. The UM contrast also again indicates an oil layer above the second surfactant grading into the bulk emulsion over 300–400 Å. Fig. 3c and d show similar structures. However as we progress from SMOSTO through SMOCONC to SMODIL the second surfactant layer becomes a more complete monolayer.
P.A. Reynolds et al. / Journal of Colloid and Interface Science 364 (2011) 539–545
Finally Fig. 3e shows that we have developed a third surfactant layer with the P31:7-based emulsion. We can see from the CM contrast that the layers become less complete monolayers as we leave the oxide surface. The difference between UM and CM further shows a complementary increasing oil content in the layers. The two aqueous layers, separating the three oil + surfactant layers, are distinctly different, with the top aqueous layer being thicker. These profiles and structures follow a trend. The PIBSA is the most hydrophobic, followed by the SMOSTO, then SMO, with P31:7 being the most hydrophilic surfactant. The more hydrophilic the surfactant used, the greater the buildup of layered structure on the oxide surface. The layered structure of alternating aqueous and oil + surfactant regions begins to resemble in thickness and content the known lamellar phases. In these lamellar phases surfactant layers separate alternating oil and aqueous layers [6]. This may be occuring here, but we cannot resolve our single surfactant + oil layer (sandwiched between the two aqueous layers in the 3-LAYER model) into three layers of surfactant then oil then surfactant. However we do know that if there is progression to an even more hydrophilic surfactant, Pluronic L92, SANS on emulsions shows that in addition to aqueous droplets in a continuous oil-based phase a third lamellar bulk phase of just this type develops [6].
4. Conclusions Lamellar ordering of the surfactant in complex isotropic fluids at the air–fluid and solid–fluid interface has been observed before [1–4 and references therein]. This ordering can be from just a few lamellae, up to almost bulk reordering, with layer ordering on the micron scale. We have previously found a simple surfactant monolayer interface between a high internal phase emulsion and a silicon surface when a hydrophobic surfactant is used to stabilise the emulsion [5]. We have also found a micron scale thickness bulk lamellar phase is present at the aqueous–oil interface in a pure high internal phase emulsion stabilised by a much more hydrophilic surfactant [6]. In this paper, by using a series of surfactants of increasing hydrophilicity, we have shown that the transition from monolayer to multilayer structures at the silicon–emulsion interface is driven by increasing surfactant hydrophilicity. These structures not only develop some layers reminiscent of bulk lamellar phases perpendicular to the silicon surface, but also become
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increasingly rough parallel to the silicon surface. The adsorbed structure‘s surface becomes increasingly uneven. Acknowledgments The authors thank Dr. Stephen Holt and Dr. Steve King of the Rutherford-Appleton Laboratory, ISIS facility, for experimental assistance, and Dr. Steven Mork of Dow Chemical Co. for the gift of a P31:7 sample. Travel grants through the Australian Government ISTAC/ANSTO Access to Major Research Facilities programme are gratefully acknowledged. This work was financed by the Australian Research Council, under SPIRT and SRF awards jointly with Orica Ltd and ICI UK Ltd. We thank the referees for their helpful comments leading to a clarified paper. References [1] D.J. McGillivray, R.K. Thomas, A.R. Rennie, J. Penfold, D.S. Sivia, Langmuir 19 (2003) 7719. [2] J. Penfold, D.S. Sivia, E. Staples, I. Tucker, R.K. Thomas, Langmuir 20 (2004) 2265. [3] C. Åberg, E. Sparr, K.J. Edler, H. Wennerstrom, Langmuir 25 (2009) 12177. [4] S.E. Friberg, C. Solans, Langmuir 2 (1986) 121. [5] P.A. Reynolds, M.J. Henderson, S.A. Holt, J.W. White, Langmuir 18 (2002) 9153. [6] J. Zank, P.A. Reynolds, A.J. Jackson, K.J. Baranyai, A.W. Perriman, J.G. Barker, M.H. Kim, J.W. White, Physica B 385 (2006) 776. [7] P.A. Reynolds, E.P. Gilbert, J.W. White, J. Phys. Chem. B 104 (2000) 7012. [8] P.A. Reynolds, E.P. Gilbert, J.W. White, J. Phys. Chem. B 105 (2001) 6925. [9] P.A. Reynolds, E.P. Gilbert, M.J. Henderson, D.J. McGillivray, J.W. White, J. Phys. Chem. B 113 (2009) 12231. [10] P.A. Reynolds, E.P. Gilbert, M.J. Henderson, D.J. McGillivray, J.W. White, J. Phys. Chem. B 113 (2009) 12243. [11] P.A. Reynolds, D.J. McGillivray, J.P. Mata, P.N. Yaron, J.W. White, J. Colloids Interface Sci. 349 (2010) 544. [12] K.J. Baranyai, PhD Thesis, Australian National University, 2011. [13] P.N. Yaron, P.A. Reynolds, J.P. Mata, D.J. McGillivray, J.W. White, J. Phys. Chem. B 114 (2010) 3500. [14] P.N. Yaron, A.J. Scott, P.A. Reynolds, J.P. Mata, J.W. White, J. Phys. Chem. B 115 (2011) 5775. [15] P.A. Reynolds, M.J. Henderson, J.W. White, Colloids Surf. A 232 (2004) 55. [16] J. Penfold, R.M. Richardson, A. Zarbakhsh, J.R.P. Webster, D.G. Bucknall, A.R. Rennie, R.A.L. Jones, T. Cosgrove, R.K. Thomas, J.S. Higgins, P.D.I. Fletcher, E. Dickinson, S.J. Roser, I.A. McLure, R. Hillman, R.W. Richards, E.J. Staples, A.N. Burgess, T.D. Blake, J.W. White, J. Chem. Soc., Faraday Trans. 93 (1997) 3899. [17] A. Zarbaksh, J. Bowers, J.R.P. Webster, Meas. Sci. Technol. 10 (1999) 738. [18] S.A. Holt, P.A. Reynolds, J.W. White, Phys. Chem. Chem. Phys. 2 (2000) 5667. [19] J. Penfold, in: P. Lindner, Th. Zemb (Eds.), Neutron X-Ray and Light Scattering, Elsevier, Amsterdam, 1991, p. 223. [20] A.S. Brown, S.A. Holt, P.A. Reynolds, J. Penfold, J.W. White, Langmuir 14 (1998) 5532.