Ultrasound-Assisted Generation of Foam - American Chemical Society

Department of Chemical Engineering, The University of Birmingham, Edgbaston,. Birmingham B15 2TT, United Kingdom. Foams represent an important class o...
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Ind. Eng. Chem. Res. 2005, 44, 3312-3320

Ultrasound-Assisted Generation of Foam Khai Sin Lim and Mostafa Barigou* Department of Chemical Engineering, The University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom

Foams represent an important class of structured liquids of relevance to a wide range of industries. Their quality is mostly determined by their complex cellular structure, which defines primarily their texture and to a large extent their rheology and stability. The foam structure is influenced not only by the formulation used but also crucially by the production process adopted, hence the need for production techniques that can assist in the generation of foams with controlled structures. The ability of high-intensity ultrasound waves to influence the mean bubble size and texture homogeneity of foam generated pneumatically has been investigated. An ultrasound probe located near the pneumatic foam generator and operating at a fixed frequency produced significant changes in the foam bubble size and foam homogeneity. Under certain conditions, foam exhibited a smaller bubble size and a narrower bubble-size distribution. Such enhanced homogeneity in texture is highly desirable to reduce the presence of aesthetically unattractive large cavities and to reduce the destabilizing effects of coarsening or Ostwald ripening, i.e., the growth of large gas bubbles at the expense of smaller ones due to gas diffusion driven by the higher Laplace pressure of the gas in the smaller cells. This enhanced stability was reflected in a slower rate of foam collapse and, hence, a longer foam lifetime. These effects are demonstrated for foams with a wide range of formulations. 1. Introduction Recent years have seen a considerable rise in the application of high-intensity ultrasound (16 kHz e frequency e 100 kHz) in the processing of a variety of biological and nonbiological materials, with a range of processing methods having been found to benefit from sonication.1 The major effects of high-intensity ultrasound are usually attributed to cavitation, i.e., the rapid growth and explosive collapse (implosion) of microscopic bubbles as the alternate compression and rarefaction of the sound waves pass through the liquid. Depending on the liquid and conditions used, these bubbles are usually on the order of 100-200 µm in diameter with a lifetime of microseconds. Their individual collapse can produce high shear gradients and shock waves accompanied by the generation of very high local temperatures (∼5000 °C), pressures (∼500 atm), and electric fields,2 while the bulk liquid remains at nearly ambient conditions. Liquid microjets are produced through the collapsing bubbles, which travel at a velocity on the order of ∼500 ms-1, and if they impinge on a boundary, they can seriously affect its surface morphology. Such liquid microjets can also set any suspended particles into motion.3 In particular, the effects of power ultrasound on the structure and dynamics of particles have received considerable attention over the past decade or so. Some studies on suspended metallic particles have shown that by sonication the particles can be forced into such violent collisions (collision speed ∼ 500 ms-1) that fusion occurs because of the very high local temperatures generated (∼3000 °C). Chemical reaction between the colliding powders can also ensue in some cases. For example, when copper and sulfur are sonicated together * To whom correspondence should be addressed. Tel.: +44 (0)121 414 5277. Fax: +44 (0)121 414 5324. E-mail: [email protected].

in hexane for 1 h, 65% Cu2S is generated.4 In other instances, particle aggregation was achieved, such as in the sonication of copper, TaS2, and MoO3 powders.5 Sonication of polymer particles suspended in water (e.g., polyethylene and polypropylene), on the other hand, showed that either agglomeration or fragmentation can occur depending on the type of polymer and its physical properties. Considerable surface roughening also occurs and could be exploited in enhancing chemical reactions at polymer particle surfaces.3 Other studies have shown that application of highintensity ultrasound to crystallization processes can generate significant reductions in the crystal size without adversely affecting the crystal structure. Nucleation and growth rates can be enhanced substantially, whereas the induction time and crystal size distribution can be markedly reduced. It also seems that ultrasound can reduce agglomeration and improve product handling.6,7 Thus, ultrasound may be used to control the crystal properties and/or to avoid seeding of solutions. There have also been reports that high-intensity ultrasound has the potential of providing an efficient method of emulsification.8-10 Emulsions generated with ultrasound have been produced in relation to the textile, cosmetic, pharmaceutical, and food industries but mainly in the batch mode on a laboratory scale. Such emulsions are said to often exhibit a better stability than those produced by conventional mechanical means such as rotor-stator systems and high-pressure homogenizers. They often require little or no surfactant and display a narrower droplet size distribution and a smaller mean droplet size. Again, ultrasound cavitation has been identified as the phenomenon behind the enhanced emulsification process. Small bubbles collapsing near the phase boundary of two immiscible liquids give rise to shock waves and high-velocity microjets, which are thought to be responsible for the mixing of the liquid layers. However, the exact mechanisms of droplet

10.1021/ie0491950 CCC: $30.25 © 2005 American Chemical Society Published on Web 03/10/2005

Ind. Eng. Chem. Res., Vol. 44, No. 9, 2005 3313 Table 1. Foaming Systems Used

surfactant SDS SDS SDS SDS SDS SDS SDS SDS SDS SDS SDS SDS SDS SDS WPC WPC WPC

surfactant concn wt % cmc 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.24 0.24 0.24 0.24 0.24 0.24 0.24 1.00 1.50 2.00

0.5 0.5 0.5 0.5 0.5 0.5 0.5 1.0 1.0 1.0 1.0 1.0 1.0 1.0

stabilizer type

concn

glycerol glycerol PEO PEO XG XG

20% (v/v) 50% (v/v) 0.1 wt % 0.5 wt % 0.025 wt % 0.050 wt %

glycerol glycerol PEO PEO XG XG CMC CMC CMC

20% (v/v) 50% (v/v) 0.1 wt % 0.5 wt % 0.025 wt % 0.050 wt % 0.20 wt % 0.20 wt % 0.20 wt %

formation and disruption and the role of the various process parameters are not well understood. Gas-liquid foams bear an intrinsic similarity to emulsions because of their colloidal nature and represent an important class of highly structured fluids. Intuitively, one would then presume that ultrasound would have similar effects on foams as it has on emulsions and other particulate systems. Previous work on gas-liquid foams dealt with the use of high-intensity ultrasound to control unwanted foaming. A few studies emerged that demonstrated the effectiveness of highintensity ultrasound in destabilizing unwanted foams, both static and dynamic.11,12 The ability to suppress dynamic foams would be particularly desirable in processes that require continuous defoaming such as bioreactors. The technique, being noninvasive, would have a crucial advantage over other chemical and mechanical methods in processes where contamination cannot be tolerated. However, from some studies related to wastewater treatment, there is some evidence that ultrasound can inactivate microorganisms,13 which might limit the application of the technique in certain cases. The use of ultrasound to positively influence the structure of designer foams during formation does not seem to have been studied before, however. Designer foams find wide applications in many industries including food, cosmetics, personal care, and pharmaceutical, which are increasingly concerned with the production of materials with complex cellular structures. In addition to the association with high quality, bubbles also offer attractive aesthetics, as well as great possibilities for novel structures and textures. For a foam, texture, rheology, stability, and shelf life are important attributes because they affect consumer perception of the quality of any foam-based product, as well as being closely linked to value generation. For example, foam structures in food products such as ice cream, mousses, and confectioneries offer many benefits including improved product volumes and, thus, a reduction in the product density, improvements in the rheology and textural quality and, thus, the taste and mouthfeel of the product, increased surface area, alteration of digestibility and shelf life due to increased porosity, and modulated flavor intensity. This is not unique to food foams but is equally valid for many other foam-based products such as cosmetics and personal care products. One way of controlling these features is

static surface tension (mN m-1)

Newtonian or apparent viscosity (mPa s)

49.6 49.4 52.7 39.7 37.0 48.0 46.5 37.3 37.9 44.0 39.7 38.7 37.3 36.7 61.1 58.6 57.7

1.15 1.96 6.99 1.43 2.97 η ) 0.002γ˘ -0.05 η ) 0.011γ˘ -0.22 1.09 1.93 7.40 1.75 3.21 η ) 0.003γ˘ -0.08 η ) 0.011γ˘ -0.24 3.59 3.45 3.41

through formulation design. However, the foam generation process itself is crucial in achieving foam products with enhanced quality and stability. For example, the generation of foam with a uniform texture is usually too difficult under normal circumstances, and it would thus be of great industrial benefit to develop processing methods that can assist in the generation of foams with controlled structures. We recently reported preliminary findings on some of the effects that the use of high-intensity ultrasound can have on the structure of pneumatically generated foam.14 That study used a simple setup, whereby foam was generated by sparging gas into a cylindrical glass column immersed in a standard ultrasound bath (Grant XB-22 model), which operated at a fixed frequency of 38 kHz and delivered a total constant but not spatially uniform ultrasound power of average density 0.011 W cm-3 (rms value 238 W and peak value 475 W, as quoted by the manufacturer). This represents the total electrical power supplied to the ultrasound transducers in the bath. Here, we report the results from a more detailed investigation that uses a probe-type ultrasound source with a fixed frequency but adjustable power input to influence foam structure at the point of generation. The effects of ultrasound power are studied using a wide range of aqueous and viscous foaming systems stabilized with detergent-type or protein surfactants. 2. Materials and Methods 2.1. Foaming Systems. Two different surfactants were used: an anionic detergent-type surfactant, sodium dodecyl sulfate (SDS), and a protein surfactant, whey protein concentrate (WPC). The foaming systems studied and their physical properties are summarized in Table 1. The surfactants were dissolved in distilled water at different concentrations, as shown in Table 1. The surfactant concentration is also expressed in cmc, where cmc is the critical micelle concentration of the particular surfactant in pure water, corresponding to the minimum static surface tension of the mixture. Several stabilizers [glycerol, xanthan gum (XG), poly(ethylene oxide) (PEO), and carboxymethylcellulose (CMC)] were added at different concentrations to alter the viscosity of the surfactant solutions and aid the stability of the foams. Most of the foaming solutions had a Newtonian rheology, but some solutions exhibited a non-Newtonian shear-thinning behavior and were well

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Figure 1. Foam generation setup: (1) rotameter; (2) control valve; (3) gas sparger; (4) sonicator; (5) ultrasound probe; (6) surfactant solution; (7) foam; (8) camera. Table 2. Ultrasound Power Settings ultrasound amplitude % mm 20 30 40 50 60 70 80

0.025 0.037 0.049 0.063 0.074 0.086 0.098

ultrasound power (W)

ultrasound intensity (W cm-2)

ultrasound density (W cm-3)

5 18 31 45 61 75 87

0.99 3.55 6.12 8.88 12.04 14.80 17.17

0.007 0.024 0.041 0.060 0.081 0.100 0.116

represented by a two-parameter power law model (τ ) λγ˘ x). Table 1 shows either the Newtonian viscosity of the solution or the relationship for its apparent viscosity, as given by the power law model. 2.2. Foam Generation and Ultrasound Irradiation. Foam was generated pneumatically by sparging of nitrogen gas at a fixed rate of 0.35 L min-1, through a sintered glass sparger of porosity 100-160 µm, inside a square section Perspex column of dimensions 100 × 100 mm, as shown in Figure 1. The volume of the foaming solution used was 750 cm3. Ultrasound irradiation was achieved by using a probe-type ultrasound processor (Autotune-Series 750W model, Sonics & Materials). An ultrasound probe of 25.4-mm (1.0-in.) diameter was positioned near the foam generator, as shown in Figure 1, and emitted ultrasound waves at a fixed frequency of 20 kHz. The intensity of the ultrasound field was varied by varying the amplitude of acoustic waves within the range 20-80%, i.e., 0.0250.098 mm. The total ultrasound power, measured in terms of the electrical power delivered to the probe, was displayed by the instrument. The corresponding values of the ultrasound power settings were in the range 0.99-17.17 W cm-2, as shown in Table 2. Because high-intensity ultrasound is known to produce microbubbles in liquids via the process of cavitation, it was important to check whether this phenomenon contributed to the foaming process, i.e., whether any cavitation bubbles were causing additional generation of foam to that produced by the nitrogen gas injected. A test was conducted whereby ultrasound was applied to the surfactant solution in the column with the nitrogen gas supply switched off. The test was carried out repeatedly over extended periods of time,

exceeding those used for the normal foaming experiments described above, but no foaming was observed. Therefore, it could be safely assumed that, under the range of conditions investigated, any ultrasound effects on the pneumatically generated foams could not have arisen, wholly or partly, from possible foaming caused by cavitation. 2.3. Foam Bubble-Size Distribution. The bubblesize distribution was determined by photographing the foam through the transparent flat column wall using a digital camera. Photographs were taken using fiberoptic backlighting, at a position approximately 20 mm above the liquid surface. This measure was adopted to ensure that only freshly generated foam was photographed, thus capturing any ultrasound effects on the foam structure at the earliest stage possible before any foam aging effects (drainage and coarsening) set in. The digital images were subsequently analyzed using Q-Win-Pro Leica software. 2.4. Foam Stability. The effect of using ultrasound on the stability of the foams generated was assessed by measuring their rate of collapse and comparing it to that of foams obtained from the same foaming system in the absence of ultrasound. In this experiment, a foam bed of height H0 ) 250 mm was generated, the gas flow and ultrasound processor (when used) were then immediately switched off, and foam collapse was measured by monitoring the decline in the foam height with time. The duration of the experiment depended on the nature of the foam and its stability and varied from minutes to hours. Foam stabilities were compared using the halflifetime, t1/2, of the foam, which is defined as the time required for the foam to collapse to half of its original height. 3. Results and Discussion 3.1. Descriptive Statistics. A number of statistical parameters were used to describe the results obtained from the analysis of the foam images, and these parameters are defined in the Appendix. An analysis of variance (ANOVA) was performed, using Minitab statistical software, to test the significance of the difference in the bubble size caused by varying the ultrasound amplitude or power. ANOVA is a statistical assessment of sample data to decide if differences exist between various groups of data. The null hypothesis of ANOVA is that the means of different groups of data are the same; i.e., in this case, the d10 values of the different foams generated with or without the assistance of ultrasound are the same. ANOVA yields two important parameters, the F-statistic value as well as the P value. A high F-statistic value represents a large difference between the means of the samples, while the P value is a measure of the significance of the F value. The default value of P is taken as 0.005 (i.e., 99.5% confidence level), so that if the P value is lower than 0.005, the probability of making an error by rejecting the null hypothesis is small; i.e., the null hypothesis that the means of all of the groups of data are the same has to be rejected. In this study, ANOVA was performed twice for each foaming system to compare a sample of foam generated without the assistance of ultrasound to samples of foams formed at different ultrasound amplitudes, with these samples being (i) combined together and (ii) considered individually. The change in averages for these data groups is established using an assumed ratio of variance

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Figure 4. Effect of ultrasound on the foam bubble-size distribution: SDS, 0.5 cmc (0.12 wt %); 2, A ) 0; 0, A ) 40%; ×, A ) 80%. Figure 2. Effect of the sample size on foam bubble parameters: SDS, 1.0 cmc (0.24 wt %); glycerol, 50% (v/v); 9, d10; 2, d32; +, σ.

Figure 5. Effect of ultrasound on the foam bubble-size distribution: SDS, 0.5 cmc (0.12 wt %); PEO, 0.5 wt %; 2, A ) 0; 0, A ) 40%; ×, A ) 80%. Figure 3. Effect of the sample size on the bubble-size distribution: SDS, 1.0 cmc (0.24 wt %); glycerol, 50% (v/v); +, 50 bubbles; ×, 200 bubbles; 9, 400 bubbles; 2, 600 bubbles; O, 800 bubbles.

between the different groups, compared to the expected variance within the groups. Finally, a fundamental parameter that affects the reliability of any statistical measurement is the sample size, which must be large enough to avoid statistical bias. To determine the minimum number of bubbles required for statistical analysis of the foam images, samples of 30, 50, 100, 150, 200, 400, 600, and 800 were tested. The results plotted in Figure 2 show the main parameters of the bubble-size distribution, i.e., d10, d32, and σ, which remain unaffected when a sample of 200 bubbles or more is used. The bubble-size-distribution curves obtained from samples of 200 bubbles or more also clearly coincide, as shown in Figure 3. Some statistical bias can be expected from smaller samples. Therefore, a sample size of 200 bubbles was deemed sufficient to avoid statistical bias when determining the foam bubble-size distribution in a given experiment. 3.2. SDS Foams. Different effects were generated in the SDS foams by the application of high-intensity

ultrasound waves depending on the surfactant concentration used. Two SDS concentrations were tested, 0.12 and 0.24 wt % corresponding to 0.5 and 1.0 cmc, respectively. 3.2.1. Low-SDS-Concentration Foams. These foams, containing 0.5 cmc of SDS, incurred a significant reduction in their mean bubble sizes, i.e., a reduction in the number mean bubble diameter, d10, and the Sauter bubble diameter, d32, under all conditions investigated, resulting in the generation of a finer foam texture. The largest reduction in the bubble size was observed in aqueous SDS foams as well as foams containing 0.5 wt % PEO or 0.025 wt % XG. The largest reductions in d10 and d32 were achieved at an ultrasound amplitude of 40% (0.049 mm and 0.041 W cm-3) for aqueous SDS foams. In general, however, the effects were less pronounced for the more viscous liquids. This is expected because of the higher dissipation of ultrasound energy in these viscous systems, which would probably require a greater ultrasonic power to achieve the same reductions in bubble size. Typical bubble-size distributions for these foaming systems are shown in Figures 4 and 5, while the statistical data for all experiments are summarized in Table 3.

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Table 3. Statistical Parameters for the Foam Bubble-Size Distributions of Low SDS Concentration A (%) SDS (0.5 cmc) + PEO (0.5 wt %)

SDS (0.5 cmc) d10 (mm) d32 (mm) σ (mm) Cv M S K F P Foverall Poverall

0

20

40

0.74 0.79 0.14 0.19 0.72 1.40 5.13

0.64 0.67 0.10 0.16 0.62 0.92 1.48 71.61 ,0.001

0.57 0.60 0.09 0.15 0.57 0.27 -0.12 203.27 ,0.001 66.12 ,0.001

80

0

30

0.64 0.70 0.14 0.21 0.61 1.24 1.71 52.20 ,0.001

0.71 0.76 0.13 0.18 0.70 1.33 5.15

0.63 0.67 0.11 0.17 0.62 0.37 -0.11 42.7 ,0.001

There is a clear shift in the bubble-size distribution produced under sonication toward the lower end of the bubble-size spectrum. This is accompanied by a considerable narrowing of the bubble-size distribution, which shows a significant enhancement in the uniformity of the foam texture. This observation is supported by the pertinent statistics, i.e., a reduction in the coefficient of variation Cv, as shown in Table 3. Skewness, S, is also considerably reduced because of the elimination of the larger bubbles in the tail, as is kurtosis, K; i.e., the bubble-size distribution is much closer to the bell-shaped normal distribution with a greater clustering around the mean. As was already pointed out, the generation of foam with a uniform bubble size is extremely difficult under normal circumstances. Enhanced homogeneity in texture is highly desirable to reduce the number of aesthetically undesirable large cavities and to enhance the foam stability by reducing the destabilizing effects of coarsening or Ostwald ripening, i.e., the growth of large gas bubbles at the expense of smaller ones, because of gas diffusion driven by the higher Laplace pressure in the small cells. The improvements in the foam structure start to get reversed when the ultrasound amplitude is increased beyond about 60%, however, leading to some deterioration in foam homogeneity compared to what is achieved at lower amplitudes because of the formation of some large bubbles, as demonstrated by the 80% amplitude curves (Figures 4 and 5). The coefficients of variation, kurtosis, and skewness increase at 80% amplitude, above the values achieved at 40% amplitude; i.e., the bubble-size distribution at high ultrasound amplitudes becomes less normal in shape and more positively skewed than that at low ultrasound amplitudes. However, the foam texture is still finer and more homogeneous than that without the application of ultrasound. Foam generated in the absence of ultrasound was wet with approximately spherical bubbles separated by relatively thick liquid films, and the gas volume fraction was about 0.80. The application of ultrasound during foam generation was found to reduce the gas volume fraction slightly down to ∼0.76 at 40% amplitude; i.e., the foam produced was slightly wetter. Further increments in ultrasound amplitude up to 80%, however, increased the gas volume fraction back to ∼0.81. Therefore, under the conditions investigated here, ultrasound did not appear to have a considerable influence on the foam gas holdup. The F-statistic values as well as P values yielded by the ANOVA analysis are listed in Table 3. The overall F values are large, and the overall P values are less than the default value of 0.005. This shows that, considering

40 0.62 0.65 0.11 0.17 0.60 0.67 0.33 65.49 ,0.001 29.06 ,0.001

SDS (0.5 cmc) + XG (0.025 wt %)

80

0

20

0.63 0.69 0.13 0.21 0.61 1.34 3.46 39.05 ,0.001

0.65 0.70 0.13 0.20 0.66 0.80 4.30

0.62 0.64 0.07 0.11 0.62 0.15 0.52 8.85 ,0.001

40 0.59 0.64 0.12 0.20 0.57 0.59 0.34 27.47 ,0.001 12.68 ,0.001

80 0.60 0.66 0.14 0.23 0.58 1.21 1.63 18.11 ,0.001

all of the foam samples together, the use of ultrasound to assist with the foam generation process does have a significant effect on the foam bubble size. Taking each sample of ultrasound-processed foam individually, all individual F values are also high and corresponding P values are ,0.001 for each of the ultrasound amplitudes used. This confirms that each ultrasound amplitude used has a significant effect on the foam bubble size. As was already pointed out previously, a homogeneous foam texture is highly desirable from both an appearance point of view and a stability standpoint. Better cell size uniformity reduces foam coarsening, which is caused by gas diffusion from smaller cells to larger ones because of the higher Laplace pressure in the smaller cells. Cell growth ultimately leads to foam structure breakdown. The stability of foams generated in the presence of ultrasound was measured and compared to that of foams generated in the absence of ultrasound. Figure 6 shows the collapse curves of foams containing 0.5 cmc of SDS. It can be seen that foams produced under sonication appear to collapse more slowly than the native foam; the half-lifetime of the foam, t1/2, increased from 35 to 53 min when the ultrasound amplitude was raised from 0 to 80%. 3.2.2. High-SDS-Concentration Foams. In general, for these systems that contained 1.0 cmc of SDS, the application of ultrasound did not have much effect on the mean foam bubble size at low ultrasound amplitudes, with the reduction in d10 and d32 being small, as shown in Table 4. Interestingly, at higher amplitudes, however, the use of ultrasound yielded foams with somewhat larger bubble sizes compared to foams generated in the absence of ultrasound (see Table 4). This

Figure 6. Foam collapse curves: SDS, 0.5 cmc (0.12 wt %); 2, A ) 0; +, A ) 20%; 0, A ) 40%; ×, A ) 80%.

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Figure 7. Foam images: SDS, 1.0 cmc (0.24 wt %); glycerol, 20% (v/v). (a) A ) 0; (b) A ) 70%. Table 4. Statistical Parameters for the Foam Bubble-Size Distributions of High SDS Concentration A (%) SDS (1.0 cmc) + glycerol (20% (v/v))

SDS (1.0 cmc) d10 (mm) d32 (mm) σ (mm) Cv M S K F P Foverall Poverall

0

20

0.59 0.62 0.09 0.16 0.58 0.19 0.18

0.57 0.60 0.09 0.16 0.56 0.69 0.94 3.57 0.060

40 0.57 0.61 0.10 0.18 0.55 0.91 0.70 3.25 0.072 9.28 ,0.001

80

0

0.61 0.66 0.11 0.18 0.59 1.39 3.37 7.36 0.007

0.57 0.61 0.10 0.18 0.58 -0.05 1.06

20

40

0.56 0.56 0.59 0.60 0.10 0.11 0.19 0.19 0.54 0.55 0.23 0.25 -0.30 0.98 2.47 2.11 0.117 0.147 62.54 ,0.001

effect is well demonstrated by the foam images shown in Figure 7 for a solution containing added glycerol at 20% (v/v); in this case, d10 increased by 25% and d32 increased by 30%. Moreover, the foams generated exhibited much more variation in the cell size, as is clearly apparent from the images in Figure 7 and the corresponding bubble-size distributions represented in Figure 8. Thus, for these systems, the application of ultrasound reduced the foam homogeneity at high amplitudes; in particular, considerable increases resulted in positive skewness and kurtosis, thus leading to less symmetry and less normality in the bubble-size distributions (see Table 4). Under no ultrasound, high-SDS-concentration foams were somewhat wetter than low-SDS-concentration

Figure 8. Effect of ultrasound on the foam bubble-size distribution: SDS, 1.0 cmc (0.24 wt %); glycerol, 20% (v/v); 2, A ) 0; 0, A ) 40%; ×, A ) 70%.

SDS (1.0 cmc) + XG (0.025 wt %)

70

0

20

0.71 0.79 0.16 0.23 0.65 1.18 0.90 101.99 ,0.001

0.54 0.56 0.07 0.13 0.54 0.01 0.01

0.54 0.57 0.09 0.17 0.54 0.40 -0.29 0.07 0.785

40 0.56 0.60 0.11 0.19 0.55 0.73 6.86 5.25 0.022 14.29 ,0.001

80 0.60 0.68 0.15 0.24 0.58 1.30 2.89 29.22 ,0.001

foams, with a gas volume fraction of ∼0.75 compared to ∼0.80. The application of ultrasound, however, increased the gas holdup of these foams to ∼0.83 at 80% amplitude. The overall F-statistic values yielded by the ANOVA analysis, considering all foam samples collectively, are high, while the P values are all less than 0.005, suggesting that the ultrasound effects observed on the whole are true and significant. However, the effects at high amplitudes might have dominated to give large overall F values because ultrasound seems to have little effect on the mean bubble size at low amplitudes. In this case, one should look at the individual F and P values obtained for each ultrasound amplitude compared with the case of no ultrasound being used. Indeed, the individual F values listed in Table 4 at low ultrasound amplitudes (e40%) are generally low, with P values greater than the default value of 0.005. Therefore, we cannot reject the null hypothesis at these amplitudes; i.e., the effects are not statistically significant and, hence, there is no real evidence that this level of ultrasound affects the foam bubble size. On the other hand, foams generated at high ultrasound amplitudes (>40%) have high F values, and P values which are ,0.001. This suggests that the effects observed on the foam bubble size in these more concentrated SDS systems, when using relatively high levels of ultrasonic power, are statistically different. The use of two different SDS concentrations, one low and one high, led to different ultrasound effects on the foam bubble size and texture uniformity. This discrepancy in behavior may be attributed to the differences in the interfacial properties of the two systems, i.e., static as well as dynamic surface tension. Such inter-

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Figure 9. Foam images: WPC, 1.0 wt %; CMC, 0.2 wt %. (a) A ) 0; (b) A ) 70%.

bubble size was approximately halved at an ultrasound amplitude of 70% (0.086 mm and 0.100 W cm-3), as demonstrated by the images in Figure 9. The foam was found to be slightly wetter at this ultrasound amplitude, with the gas volume fraction being ∼0.82 compared to ∼0.86 for foam generated without ultrasound. There is a substantial shift in the bubble distribution toward smaller diameters, as shown in Figure 10, accompanied by a considerable narrowing of the distribution. The statistical analysis of the results is summarized in Table 5. When the WPC concentration was increased to 1.5 and 2.0 wt %, significant changes in the foam texture (reduction in the bubble size and better uniformity) required higher ultrasound amplitudes above 60%. This is in sharp contrast to the low-SDS-concentration foams, which acquired their finest textures at lower amplitudes. An increase in the ultrasound amplitude also reduced the collapse rate of the protein foam and lengthened its lifetime considerably, as shown in Figure 11. The foam half-lifetime, t1/2, increased significantly to 9 min at an ultrasound amplitude of 80% compared to 3.5 min when the foam was generated without ultrasound assistance. It is noteworthy that, although the same foam generator was used, the form of the bubble-size distribution of the WPC foams was different from that of the SDS foams, being generally much wider and characterized by more peaks. A good fit was obtained by the normal distribution for the protein foams, while the SDS foams were all well described by a log-normal distribution. This phenomenon may be attributed to the differences in the molecular structures of SDS and WPC and their

Figure 10. Effect of ultrasound on the foam bubble-size distribution: WPC, 1.0 wt %; CMC, 0.2 wt %; 2, A ) 0; ×, A ) 70%.

facial phenomena would be expected to affect the formation of bubbles as they emerge from the porous gas sparger, as well as their interaction with each other and with the ultrasound waves, thus leading to foams with different textural characteristics. Such phenomena cannot be explained without further, more detailed work on the interfacial properties of these systems, probably combined with a study of the fundamental behavior of single bubbles in an ultrasound field to shed light on the complex interactions that may occur during foam formation. 3.3. WPC Foams. The effects of ultrasound on WPC foams were striking. Ultrasound-assisted generation of foam from protein systems containing 1.0 wt % WPC yielded foams with a much finer texture. The mean

Table 5. Statistical Parameters for the Foam Bubble-Size Distributions of WPC Systems A (%) WPC (1.0 wt %) + CMC (0.2 wt %) d10 (mm) d32 (mm) σ (mm) Cv M S K F P Foverall Poverall

0

20

1.63 1.88 0.47 0.29 1.63 0.18 0.05

1.11 1.28 0.31 0.28 1.05 0.55 -0.29 85.15 ,0.001

40 1.10 1.31 0.35 0.32 1.08 0.14 -0.81 81.43 ,0.001 64.86 ,0.001

WPC (1.5 wt %) + CMC (0.2 wt %)

70

0

20

0.94 1.06 0.25 0.27 0.93 0.11 -0.86 138.85 ,0.001

0.93 1.03 0.22 0.24 0.94 0.27 0.20

0.88 0.97 0.20 0.23 0.87 0.21 -0.60 2.86 0.092

40 0.87 0.98 0.22 0.26 0.84 0.61 0.27 3.66 0.057 23.18 ,0.001

WPC (2.0 wt %) + CMC (0.2 wt %)

80

0

20

0.70 0.80 0.18 0.26 0.66 0.88 0.87 64.8 ,0.001

0.86 0.90 0.18 0.21 0.82 0.44 0.93

0.83 0.92 0.20 0.25 0.81 0.39 -0.32 1.40 0.237

40 0.87 0.99 0.23 0.26 0.85 0.63 0.24 0.26 0.614 23.36 ,0.001

80 0.67 0.73 0.14 0.21 0.64 0.92 0.84 65.12 ,0.001

Ind. Eng. Chem. Res., Vol. 44, No. 9, 2005 3319

Figure 11. Typical foam collapse curves: WPC, 1.0 wt %; CMC, 0.2 wt %; 2, A ) 0; [, A ) 20%; 0, A ) 40%; ×, A ) 80%.

behavior at the film interfaces. It is well-known that detergent surfactants and proteins are characterized by different mechanisms of film stabilization. Detergents generally have small molecules that can rapidly diffuse to a newly generated surface, where they adsorb but cannot undergo a conformational change to enhance their surface activity and binding and, therefore, can only act as discrete molecules. On the other hand, protein molecules are larger, diffuse more slowly, and upon adsorption at an interface tend to undergo major structural rearrangements. Interaction between neighboring molecules causes the formation of a highly cohesive surface layer similar to a rubber sheet.15,16 Protein-stabilized films rely on the viscoelastic properties of this superficial “skin” to dissipate any local film stretching, and this mechanism relies on the immobilization of the molecules at the surface. This may explain the fact that protein films require higher ultrasound amplitudes to break and, thus, generate smaller bubbles.

SDS foams, an increase in the WPC concentration requires a higher ultrasonic power to achieve similar textural effects. More detailed work is needed to explain the phenomena that underlie the ultrasound effects observed before the use of the technique can be optimized. In particular, the results discussed here were all obtained at one frequency (20 kHz), which is at the lower end of the ultrasound spectrum. It seems plausible that much higher frequencies may have a greater impact on the foam structure, and these need to be investigated up to the megahertz range and probably beyond. More fundamental work on how bubble mechanics are affected by ultrasound waves may shed light on the mechanisms that drive the transformations in the foam structure. On the basis of the results obtained, it seems conceivable that ultrasound may offer a technique for controlling the foam texture by affecting the initial bubble formation and/or by affecting bubble coalescence. If fully proven, the results should eventually advance the scientific ability within the industry to produce foambased products with improved structures and stability. Appendix The statistical parameters used to describe the results obtained from the analysis of the foam images are defined in the following, where di is the equivalent circular diameter of an individual bubble i and n is the number of bubbles in the sample:

(i) Number mean bubble diameter, d10: n

di ∑ i)1

d10 )

n

(1)

(ii) Sauter mean bubble diameter, d32: n

4. Conclusions The results presented have demonstrated the effects that high-intensity ultrasound can have on foams generated pneumatically in a wide range of aqueous and viscous systems containing either a detergent-type surfactant or a protein surfactant. The nature and extent of the effects observed are a function of the formulation of the foam and the ultrasonic power used. In general, for low- SDS-concentration foams, foam exhibits a significantly smaller bubble size and narrower bubble-size distribution when ultrasound is applied at the point of foam generation. Such enhanced homogeneity in texture is highly desirable to reduce the presence of aesthetically unattractive large cavities and to enhance the foam stability by reducing the destabilizing effects of coarsening. Foams generated under such conditions are characterized by a slower rate of foam collapse and, hence, a longer lifetime. At a fixed ultrasound frequency, there seems to be an optimum point beyond which a higher ultrasonic power does not necessarily result in a finer foam or better texture homogeneity. In more concentrated SDS systems, the effects are small at low ultrasonic powers, and as the ultrasound power is increased, a deterioration in the bubble-size distribution is observed. Protein-stabilized foams, however, acquire a much finer and more uniform texture under the action of ultrasound waves. In contrast to

d32 )

di3 ∑ i)1 n

(2)

di2 ∑ i)1 While d10 gives the average bubble size, d32 is considered to be a better representative of the mean bubble diameter because it is directly related to the ratio of gas holdup and interfacial area in the foam.

(iii) Standard deviation, σ:

σ)

x

n

(di - d10)2 ∑ i)1 n-1

(3)

(iv) Coefficient of variation, Cv: Cv ) σ/d10

(4)

This coefficient gives a measure of the spread of the distribution relative to its mean.

(v) Median, M

3320

Ind. Eng. Chem. Res., Vol. 44, No. 9, 2005

This is the middle number in the data set when the data points are arranged from low to high. It is worth recalling that, for a normal distribution, the median and the mean coincide, i.e., M ) d10.

(vi) Skewness, S: S)

∑(

)

di - d10 σ

n (n - 1)(n - 2)

3

K)

[

n(n + 1) (n - 1)(n - 2)(n - 3)

(

∑

)]

di - d10 σ

4

cmc ) critical micelle concentration CMC ) carboxymethylcellulose PEO ) poly(ethylene oxide) SDS ) sodium dodecyl sulfate XG ) xanthan gum WPC ) whey protein concentrate

(5)

This parameter gives a measure of the asymmetry of the distribution. The direction of skewness is to the tail, and the larger the number, the longer the tail. If S is positive, skewness is to the right because the tail on the right-hand side of the distribution will be longer and vice versa. For a normal distribution, S ) 0.

(vii) Kurtosis, K:

Abbreviations

-

3(n - 1)2 (6) (n - 2)(n - 3)

This is a measure of the combined weight of the tails in relation to the rest of the distribution. As the tails of a distribution become heavier, K increases. As the tails become lighter, K decreases. A histogram with a normal distribution has K ) 0. If the distribution is peaked (tall and skinny), K is positive, and the distribution is said to be leptokurtic. If the distribution is flat, K is negative, and the distribution is said to be platykurtic. Nomenclature A ) ultrasound amplitude Cv ) coefficient of variation di ) equivalent circular diameter of individual bubble i d10 ) number mean bubble diameter d32 ) Sauter mean bubble diameter H ) foam height H0 ) initial foam height K ) kurtosis M ) median n ) number of bubbles in a sample S ) skewness x ) flow behavior index t1/2 ) foam half-lifetime

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Greek Letters γ˘ ) shear rate λ ) consistency index η ) apparent viscosity σ ) standard deviation τ ) shear stress

Received for review August 31, 2004 Revised manuscript received January 28, 2005 Accepted February 2, 2005 IE0491950