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Growth of Surfactant Domains in Protein Films Alan R. Mackie,*,† A. Patrick Gunning,† Luis A. Pugnaloni,‡ Eric Dickinson,‡ Peter J. Wilde,† and Victor J. Morris† Department of Materials Science, Institute of Food Research, Norwich Research Park, Colney NR4 7UA, United Kingdom, and Procter Department of Food Science, University of Leeds, Leeds LS2 9JT, United Kingdom Received March 10, 2003. In Final Form: April 30, 2003
Surfactants, in particular nonionic surfactants, form phase-separated domains when competitively displacing protein films from a fluid interface. The present article seeks to quantify the size, shape, and number of the growing domains as the displacement progresses. The two proteins used in this study, β-casein and β-lactoglobulin, were separately displaced by the nonionic surfactant Tween 20. In the cases of both proteins, the mean surfactant domain area was found to increase exponentially as a function of the fraction (area) of the interface containing surfactant. Similarly, the number of domains per unit area was found to decrease rapidly for both proteins as a function of the surfactant area fraction. While computer simulations of domain growth could not closely mimic either of these traits, they suggested that a likely explanation for this is that the rate of domain coalescence is controlled by the strength of the protein film. The mechanically stronger (more elastic) β-lactoglobulin films were better able to resist the coalescence than the mechanically weaker (more viscous) β-casein films. No simple relationship was found between the domain shape and the other measured properties of the film, except for the case of aged β-casein films, where the domain shapes became markedly less circular.
Introduction Many commercial colloidal systems, particularly in the food industry, are stabilized by a combination of proteins and low-molecular-weight surfactants or lipids. Proteins and surfactants employ very different and incompatible stability mechanisms. Thus, an understanding of the interactions between these two very different species is key to addressing issues of stability in such colloidal systems. With this in mind, work has been undertaken over the past few years to study the interactions between surfactants and proteins at interfaces.1-3 The advances made in interfacial rheology4-6 and molecular resolution imaging techniques7,8 have led to an improved understanding of these systems.9-11 In particular, the combined use of Langmuir-Blodgett (LB) deposition and atomic force microscopy (AFM) techniques has revealed the * Author to whom correspondence should be addressed. Telephone: 44 1603 255261. Fax: 44 1603 507723. E-mail: alan.mackie@ bbsrc.ac.uk. † Institute of Food Research. ‡ University of Leeds. (1) Dickinson, E. Colloid Surf., B: Biointerfaces 2001, 20, 197. (2) Sun, M. L.; Tilton, R. D. Colloid Surf., B: Biointerfaces 2001, 20, 281. (3) Miller, R.; Fainerman, V. B.; Makievski, A. V.; Kragel, J.; Grigoriev, D. O.; Kazakov, V. N.; Sinyachenko, O. V. Adv. Colloid Interface Sci. 2000, 86, 39. (4) Jones, D. B.; Middelberg, A. P. J. Chem. Eng. Sci. 2002, 57, 1711. (5) Burgess, D. J.; Sahin, N. O. J. Colloid Interface Sci. 1997, 189, 74. (6) Patino, J. M. R.; Sanchez, C. C.; Nino, M. R. R.; Fernandez, M. C. J. Colloid Interface Sci. 2001, 242, 141. (7) Gunning, A. P.; Mackie, A. R.; Kirby, A. R.; Morris, V. J. Langmuir 2001, 17, 2013. (8) Scheuring, S.; Fotiadis, D.; Moller, C.; Muller, S. A.; Engel, A.; Muller, D. J. Single Mol. 2001, 2, 59. (9) Bos, M. A.; van Vliet, T. Adv. Colloid Interface Sci. 2001, 91, 437. (10) Sengupta, T.; Damodaran, S. J. Agric. Food Chem. 2001, 49, 3087. (11) Girardet, J. M.; Humbert, G.; Creusot, N.; Chardot, V.; Campagna, S.; Courthaudon, J. L.; Gaillard, J. L. J. Colloid Interface Sci. 2001, 243, 515.
detailed mechanism by which surfactants competitively displace proteins from interfaces. This has led to the development of a new “orogenic” displacement model.12-16 Orogenic displacement occurs in the following manner. Heterogeneity in the protein film, due to packing limitations, allows the added surfactant to adsorb into localized defects, and these nucleated sites then grow. The expansion of the surfactant domains compresses the protein network, which initially increases in density without increasing in thickness. Once a certain critical density is reached, the thickness of the protein layer increases such that the total protein film volume is maintained as the surfactant domains expand. At sufficiently high surface pressures, the continuous protein network fails, releasing protein, which then desorbs from the interface. This model has been shown to work12-16 for a range of proteins with different secondary and tertiary structures and at solid/ liquid, liquid/liquid, and gas/liquid interfaces. It has also been shown to apply for different types of surfactant, that is, nonionic, cationic, anionic, and zwitterionic. The model has highlighted the importance of the surface pressure induced by the adsorbed surfactant and the elasticity of the protein film, which resists the expansion of the surfactant domains. It has been also shown17 that protein films can continue to strengthen over long periods of time, thus potentially making them more difficult to displace. This article considers the effect of protein film aging on the competitive displacement process. (12) Mackie, A. R.; Gunning, A. P.; Wilde, P. J.; Morris V. J. J. Colloid Interface Sci. 1999, 210, 157. (13) Gunning, A. P.; Mackie, A. R.; Wilde, P. J.; Morris, V. J. Langmuir 1999, 15, 4636. (14) Mackie, A. R.; Gunning, A. P.; Wilde, P. J.; Morris, V. J. Langmuir 2000, 16, 2242. (15) Mackie, A. R.; Gunning, A. P.; Wilde, P. J.; Morris, V. J. Langmuir 2000, 16, 8176. (16) Mackie, A. R.; Gunning, A. P.; Wilde, P. J.; Morris, V. J. Langmuir 2001, 17, 6593. (17) Garofalakis, G.; Murray, B. S. Colloid Surf., B: Biointerfaces 2001, 21, 3.
10.1021/la034409o CCC: $25.00 © 2003 American Chemical Society Published on Web 06/20/2003
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Materials and Methods
Figure 1. AFM images of the displacement of β-lactoglobulin (a, b) and β-casein (c, d) from the air/water interface by Tween 20. The images are 1.0 µm, 3.2 µm, 6.4 µm, and 6.4 µm, respectively. The light regions are the protein film, and the dark regions are where the surfactant was.
It would be extremely useful to have models that predict the growth of domains or changes in the domain shape. A computer simulation model of the competitive displacement of globular proteins by low-molecular-weight surfactants has been recently advanced.18 In this approach, a protein film is modeled as a quasi two-dimensional network of spheres connected through flexible bonds and adsorbed to a planar surface. A second species of surfaceactive spheres, which do not form bonds, either with each other or with the “proteins”, is then introduced beneath the film to promote competition for the interface. With the use of a Brownian dynamics algorithm, it has been demonstrated18,19 that this type of model can reproduce the heterogeneous way in which nonionic surfactants displace protein films. The orogenic model has already been beneficial when predicting the behavior of complex food systems. However, so far, despite its broad range of applicability, the precise character of the displacing surfactant domains has not been examined in detail. Previously, work has been in the form of graphs of the area occupied by protein (%) as a function of the surface pressure. These graphs were based on images such as those shown in Figure 1. The work described here uses image analysis to measure size and shape parameters for a large number of surfactant domains with a view to yield a more detailed description of “orogenic” displacement. Comparisons are made with the analysis of images created by Brownian dynamics simulations of the displacement process. The domain growth parameters are also compared to those generated by a new phenomenological type of domain growth simulation. Also, the experimental data have been extended to include the effect of protein film aging on the kinetics of displacement. This has been included because of published reports17 that protein films can become more difficult to displace as they age. (18) Wijmans, C. M.; Dickinson, E. Langmuir 1999, 15, 8344. (19) Wijmans, C. M.; Dickinson, E. Langmuir 1998, 14, 7278.
The milk proteins used in this study were β-lactoglobulin (L0130, lot 91H7005) and β-casein (C-6905, lot 12H9550) from Sigma Chemicals (Poole, U.K.). Samples were initially prepared at 2 mg/mL in water. The water used in this study was surface pure (γ0 ) 72.6 mN/m at 20 °C), cleaned using an Elga Elgastat UHQ water purification system. The surfactant used was poly(oxyethylene) sorbitan monolaurate (Tween 20), which was obtained as a 10% solution (Surfact-Amps 20) from Pierce (Rockford, IL). Surface-tension measurements were made using a wetted ground glass Wilhelmy plate and a Langmuir trough (Labcon, Ltd., Durham, U.K.). The poly(tetrafluoroethylene) trough had one fixed and one mobile barrier. All experiments were performed at room temperature (22 °C) with distilled water as the subphase. Films formed by spreading were done so by dropwise addition directly to the surface from protein solutions of 2 mg/mL in 10 mM sodium phosphate (pH 7.0). The LB films were formed on hydrophilic freshly cleaved mica substrates. The LB films were produced by lowering a freshly cleaved piece of mica sheet, mounted perpendicular to the interface, down through the interface and then pulling it back out again. The mounted piece of mica was driven at a constant rate of 0.2 mm/s. The surface tension was monitored during the dip, and this showed that the protein film was only transferred onto the mica on the upward stroke. The AFM images were collected under butanol. The precise details of the AFM and the imaging techniques are given elsewhere.20 The AFM images were analyzed using Image-Pro software (Media Cybernetics, Inc., Silver Spring, MD). Analysis consisted of applying a flattened filter so that a background correction could be applied to the images. A count/measure operation was then performed on the resulting image. This counted the number of dark regions in the image, which correspond to the surfactant domains, and measured the required size and shape parameters. A minimum domain size threshold was used to counter pixelation effects; that is, for a given image the minimum domain size included in calculations was about four pixels. A total of more than 84 000 domains were analyzed in 40 different protein films. Two types of simulations have been investigated. The first is a Brownian dynamics simulation based on a statistical model described in detail elsewhere.18,21 Briefly, 1000 spheres of unit diameter, “the proteins”, are placed at an “adhesive” planar interface and allowed to form a quasi two-dimensional network through elastic bonds. Then, 2000 “small” spheres (relative diameter 0.5), which do not form any bonds, are introduced beneath the interface to simulate the nonionic surfactant, so promoting competitive adsorption. The small spheres are assigned a higher preference for the interface than the big spheres (about 10 times higher adsorption energy), so that they displace the proteins from the interface. The big spheres can rearrange their network structure by two mechanisms: first, by breaking bonds as they stretch apart beyond a critical bond length (0.4 particle diameters) and, second, by forming new bonds with a reaction probability of unity.21 Periodic boundary conditions are applied to the interfacial plane. Detailed descriptions of the displacement patterns found in this type of simulation can be found elsewhere.18,22 Because the amount of domain growth that can occur is limited in the simulation just described, a second phenomenological simulation was designed. This model was introduced to follow the displacement behavior commencing from when the surfactant domains first become visible by AFM. The model consists of a number of circles randomly placed in a plane with a number density of 300 circles/µm2. The areas of the circles are selected from a log-normal distribution with a mean of 125 nm2 and a width corresponding to that seen in the experimental data. The fraction of the surface occupied by the circular domains was about 5% at the start of the simulation. The domains are allowed to (20) Mackie, A. R.; Gunning, A. P.; Ridout, M. J.; Morris, V. J. Biopolymers 1998, 46, 245. (21) Wijmans, C. M.; Dickinson, E. Phys. Chem. Chem. Phys. 1999, 1, 2141. (22) Pugnaloni, L. A.; Ettelaie, R.; Dickinson, E. Colloid Surf., B: Biointerfaces, accepted for publication.
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Table 1. Log-Normal Surfactant Domain Area Distribution Parameters for a Selection of Displacement Curves for Both β-Lactoglobulin (LG) and β-Casein (CAS)a protein
interface
spread/adsorbed
surface pressure (mN/m)
surfactant area (%)
mean domain area (µm2)
distribution width
LG LG LG LG CAS CAS CAS CAS CAS CAS
air/water air/water air/water air/water air/water air/water air/water air/water oil/water oil/water
S S A A S S A A S S
18.6 24.6 25.1 29.1 15.9 19.2 20.4 20.7 24.9 30.5
13 90 36 70 3 64 34 49 7 78
0.000 18 0.005 78 0.002 49 0.009 28 0.000 13 0.091 04 0.018 75 0.018 56 0.000 33 0.016 24
0.418 0.429 1.64 0.495 0.352 0.518 0.431 0.446 0.298 0.833
a
Data are given for the start and end of displacement where possible. The data in rows 5 and 6 are derived from Figure 2.
grow according to the basic rules of the Langmuir isotherm; that is, there is a balance between the amounts of surfactant arriving and leaving the interface. The amount arriving is proportional to the bulk concentration, which is assumed not to vary significantly over the course of the experiment. In the standard adsorption model for a simple surfactant system, the amount of surfactant leaving the surface is governed by the surface coverage. However, in this case the surface is dominated by the protein. Because of the elastic nature of the protein film, we propose a difference in pressure between the surfactant domain and the protein domain. This leads to a line tension at the domain boundary. To account for this, we have introduced a line tension into the model such that the area of the circle (a) is allowed to increase at a rate proportional to the circle circumference and inversely proportional to the surface pressure (Π) generated by the surfactant (eq 1).
da 2πr ) dt cΠ
(1)
where r is the radius of domain and c is a constant. The surface pressure was calculated as a function of the protein area fraction from experimental data. The circles are allowed to coalesce, and periodic boundary conditions are applied. For the purposes of the coalescence, the continuous region is treated as a liquid; that is, when two domains coalesce the resulting domain remains circular and moves to the center of gravity of the two original domains. The mean circle radius, the number of circles, and the proportion of the area occupied by the circles are all monitored. This model was designed to cover the range of sizes resolved by AFM and does not have the resolution of the Brownian dynamics simulation described earlier.
Results AFM images were previously analyzed to yield the area occupied by the protein as a proportion of the total area.12-16 This analysis has been extended to the measurement of size and shape parameters for the individual surfactant domains within the images. The initial parameters used were the domain area, the domain density (i.e., the number of domains per unit area), and a shape parameter, “roundness” (R), defined by
R ) P2/4πa
(2)
Here, P is the domain perimeter length and a is the domain area. Thus, a perfect circle gives a value of unity. The shape of the domains can be used to infer information about the strength of the protein film.12 Figures 2-5 show some image analysis results of mixed β-casein: Tween 20 films at both the air/water and oil/ water interfaces. Figure 2 shows the size distribution of domain areas to be log-normal both in the early stages (30 min after surfactant addition) and the final stages of protein displacement (150 min after surfactant addition). The two distributions have widths that differ by about
Figure 2. Size distributions of surfactant domains in a mixed β-casein/Tween 20 film at the air/water interface both at the start (outline) and end (solid) of displacement. The surfactant took some 3 h from first addition to completely remove the protein film.
40%. The data shown are specifically for β-casein spread at the air/water interface, but the plot is representative of all the data analyzed for both β-casein and β-lactoglobulin, in that the functional form of the distribution is approximately log-normal and does not alter significantly over the course of the displacement. A selection of these data are shown in Table 1. While the shape of the domain size distributions does not in general change over the course of displacement, there are differences in the shapes of the distributions produced under different conditions (see Table 1). Figure 3 shows the variation in the mean area of the individual surfactant domains as a function of the proportion of the film area occupied by surfactant (surfactant area fraction). It is clear from both Figures 2 and 3 that the domains grow in size as surfactant displacement of the protein film progresses. The distribution of domain areas is log-normal, and the functional form is unchanged by the domain expansion. Therefore, the relationship between the mean domain area and the proportion of the film area occupied by surfactant can be approximated by
a j ∝ ekA
(3)
where A is the proportion of the film occupied by surfactant (expressed as a percentage), a j is the mean domain area, and k is a rate constant. The fitted value of k for all the β-casein data was 0.109. The continuous line in Figure 3 was produced by simulation based on the phenomenological model for expanding domains previously described. The data are a mean of 10 simulations and show two distinct regimes. The first, in the early stages of domain expansion up to a surfactant area fraction of about 30%,
Surfactant Domains
Figure 3. Mean surfactant domain area as a function of the surfactant area fraction (%) for both spread (outlined symbols) and adsorbed (solid symbols) films of β-casein at the air/water (diamonds) and oil/water (squares) interfaces. The dashed line is the best-fit line through the data. The continuous line is the mean result from 10 runs of the phenomenological domain growth simulation.
Figure 4. Surfactant domain density (µm-2) as a function of the surfactant area fraction (%) for both spread (outlined symbols) and adsorbed (solid symbols) films of β-casein at the air/water (diamonds) and oil/water (squares) interfaces. The continuous line is the result from the phenomenological domain growth simulation.
is a result primarily of domain growth with only limited coalescence. The second regime shows a steeper rise in mean domain area as a function of the surfactant area fraction and is primarily caused by coalescence of the domains. The model was unable to reproduce exactly the same increase in the mean domain area found experimentally. The first stage of domain growth is matched reasonably closely, but the coalescence phase causes the mean area to rise too steeply. In other words, the model allows too much coalescence when compared to the experimental system. It has been shown that protein displacement occurs via an “orogenic” mechanism,12 which relies on the nucleation of domains that subsequently expand. It is unclear, however, whether the nucleation of domains is limited to the early stages of displacement or whether holes continue to nucleate as displacement progresses. Figure 4 shows the calculated domain number density as a function of the surfactant area fraction. It is clear that the number density falls as the displacement progresses, presumably at least in part as a result of domain coalescence. In fact, the number density falls from initial levels of a few hundred/µm2 down to around 10 (or less)/µm2. Again, the
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Figure 5. Mean roundness of the surfactant domains as a function of the surfactant area fraction (%) for both spread (outlined symbols) and adsorbed (solid symbols) films of β-casein. The data shown are for the air/water (diamonds) and oil/water (squares) interface. Also shown are data for an aged film at the air/water interface (triangles).
results from the phenomenological simulation of expanding domains are plotted as a continuous line on this figure. As in the previous figure, the simulation fails to match the data, showing that the numerical model did not remove the small domains fast enough. In addition to the size of the surfactant domains, we have also studied their shape. Figure 5 shows domain roundness as defined by eq 2 plotted as a function of the proportion of the film occupied by surfactant. The graph shows data for various β-casein films, spread or adsorbed at either the air/water or oil/water interfaces. It is clear from our previous work12 that newly formed films of β-casein displaced from the air/water interface form circular or near-circular domains. Accordingly, we see that the average roundness values for these films are 1.2 or less, the only exception being for the data in the early stages of displacement, which have a roundness value of 1.4. In contrast to this, the value for β-casein at the oil/ water interface is higher, between 1.4 and 2. The aged β-casein sample also displayed less rounded domains, with a roundness value in excess of 2. β-Lactoglobulin forms more elastic films than β-casein, which makes them more difficult to displace.12 Images of β-lactoglobulin films were, therefore, analyzed separately, and the results are shown in Figures 6-8. In Figure 6, the mean surfactant domain area is plotted as a function of the surfactant area fraction. As in the case of β-casein, the data can be approximated by eq 3 with a value for k of 0.0675, which is about half the value for β-casein. This indicates a less marked difference in growth between larger and smaller domains than was the case for the β-casein. The phenomenological simulation of domain growth matches the β-lactoglobulin data less closely than the β-casein data (Figure 3). Figure 7 shows the domain density as a function of the proportion of the film occupied by surfactant. The density falls rather more gradually than that for β-casein (Figure 4) from a value of a few hundred/µm2 to values of a few tens of domains/µm2. The β-lactoglobulin data (Figure 7) are consistently higher than the domain density values for β-casein (Figure 4). While the simulation results (continuous line) fall unevenly, they actually resemble the data for β-lactoglobulin more closely than β-casein. The domain shape data for β-lactoglobulin, shown in Figure 8, is markedly different from that of the β-casein in Figure 5. The surfactant domains in the
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Figure 6. Mean surfactant domain area as a function of the surfactant area fraction (%) for both spread (outlined symbols) and adsorbed (solid symbols) films of β-lactoglobulin at the air/ water (diamonds) and oil/water (squares) interfaces. The dashed line is the best-fit line through the data. The continuous line is the mean result from 10 runs of the phenomenological domain growth simulation.
Mackie et al.
Figure 8. Mean roundness of the surfactant domains as a function of the total surfactant area (%) for both spread (outlined symbols) and adsorbed (solid symbols) films of β-lactoglobulin at the air/water (diamonds) and oil/water (squares) interfaces.
Figure 9. Mean displacer domain area as a function of the displacer area fraction (%) generated by the Brownian dynamics simulation. The continuous line is the result from the phenomenological domain growth simulation. Figure 7. Surfactant domain density (µm-2) as a function of the total area of surfactant (%) for both spread (outlined symbols) and adsorbed (solid symbols) films of β-lactoglobulin at the air/ water (diamonds) and oil/water (squares) interfaces. The continuous line is the result from the phenomenological domain growth simulation.
β-lactoglobulin film become gradually less circular and more convoluted as the displacement progresses; with the exception of protein spread at the oil/water interface, all the data show the same trend. It would appear from Figures 2-8 that the way in which the expanding surfactant domains behave is controlled by the interfacial properties of the protein component of the film. However, there does not appear to be a single parameter that can be used to predict this behavior. Because of the complex behavior of these systems, various types of modeling may be used to provide useful insights. We report here on the use of two completely different types of simulation. First, a Brownian dynamics simulation of a gel-like protein layer was constructed to provide information at the molecular scale. Two-dimensional projections of the model spheres on the plane of the interface were used to mimic the imaging of a high-resolution AFM scan. Only the big spheres, which represent the proteins, were included in each image. Additionally, the spheres were rendered with an effective diameter slightly larger (10%) than the actual diameter. In this way, two very close spheres are seen as a single object; that is, they would overlap on the image, as would be the case during
Figure 10. Displacer domain density as a function of the displacer area fraction (%) by the Brownian dynamics simulation. The continuous line is the result from the phenomenological domain growth simulation.
an AFM scan. It is important to note that no topographic information can be obtained from these images. The final images are black-and-white representations of surfactantrich and protein-rich regions. The results of this analysis are shown in Figures 9 and 10 along with data from the phenomenological domain expansion simulation for comparison. The arbitrarily scaled mean domain area is shown in Figure 9 as a function of the displacer area fraction. Although the data from the Brownian dynamics simulation covers only a limited range, it does not follow the relationship of eq 3 (correlation coefficient of 0.96). Instead,
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Figure 11. Protein area fraction (%) as a function of the surface pressure for fresh (diamonds) and aged (squares) β-casein. The aging was for 24 h.
there seems to be a linear relationship between the mean domain area, a, and A (correlation coefficient 0.98). Similarly, the data in Figure 10 show that the number of domains falls very steeply as a function of the displacer area fraction. This seems to better follow the experimental findings (see Figure 7). No single surface rheological parameter measured for these films can be used to predict the behavior for all the proteins studied. Despite this, there is one major factor that can impinge on both the rheological properties and the ease of displacement of a protein film: film aging. Because the complex structures that make up a protein film continue to change over long periods of time (days), the properties of the film can also change significantly. We have investigated these changes here specifically for β-casein films, although it should be recognized that most protein films also strengthen with age. Figure 11 shows the way in which the proportion of the surface area occupied by protein changes as surfactant is added, as a function of surface pressure for both fresh and aged (24 h) films. The difference in the displacement pressures between the fresh and the aged films is clear, the aged film being more difficult to displace than the fresh one, that is, requiring a higher surface pressure. This pattern of behavior has been seen before for other proteins.23 The AFM images taken of the fresh and aged films also show marked differences. Figure 12a shows an image of a fresh β-casein film being displaced by Tween 20 and transferred to the substrate at a surface pressure of 19.2 mN/m. The image in Figure 12b shows an aged β-casein film transferred at a surface pressure of 21.3 mN/m. There are very clear differences between the morphology of the domains despite the fact that the protein occupies the same proportion of the interface in both cases, that is, 36.5%. The increase in surface pressure required to displace the same amount of protein highlights the fact that the aged film was stronger than the fresh one. These differences were quantified by image analysis, and details of the resulting parameters are given in Table 2. The mean domain area for the fresh film in Figure 12a is very similar to that for the aged film in Figure 12b. The mean domain areas calculated from all the images of the two transferred films are also very similar to these values. Thus, it would appear that, at least for β-casein, the aging process has little or no effect on the growth of the domains as a function of the area they occupy even though an aged film requires a higher surface pressure to displace it. However, there (23) Leaver, J.; Law, A. J. R.; Brechany, E. Y.; McCrae, C. H. Int. J. Food Sci. Technol. 1999, 34, 503.
Figure 12. Images of partially displaced protein films of β-casein. The image of the fresh film (a) is 6.4 × 6.4 µm and the aged film (b) is 10 × 10 µm.
is clearly an effect on the shape of the domains. The roundness shape parameter shows a large difference between the fresh and aged films. This links the greater strength of the film, in terms of the surface pressure required to displace it, to the more convoluted shape of the domains. Discussion In this article, we have looked at the information that can be provided by a detailed examination of surfactant domain size and shape through the course of displacement of a protein film by nonionic surfactant. It is clear from Figures 3-8 that there were significant differences between the domain parameters of interfacial films formed
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Table 2. Hole-Shape Parameters for Fresh and Aged β-Casein Filmsa min domain area mean domain area max domain area min perimeter mean perimeter max perimeter min roundness mean roundness max roundness a
fresh (mean)
fresh (image)
aged (mean)
aged (image)
0.002 0.185 ( 0.032 6.283
0.01 0.234 ( 0.098 3.941 0.291 1.437 ( 0.256 10.49 1 1.099 ( 0.033 2.222
0.0002 0.158 ( 0.029 7.218
0.006 0.239 ( 0.067 4.631 0.207 2.090 ( 0.372 17.88 1 2.023 ( 0.150 5.693
1 1.179 ( 0.017 3.097
1 2.166 ( 0.105 20.33
Data are given on the basis of both the images in Figure 11 and the mean based on all the images taken at the same surface pressure.
from β-lactoglobulin and β-casein. It is not yet clear what these differences tell us about the interfacial protein layer. We have shown that the mean areas of the individual surfactant domains have an exponential relationship to the surfactant area fraction. This indicates that the surfactant domains do not all grow at the same rate, as they do in the Brownian dynamics simulation. Instead, experimentally, it was found that the larger domains grew at the expense of the smaller ones, increasing the mean domain area exponentially. The data show that the mean domain area increased more rapidly for β-casein than that for β-lactoglobulin. For both proteins, we see that the number of surfactant domains per unit area decreases sharply as the surfactant area fraction increases. The domain density in the β-casein films was found to fall more steeply than that in the case of β-lactoglobulin, or at least to fall to a lower value; that is, there were fewer domains left at percolation in the β-casein films than those in the β-lactoglobulin films. The phenomenological simulation showed that the main driver for the increase in mean area and the decrease in the number of domains per unit area was coalescence and not the rate of domain growth. All these factors can be combined into the following hypothesis. First, the decrease in the domain density suggests that no nucleation of new domains took place after the initial stages of surfactant adsorption. Second, the mean-area increases suggest that coalescence took place faster in the β-casein films than that in the β-lactoglobulin films and faster still in the phenomenological domain growth model, which assumes a liquidlike continuous phase. This shows that the growth and coalescence of the domains are not fully accounted for in the model because the mean domain size is controlled by the rate of coalescence, which in turn is a function of the surface rheological properties of the protein film. Thus, the more elastic the film the less coalescence occurs and the slower the mean domain area increases. When the first paper on the orogenic displacement mechanism was published in 1999, it seemed clear that the differences in the domain shapes seen between β-casein and the globular proteins were caused by differences in the interfacial rheology.12 However, Figure 5 reveals that the displacement yields a broad range of roundness values that are dependent on the type of the interface and the age of the film. It has been shown24 that there is little discernible difference in the interfacial rheology of β-casein
films at the air/water and oil/water interfaces. From Figure 11, the data show that film aging has a small effect on the surface pressure at which displacement occurs. However, it is evident, both from the images in Figure 12 and the data in Table 2, that the effect upon the domain shape is marked. A correlation between film aging and interfacial rheology is already well-known.25-27 From this, we can infer that the changes in domain shape for this system are a result of increases in the protein film strength and, in particular, the fracture stress. When protein film displacement occurs, the expansion of the surfactant domains means that the protein layer is subject to large deformations. Thus, we should consider results from large deformation interfacial rheological studies, such as those of Martin et al. These studies highlight the way that β-casein flows under large deformations while β-lactoglobulin fractures, and these fractures are then propagated, as seen in Figure 1. An alternative solution to the difficulty of linking the domain shape to the film rheology is through the application of the Brownian dynamics simulation approach to the process of protein displacement by surfactant. Such simulations have in the past been used to provide surface rheological parameters of gel-like “protein” layers without added displacer “surfactant” particles.19 Thus, it should be possible to do the same in the presence of the particles. The phenomenological model should also be extended to include the rheological properties of the continuous region. So, despite the fact that the results shown from both simulations fail to closely match the experimental data in Figures 3-8, some useful conclusions have been drawn. Acknowledgment. This work was funded by the BBSRC under Grants 24/D13961 and 218/D14067. The Brownian dynamics simulation was done at the Leeds Grid Node 1 facility, funded under the 2001 HEFCE Science Research Investment Fund initiative, at the University of Leeds, which is one of the partners in the White Rose Grid project. LA034409O (24) Williams, A.; Prins, A. Colloids and Surf., A: Physicochem. Eng. Aspects, 1996, 114, 267. (25) Roth, S.; Murray, B. S.; Dickinson, E. J. Agric. Food Chem. 2000, 48, 1491. (26) Martin, A. H.; Bos, M. A.; van Vliet, T. Food Hydrocolloids 2002, 16, 63. (27) Martin, A. H.; Grolle, K.; Bos, M. A.; Cohen Stuart, M. A.; van Vliet, T. J. Colloid Interface Sci. 2002, 254, 175.
