- Email: [email protected]
Rheological and electrokinetic behavior associated with concentrated nanosize silica hydrosols
Materials Chemistry and Physics 91 (2005) 205–211
Rheological and electrokinetic behavior associated with concentrated nanosize silica hydrosols Ungyu Paika,∗ , Jang Yul Kima , Vincent A. Hackleyb a b
Department of Ceramic Engineering, Hanyang University, 17 Haengdang-dong, Seongdong-ku, Seoul 133-791, Republic of Korea Material Science and Engineering Laboratory, National Institute of Standards and Technology, Gaithersburg, MD 20899-8520, USA Received 21 July 2004; received in revised form 2 November 2004; accepted 15 November 2004
Abstract The influence of solids loading and the electrical double layer on the rheological behavior of concentrated silica nanosols was investigated. In this study, silica suspensions were characterized by viscosity, electrokinetic sonic amplitude measurements, and by theoretical considerations. Despite a high electrokinetic potential at pH 8, fumed silica not only exhibits rheological behavior normally indicative of an unstable suspension, but the rheology does not have the expected DLVO dependence on ionic strength. Normalization of viscosity to an effective volume fraction that incorporates the influence of the electrical double layer, leads to partially superimposable curves. The positive correlation between zeta potential and viscosity indicates that classical DLVO calculations alone are insufficient to predict the rheological behavior of concentrated silica nanosols, without first taking into account the effects of particle crowding and the repulsive interactions on suspension structure. The relatively low magnitude of van der Waals attractive forces between silica particles in water also plays an important role at high electrolyte concentrations. A comparison is made between silica nanosols and silica microspheres, and also between nano-silica and nano-alumina. © 2004 Published by Elsevier B.V. Keywords: Ceramics; Oxides; Surface properties
1. Introduction Nanosize inorganic particles (i.e., below 100 nm) are gradually being incorporated into a broad range of advanced devices and applications; some examples include electronic packages, ultra-thin-film optical devices, advanced fuel cell catalysts, molecular conductors, and biochips [1–7]. In most cases, the nanoparticle component is incorporated or utilized via a liquid suspension. Classical colloid science is generally used to both describe and predict the properties and behavior of so-called nanosols, in which the dispersed phase has dimensions in the nanoscale regime. Recent evidence [8] has indicated that classical colloid principles might not fully explain the complex behavior of concentrated nanosols. Thus difficulties can be anticipated in the course of research, development and production of devices based on nanosol technology. ∗
Corresponding author. Tel.: +82 2 2290 0502; fax: +82 2 2281 0502. E-mail address: [email protected] (U. Paik).
0254-0584/$ – see front matter © 2004 Published by Elsevier B.V. doi:10.1016/j.matchemphys.2004.11.011
According to Derjaguin–Landau–Verwey–Overbeek (DLVO) theory [9], a cornerstone of modern colloid science, two types of forces exist between colloidal particles suspended in a dielectric medium: (1) electrostatic forces, which result from unscreened surface charge on the particle, and (2) London–van der Waals attractive forces, which are universal in nature. The colloidal stability and rheology of oxide suspensions, in the absence of steric additives, can be largely understood by combining these two forces (i.e., assumption of additivity). However, the expressions of the electrical forces are derived from the Poisson–Boltzmann equation, which is based on two key approximations: (1) the solvent is considered as a structureless dielectric continuum and (2) the field generated by the ions is a mean field. There are several reports [10–12] of the unique stability of nanosize silica hydrosols near the isoelectric point (IEP). Mahanty and Ninham [13] discovered experimentally the existence of short-range forces that play an important role in the interaction process and which must be added to those
206
U. Paik et al. / Materials Chemistry and Physics 91 (2005) 205–211
forces already accounted for by the original DLVO theory. These short-range interactions are referred to as structural forces [14–16]. Structural forces might explain some particular aspects of the stability behavior of silica nanosols, but they are insufficient to account for the apparent cooperative effects of solids loading and electrostatics found in the present study. Contrary to suspensions based on colloidalsize (100–1000 nm) silica [17] and other inorganic oxides [18] as reported in the literature, we find that the rheological behavior of concentrated electrostatically stabilized silica nanosols is counterintuitive with regards to predictions based on a standard interpretation of DLVO theory. Despite a high electrokinetic potential at pH 8, fumed silica not only exhibits rheological behavior that would normally indicate an unstable or aggregated suspension (i.e., pseudoplastic-high viscosity), but the rheology does not have the expected dependence on ionic strength. In this study, experimental measurements, DLVO calculations, and simple geometric considerations are used to understand the influence of solids loading and the electrical double-layer on the rheological behavior of concentrated silica nanosols, and to compare their behavior with that of much larger silica microspheres, as well as like-sized nano-alumina, under similar conditions.
2. Experimental
2.2. Characterization techniques The electrokinetic behavior of silica suspensions at a volume fraction of 2% and a temperature of 25 ± 0.1 ◦ C were characterized using the electrokinetic sonic amplitude (ESA) technique (Acoustosizer II, Colloidal Dynamics, Sydney, Australia). The basic theory and application of ESA have been described in detail elsewhere [19–21]. For ESA measurements, two identical suspensions were prepared for each analysis. Separate acid (1.0 N HCl) and base (1.0 N NaOH) titrations were then performed beginning at the natural pH, and subsequently combined to generate a complete acid–base titration curve. Based on previous work, we estimate a measurement precision of ±1 mV for zeta potential. The rheological behavior of suspensions was measured using a controlled-stress rheometer (MCR300, Paar Physica, Stuttgart, Germany) with a concentric-cylinder tool geometry and an external temperature-controlled bath-circulator operating at 25 ± 0.1 ◦ C. To obtain the rheological behavior of suspensions at specific pH values (pH 3, 5, 7, 8, 9, 11, and 8 with added NaNO3 ), the suspensions were prepared for analysis in the manner previously described, but the pH was adjusted prior to ultrasonic treatment using HCl or NaOH. The shear rate was increased from 1 to 1000 s−1 , with a pause time of 30 s at each shear rate. Based on previous measurement data and experience, a reproducibility of ±10% can be expected for viscosity measurements performed under these conditions.
2.1. Preparation of suspensions Aerosil 90 fumed silica (designated A90) and aluminum oxide C (␥-alumina) were obtained from Degussa AG (Frankfurt am Main, Germany)1 . The specific surface area and average primary particle size, as provided by the manufacturer, was as follows: 90 ± 15 m2 g−1 and 20 nm for A90; 100 ± 15 m2 g−1 and 13 nm for ␥-alumina. Silica microspheres (designated Geltech) with a nominal median diameter of 500 nm were obtained from Geltech Inc. (Alachua, FL). The silica particles were dispersed in deionized water or NaNO3 solution. Each suspension was subjected to intense ultrasonic treatment for 5 min in order to break down aggregates. An ice bath was used to control the temperature of the suspension during ultrasonic treatment. To establish an equilibrium dispersion, the suspension was aged for 12 h at room temperature using a wrist-action shaker. Following aging, the suspension was ultrasonicated for an additional 5 min.
1 Certain trade names and company products are mentioned in the text or identified in illustrations in order to specify adequately the experimental procedure and equipment used. In no case does such identification imply recommendation or endorsement by National Institute of Standards and Technology, nor does it imply that the products are necessarily the best available for the purpose.
3. Results and discussion By changing the pH, one can alter the magnitude (and sign) of the zeta potential (ζ), while the addition of an inert electrolyte will affect both the magnitude of ζ and the electrical double-layer thickness. Thus, both pH and electrolyte concentration will directly impact colloidal stability in an electrostatically stabilized system. Fig. 1 compares ζ
Fig. 1. The relationship between zeta potential (open) and viscosity (filled) for silica suspensions as a function of suspension pH: nanosize A90 vs. Geltech microspheres (G). Viscosity was determined at a shear rate of 26.4 s−1 . Particle volume fraction given in %.
U. Paik et al. / Materials Chemistry and Physics 91 (2005) 205–211
207
Fig. 3. Diagram illustrating the relationship between average interparticle surface-to-surface separation distance, ds , and other system dimensions, for a particle diameter dp = 20 nm and Φ = 13.2%. Fig. 2. The effect of electrolyte concentration on the viscosity of 13.2% A90 silica at pH 8 as a function of shear rate.
and viscosity (at a shear rate of 26.4 s−1 ) as a function of pH for the A90 and Geltech suspensions. Even at a solid concentration of 20%, the Geltech microspheres exhibit a fairly constant and low viscosity across the entire pH range, whereas A90 exhibits a strong pH dependence at a volume fraction of 13.2%, with an increase in viscosity near pH 7 in excess of 300%. Fig. 2 shows the effect of inert electrolyte concentration on viscosity as a function of shear rate for highly charged 13.2% A90 at pH 8. Fig. 1 indicates that for Geltech microspheres, ζ and viscosity both follow the expected behavior predicted by classical DLVO theory. That is, as the pH moves away from the IEP, which is located near pH 2 for silica, ζ increases and viscosity decreases. However, A90 exhibits a discrepancy between the expectation of DLVO theory and the experimental results: as ζ, and by inference colloidal stability, of A90 increases, viscosity sharply increases. For suspensions, changes in viscosity are often assumed to reflect changes in the state of dispersion. With this assumption in mind, viscosity should exhibit a minimum (i.e., reflecting the least amount of aggregation) when ζ is at a maximum at constant ionic strength, or, similarly, at the lowest ionic strength when pH is held constant. Since A90 exhibits the reverse behavior, a deviation from DLVO appears to exist. However, the often-applied assumption that viscosity is a direct reflection of the state of aggregation (or, by inference, colloidal stability) is not strictly valid. Viscosity is a macroscopic property, and as such it will be influenced by any chemical or physical process that alters the structural or hydrodynamic conditions of the system. Hence, factors such as particle crowding, particle ordering and electroviscous effects will also impact viscosity, in addition to aggregate or network formation. In order to more properly analyze the results of Figs. 1 and 2, it helps to first lay out the physical dimensions of the system as depicted in Fig. 3. The mean interparticle center-to-center separation distance (dc2c ) is defined as dp /Φ1/2 , where dp is the primary particle diameter and Φ is the particle volume fraction. The mean interparticle surface-tosurface separation distance (ds ) is dc2c −dp . As Φ increases, the system dimensions, ds and dp , eventually become of com-
parable length (ds /dp ∼1), which can lead to constrained motion and excluded volume effects. That is, other particles may be excluded from the interparticle space once the average separation distance is of the order of the particle size, thereby reducing the number of possible positions each particle is able to sample during Brownian motion. Furthermore, each particle with a surrounding volume of liquid defines a spherical cell. Fig. 4 shows the average cell radius, rcell = dc2c /2, and ds as a function of Φ and dp . As dp decreases or Φ increases, ds becomes smaller. This has important implications for nanosize particles, and helps to explain why it is so difficult to obtain low-viscosity concentrated nanosols in aqueous systems. This explanation may not be immediately obvious, since the critical Φ corresponding to ds /dp = 1 occurs at about 13% irrespective of particle size. However, the distance over which hydrodynamic and electrostatic forces act in solution is more or less independent of particle size at first approximation. As a result, when the average separation distance between particles is rather large, these forces dissipate before they can influence neighboring particles. As a result, particle motion is independent and the rheological behavior is Newtonian so long as the particles remain stable and do not aggregate. On the other hand, as the average separation distance is reduced, these forces begin to
Fig. 4. Calculated average cell radius (open) and surface-to-surface separation distance (filled) as a function of particle volume fraction and particle size for silica.
208
U. Paik et al. / Materials Chemistry and Physics 91 (2005) 205–211
influence nearest neighbors, and the motion of nearby particles becomes coupled. Coupling leads to an increase in suspension structure, which provides an additional mechanism for viscous dissipation [22]. In the present context, structure refers to the formation of stable physical bonds between particles or to the ordering or alignment of particles in the fluid. In either case, the structure is altered or disrupted by the application of shear forces, resulting in energy dissipation. In aqueous nanosols, the effects of electrostatic forces on structure can be particularly strong as dp and ds approach the length scale over which short-range repulsive interactions are active. For the case of 20 nm A90 at Φ = 13.2%, we obtain a value of 39 nm for dc2c and 19 nm for ds . Hence, the mean separation distance between A90 particles is roughly the same as the particle diameter. If we consider also the impact of the electrical double layer surrounding the charged particles, we anticipate the appearance of particle crowding effects at a value of Φ that is lower than what would be predicted for a simple hard-sphere system. This is because the short-range electrostatic forces extend the influence of each particle beyond its actual diameter, thereby effectively decreasing the value of ds . The contribution of the double layer in the effective hard-sphere model has been discussed in previous publications [23,24]. Briefly, the electrical double layer thickness can be estimated using the Debye–H¨uckel screening length, 1/κ, where 1/2 F 2 i Ni z2i κ= εr ε0 kT and Ni and zi are the number density and valence, respectively, of the counterions of type i, and F is the Faraday constant. The double layer thickness is therefore primarily a function of ionic strength, although the magnitude of the repulsive force will depend on the surface charge density as well. For a simple 1:1 electrolyte at 25 ◦ C in water √ κ = 3.288 I (nm−1 ) where I is the ionic strength in mol L−1 . When salt is added to the suspension, it results in compression of the double layer as represented by a decrease in 1/κ. At low ionic strengths, the presence of the double layer contributes to the effects of particle crowding. At sufficiently high particle concentrations, the electrostatic interactions enhance the formation of ordered structures and viscoelasticity in a manner that is analogous to the secondary electroviscous effect [22,25,26]. According to DLVO theory, with the addition of electrolyte, the range and magnitude of the repulsive interactions are diminished. This permits a higher sticking frequency during particle collisions and leads to the formation of aggregates. Aggregation in turn is manifested by higher viscosities and shear thinning behavior. Based solely on a classical DLVO interpretation, the trend observed for the viscosity of A90 as a function of shear rate and with increasing electrolyte concentration in Fig. 2 gives
the impression that the low ionic strength nanosol is less stable than its high ionic strength counterpart. If we consider the influence of the double layer in crowded systems, as described above, a different interpretation is then possible. Krieger and Eguiluz [25] working with polymer latices demonstrated that strong repulsive interactions can result in increased structure, leading to higher viscosities and a shear-dependent flow behavior, without impacting stability per se. For a concentrated system, compression of the double layer can have a substantial impact on viscosity. Therefore, the higher suspension viscosity of A90 in the absence of added electrolyte is attributed to the development of structure resulting from the reduction in the effective average interparticle separation distance by a factor comparable to 1/κ. Shear flow alters this ordered structure, leading to the observed shear thinning response. At high shear rates, a limiting linear relation between shear stress and shear rate was observed, indicating that additional changes in structure do not occur beyond a critical shear. Addition of electrolyte causes the double layer to collapse, resulting in loss of structure, and a corresponding loss of viscosity and shear thinning behavior. On the other hand, the lower viscosity and lack of shear thinning at high electrolyte concentration (e.g., 0.5 mol L−1 ) in Fig. 2 would seem to indicate excellent colloidal stability in spite of strong electrostatic screening. This behavior, like the increase in viscosity at low ionic strength, appears to contradict DLVO predictions, but, in fact, it can be understood within the DLVO framework. Although Healy [10] explained the unusually stability of silica by invoking a surface steric barrier containing polysilicates and bound cations, Dumont [28] approached this issue by consideration of silica’s comparatively low Hamaker constant and the relative importance of the static (dielectric) term in the silica–water–silica system. The Hamaker constant reflects the magnitude of the London–van der Waals attractive forces between two particles of a given material separated by a vacuum or other medium. A comparison of Hamaker constants for several common ceramic materials across water (A131 ) is shown in Table 1. Clearly, the attractive force, and hence the driving force for aggregation, is an order of magnitude lower for silica compared with the other ceramic materials. Therefore, the electrostatic repulsive forces should continue to play a significant role for silica stability, even under conditions where the surface potential is well screened. Table 1 Hamaker constants (non-retarded) for various ceramic materials across water, calculated using the Lifshitz theory [29] Material
A131 (10−20 J)
SiO2 (amorphous) ␥-Al2 O3 ␣-Al2 O3 BaTiO3 (average) TiO2 (average)
0.46 3.48a 3.67 8 5.35
a Calculated from Eq. (8) in [30] using a value of 8.7 for the relative permittivity [31] and 1.7 for the refractive index [32].
U. Paik et al. / Materials Chemistry and Physics 91 (2005) 205–211
Fig. 5. Calculated DLVO pair interaction energy curves for silica and ␥alumina, based on a spherical geometry with a particle diameter of 20 nm and a Stern potential of 85 mV.
Fig. 5 shows the DLVO pair interaction energy calculated as a function of separation distance [27]. DLVO pair interaction energy curves were calculated using the Hamaker constants for silica and ␥-alumina listed in Table 1, and applying a spherical particle geometry. Otherwise, material parameters, such as particle size (10 nm radius), ionic strength (0.001 and 0.5 mol L−1 ), and Stern potential (±85 mV), were chosen based on A90 at pH 8 and used for both sets of calculations in order to stress the impact of the Hamaker constant. The Stern potential was estimated from measurements of ζ. The resulting curves in Fig. 5 for A90 silica are marked (a) and (b), and those for alumina are identified as (c) and (d). At low ionic strength, both systems display large repulsive (positive) energy barriers extending out more than 30 nm from the particle surface, and representing a high degree of stability. At 0.5 mol L−1 calculations show a net attractive (negative) interaction for alumina at all separation distances beyond 1 nm (the net energy approaches zero in the bulk solution), with a primary maximum barely above zero, indicating an unstable system. In contrast, the corresponding curve for silica exhibits a significant, albeit reduced, repulsive barrier that is active over short separation distances (below 2 nm), and which should be sufficient in magnitude (about 30 kT) to prevent extensive aggregation from occurring in this system. The relative heights of the maxima in the pair interaction curves directly reflect the relative degree of colloidal stability. In the case of silica, the maximum is reduced by about 32% upon raising the electrolyte concentration from 0.001 to 0.5 mol L−1 . Additionally, the distance over which the net repulsive interaction is felt is greatly compressed due to screening. Although these calculations are not quantitative with respect to real systems, since they consider explicitly pair interactions and do not take into account multi-particle interactions in crowded systems, they do indicate clear trends and order of magnitude differences, and therefore lend support for our interpretation of the experimental results for both silica and alumina. For experimental confirmation of the DLVO calculations and for comparative purposes, we measured the viscosity of
209
Fig. 6. The effect of electrolyte concentration on the viscosity of 13.2% ␥-alumina at pH 5 as a function of shear rate.
a similar sized and highly charged 13.2% ␥-alumina nanosol at pH 5 (IEP is near pH 9) as a function of electrolyte concentration and shear rate. These results are shown in Fig. 6, and should be compared with the corresponding data for A90 silica shown in Fig. 2. For alumina, the change in viscosity and shear thinning behavior with increasing ionic strength follows the expected monotonic DLVO prediction. That is, with increasing ionic strength, viscosity continually rises and shear thinning becomes more prominent. At 0.5 mol L−1 , the alumina nanosol is highly shear thinning as a result of extensive aggregation in the unstable suspension as predicted by the DLVO calculations in Fig. 5. In Fig. 7, the normalized viscosity for the silica nanosol is plotted as a function of electrolyte concentration and solid volume fraction. In this case, viscosity is normalized to the ‘effective’ volume fraction, which takes into account the thickness, 1/κ, of the electrical double layer, and treats this as a hard sphere extension to the particle diameter. As one can see, the curves are partially superimposable, indicating that the increase in viscosity at very low ionic strength can be
Fig. 7. Viscosity of A90 silica at pH 8 as a function of the actual particle volume fraction and electrolyte concentration and at a shear rate of 26.4 s−1 . Viscosity is normalized to an effective volume fraction that accounts for the thickness of the electrical double layer, 1/κ.
210
U. Paik et al. / Materials Chemistry and Physics 91 (2005) 205–211
4. Conclusions
Fig. 8. The effect of dilution on the viscosity of A90 silica measured at a shear rate of 26.4 s−1 . Particles were first dispersed in deionized water at 13.2% and then diluted to 2%.
at least partially attributed to exclude volume effects resulting from the influence of repulsive interactions, particularly above 13%. However, there is some overcompensation with the low ionic strength suspension at low solids concentrations. Apparently, the influence of the electrical double layer cannot be simply viewed as an extension of the hydrodynamic diameter with the resultant increase in excluded volume. In reality, the effect of the repulsive interactions is only felt if neighboring particles approach to within a separation distance smaller than 2/κ (which occurs more frequently as the volume fraction is increased). Otherwise, the influence on viscosity is insignificant, since at low solids an excluded volume effect is not apparent. Thus normalization at very low solids concentrations (below about 10% in this case) is not appropriate. This is clearly demonstrated by a simple dilution experiment in which suspensions that were prepared in deionized water, without added electrolyte, at 13.2% were then diluted to 2%. The results, shown in Fig. 8, show that the viscosity is dramatically diminished upon dilution, even though 1/κ remains large and relatively constant up to about pH 9. Once diluted, the repulsive interactions no longer contribute significantly to viscosity. On the other hand, the positive deviation from the normalized curves at high solid loadings (>10%) and high electrolyte concentration (0.5 mol L−1 ) shown in Fig. 7 is consistent with an increase in aggregation resulting from the lower repulsive barrier and compressed 1/κ, combined with a higher collision frequency. In this case, the viscosity is still lower than one would expect for a fully destabilized system with high solids concentrations. Clearly, the influence of the electrical double layer is responsible for the effects observed near and above 13% solids under low ionic strength conditions. The present experimental results, particularly the positive correlation between ζ and viscosity in conjunction with the DLVO calculations, demonstrate that classical DLVO theory alone is insufficient to predict the rheological behavior of concentrated silica nanosols. The effects of particle crowding and overlapping electrical double layers on suspension structure must also be taken into account.
The observed influence of solids loading and ionic strength on the rheological behavior of concentrated silica nanosols was rationalized in terms of simple geometric considerations and overlapping electrical double layers at low ionic strength, and by consideration of the relatively low attractive component of the DLVO pair interaction term at high ionic strength. While a straight forward interpretation of the classical DLVO theory works well for larger silica microspheres, the present experimental results, particularly the positive correlation between ζ and viscosity, demonstrates that DLVO theory by itself is insufficient to predict the rheological behavior of concentrated silica nanosols. The effects of particle crowding and electrostatic interactions on suspension structure must be considered for a full accounting of the observed behavior. To some extent these effects can be considered as acting to increase the excluded volume, and appropriate normalization of flow curves to an effective volume fraction causes the curves to collapse into a narrow range; normalization only works when the solids loading reaches the critical volume fraction where the average interparticle separation distance is comparable to the particle diameter. The results point to partial compression of the electrical double layer by salt addition as a viable albeit counter intuitive method for decreasing suspension viscosity in highly charged and concentrated silica nanosols. This method works primarily because of the particularly low Hamaker constant for silica. Salt additions will not work well for most other ceramic–water systems, due to the greater magnitude of the attractive London–van der Waals interaction force. This effect was demonstrated by comparing the calculated DLVO curves for silica and alumina, and by comparison of the measured flow curves as a function of ionic strength.
Acknowledgements This work was financially supported by the Korean Institute of Science and Technology Evaluation and Planning (KISTEP) through the National Research Laboratory (NRL) program in the year of 2004.
References [1] [2] [3] [4] [5] [6] [7] [8] [9]
J. Yang, S. Mei, J.M.F. Ferreira, J. Am. Ceram. Soc. 83 (2000) 1361. L.E. Cross, Ferroelectrics 76 (1987) 241. M. Rozman, M. Drofenik, J. Am. Ceram. Soc. 81 (1998) 1757. P.G. McCormick, T. Tsuzuki, J.S. Robinson, J. Ding, Adv. Mater. 13 (2001) 1008. R.K. Singh, S.-M. Lee, K.-S. Choi, G.B. Basim, W. Choi, Z. Chen, B.M. Moudgil, J. Mater. Res. Bull. 27 (2002) 752. B. Xia, I.W. Lenggoro, K. Okuyama, Chem. Mater. 14 (2002) 2623. L.L. Beecroft, C.K. Ober, Chem. Mater. 9 (1997) 1302. S.R. Raghavan, H.J. Walls, S.A. Khan, Langmuir 16 (2000) 7920. P.C. Hiemenz, R. Rajagopalan, Principles of Colloid and Surface Chemistry, Marcel Dekker, New York, 1997.
U. Paik et al. / Materials Chemistry and Physics 91 (2005) 205–211 [10] T.W. Healy, in: H.E. Bergna (Ed.), The Colloid Chemistry of Silica, American Chemical Society, Washington, 1994, p. 147. [11] J. Depasse, A. Watillon, J. Colloid Interf. Sci. 33 (1970) 430. [12] S.K. Milonjic, Colloids Surf. 63 (1992) 113. [13] J. Mahanty, B.W. Ninham, Dispersion Forces, Academic Press, New York, 1979. [14] J.N. Israelachvili, Intermolecular and Surface Forces, Academic Press, San Diego, 1987. [15] J.A. Lewis, J. Am. Ceram. Soc. 83 (2000) 2341. [16] R.G. Horn, J. Am. Ceram. Soc. 73 (1990) 1117. [17] A.A. Zaman, B.M. Moudgil, A.L. Fricke, H. El-Shall, J. Rheol. 40 (1996) 1191. [18] Z. Zhou, P.J. Scales, D.V. Boger, Chem. Eng. Sci. 56 (2001) 2901. [19] V.A. Hackley, J. Texter, Ultrasonic and Dielectric Characterization Techniques for Suspended Particulates, The American Ceramic Society, Westerville, 1998, p. 191. [20] U. Paik, V.A. Hackley, H.W. Lee, J. Am. Ceram. Soc. 82 (1999) 833. [21] V.A. Hackley, U. Paik, B.H. Kim, S.G. Malghan, J. Am. Ceram. Soc. 80 (1997) 1781.
[22] [23] [24] [25] [26] [27]
[28] [29] [30] [31] [32]
211
W.B. Russel, J. Rheol. 24 (1980) 287. T. Okubo, J. Chem. Phys. 87 (1987) 6733. T. Matsumoto, J. Rheol. 33 (1989) 371. I.M. Krieger, M. Eguiluz, Trans. Soc. Rheol. 20 (1976) 29. R. Buscall, J.W. Goodwin, M.W. Hawkins, R.H. Ottewill, J. Chem. Soc. Faraday Trans. I 78 (1982) 2873. R.V. Linhart, J.H. Adair, STABIL ver. 4.5, University of Florida, Department of Materials Science and Engineering, 1996; R.V. Linhart, J.H. Adair, in: J.H. Adair, J.A. Casey, S. Venigalla (Eds.), Handbook on Characterization Techniques for the Solid–Solution Interface, American Ceramic Society, Westerville, 1993, p. 69. F. Dumont, in: H.E. Bergna (Ed.), The Colloid Chemistry of Silica, American Chemical Society, Washington, DC, 1994, p. 143. L. Bergstr¨om, Adv. Colloid Interf. Sci. 70 (1997) 125. L. Bergstr¨om, N. Meurk, H. Arwin, D.J. Rowcliffe, J. Am. Ceram. Soc. 79 (1996) 339. G.P. Singh, M. von Schickfus, S. Hunklinger, K. Dransfeld, Solid State Commun. 40 (1981) 951. R.H. French, H. M¨ullejans, D.J. Jones, J. Am. Ceram. Soc. 81 (1998) 2549.
Rheological and electrokinetic behavior associated with concentrated nanosize silica hydrosols Ungyu Paika,∗ , Jang Yul Kima , Vincent A. Hackleyb a b
Department of Ceramic Engineering, Hanyang University, 17 Haengdang-dong, Seongdong-ku, Seoul 133-791, Republic of Korea Material Science and Engineering Laboratory, National Institute of Standards and Technology, Gaithersburg, MD 20899-8520, USA Received 21 July 2004; received in revised form 2 November 2004; accepted 15 November 2004
Abstract The influence of solids loading and the electrical double layer on the rheological behavior of concentrated silica nanosols was investigated. In this study, silica suspensions were characterized by viscosity, electrokinetic sonic amplitude measurements, and by theoretical considerations. Despite a high electrokinetic potential at pH 8, fumed silica not only exhibits rheological behavior normally indicative of an unstable suspension, but the rheology does not have the expected DLVO dependence on ionic strength. Normalization of viscosity to an effective volume fraction that incorporates the influence of the electrical double layer, leads to partially superimposable curves. The positive correlation between zeta potential and viscosity indicates that classical DLVO calculations alone are insufficient to predict the rheological behavior of concentrated silica nanosols, without first taking into account the effects of particle crowding and the repulsive interactions on suspension structure. The relatively low magnitude of van der Waals attractive forces between silica particles in water also plays an important role at high electrolyte concentrations. A comparison is made between silica nanosols and silica microspheres, and also between nano-silica and nano-alumina. © 2004 Published by Elsevier B.V. Keywords: Ceramics; Oxides; Surface properties
1. Introduction Nanosize inorganic particles (i.e., below 100 nm) are gradually being incorporated into a broad range of advanced devices and applications; some examples include electronic packages, ultra-thin-film optical devices, advanced fuel cell catalysts, molecular conductors, and biochips [1–7]. In most cases, the nanoparticle component is incorporated or utilized via a liquid suspension. Classical colloid science is generally used to both describe and predict the properties and behavior of so-called nanosols, in which the dispersed phase has dimensions in the nanoscale regime. Recent evidence [8] has indicated that classical colloid principles might not fully explain the complex behavior of concentrated nanosols. Thus difficulties can be anticipated in the course of research, development and production of devices based on nanosol technology. ∗
Corresponding author. Tel.: +82 2 2290 0502; fax: +82 2 2281 0502. E-mail address: [email protected] (U. Paik).
0254-0584/$ – see front matter © 2004 Published by Elsevier B.V. doi:10.1016/j.matchemphys.2004.11.011
According to Derjaguin–Landau–Verwey–Overbeek (DLVO) theory [9], a cornerstone of modern colloid science, two types of forces exist between colloidal particles suspended in a dielectric medium: (1) electrostatic forces, which result from unscreened surface charge on the particle, and (2) London–van der Waals attractive forces, which are universal in nature. The colloidal stability and rheology of oxide suspensions, in the absence of steric additives, can be largely understood by combining these two forces (i.e., assumption of additivity). However, the expressions of the electrical forces are derived from the Poisson–Boltzmann equation, which is based on two key approximations: (1) the solvent is considered as a structureless dielectric continuum and (2) the field generated by the ions is a mean field. There are several reports [10–12] of the unique stability of nanosize silica hydrosols near the isoelectric point (IEP). Mahanty and Ninham [13] discovered experimentally the existence of short-range forces that play an important role in the interaction process and which must be added to those
206
U. Paik et al. / Materials Chemistry and Physics 91 (2005) 205–211
forces already accounted for by the original DLVO theory. These short-range interactions are referred to as structural forces [14–16]. Structural forces might explain some particular aspects of the stability behavior of silica nanosols, but they are insufficient to account for the apparent cooperative effects of solids loading and electrostatics found in the present study. Contrary to suspensions based on colloidalsize (100–1000 nm) silica [17] and other inorganic oxides [18] as reported in the literature, we find that the rheological behavior of concentrated electrostatically stabilized silica nanosols is counterintuitive with regards to predictions based on a standard interpretation of DLVO theory. Despite a high electrokinetic potential at pH 8, fumed silica not only exhibits rheological behavior that would normally indicate an unstable or aggregated suspension (i.e., pseudoplastic-high viscosity), but the rheology does not have the expected dependence on ionic strength. In this study, experimental measurements, DLVO calculations, and simple geometric considerations are used to understand the influence of solids loading and the electrical double-layer on the rheological behavior of concentrated silica nanosols, and to compare their behavior with that of much larger silica microspheres, as well as like-sized nano-alumina, under similar conditions.
2. Experimental
2.2. Characterization techniques The electrokinetic behavior of silica suspensions at a volume fraction of 2% and a temperature of 25 ± 0.1 ◦ C were characterized using the electrokinetic sonic amplitude (ESA) technique (Acoustosizer II, Colloidal Dynamics, Sydney, Australia). The basic theory and application of ESA have been described in detail elsewhere [19–21]. For ESA measurements, two identical suspensions were prepared for each analysis. Separate acid (1.0 N HCl) and base (1.0 N NaOH) titrations were then performed beginning at the natural pH, and subsequently combined to generate a complete acid–base titration curve. Based on previous work, we estimate a measurement precision of ±1 mV for zeta potential. The rheological behavior of suspensions was measured using a controlled-stress rheometer (MCR300, Paar Physica, Stuttgart, Germany) with a concentric-cylinder tool geometry and an external temperature-controlled bath-circulator operating at 25 ± 0.1 ◦ C. To obtain the rheological behavior of suspensions at specific pH values (pH 3, 5, 7, 8, 9, 11, and 8 with added NaNO3 ), the suspensions were prepared for analysis in the manner previously described, but the pH was adjusted prior to ultrasonic treatment using HCl or NaOH. The shear rate was increased from 1 to 1000 s−1 , with a pause time of 30 s at each shear rate. Based on previous measurement data and experience, a reproducibility of ±10% can be expected for viscosity measurements performed under these conditions.
2.1. Preparation of suspensions Aerosil 90 fumed silica (designated A90) and aluminum oxide C (␥-alumina) were obtained from Degussa AG (Frankfurt am Main, Germany)1 . The specific surface area and average primary particle size, as provided by the manufacturer, was as follows: 90 ± 15 m2 g−1 and 20 nm for A90; 100 ± 15 m2 g−1 and 13 nm for ␥-alumina. Silica microspheres (designated Geltech) with a nominal median diameter of 500 nm were obtained from Geltech Inc. (Alachua, FL). The silica particles were dispersed in deionized water or NaNO3 solution. Each suspension was subjected to intense ultrasonic treatment for 5 min in order to break down aggregates. An ice bath was used to control the temperature of the suspension during ultrasonic treatment. To establish an equilibrium dispersion, the suspension was aged for 12 h at room temperature using a wrist-action shaker. Following aging, the suspension was ultrasonicated for an additional 5 min.
1 Certain trade names and company products are mentioned in the text or identified in illustrations in order to specify adequately the experimental procedure and equipment used. In no case does such identification imply recommendation or endorsement by National Institute of Standards and Technology, nor does it imply that the products are necessarily the best available for the purpose.
3. Results and discussion By changing the pH, one can alter the magnitude (and sign) of the zeta potential (ζ), while the addition of an inert electrolyte will affect both the magnitude of ζ and the electrical double-layer thickness. Thus, both pH and electrolyte concentration will directly impact colloidal stability in an electrostatically stabilized system. Fig. 1 compares ζ
Fig. 1. The relationship between zeta potential (open) and viscosity (filled) for silica suspensions as a function of suspension pH: nanosize A90 vs. Geltech microspheres (G). Viscosity was determined at a shear rate of 26.4 s−1 . Particle volume fraction given in %.
U. Paik et al. / Materials Chemistry and Physics 91 (2005) 205–211
207
Fig. 3. Diagram illustrating the relationship between average interparticle surface-to-surface separation distance, ds , and other system dimensions, for a particle diameter dp = 20 nm and Φ = 13.2%. Fig. 2. The effect of electrolyte concentration on the viscosity of 13.2% A90 silica at pH 8 as a function of shear rate.
and viscosity (at a shear rate of 26.4 s−1 ) as a function of pH for the A90 and Geltech suspensions. Even at a solid concentration of 20%, the Geltech microspheres exhibit a fairly constant and low viscosity across the entire pH range, whereas A90 exhibits a strong pH dependence at a volume fraction of 13.2%, with an increase in viscosity near pH 7 in excess of 300%. Fig. 2 shows the effect of inert electrolyte concentration on viscosity as a function of shear rate for highly charged 13.2% A90 at pH 8. Fig. 1 indicates that for Geltech microspheres, ζ and viscosity both follow the expected behavior predicted by classical DLVO theory. That is, as the pH moves away from the IEP, which is located near pH 2 for silica, ζ increases and viscosity decreases. However, A90 exhibits a discrepancy between the expectation of DLVO theory and the experimental results: as ζ, and by inference colloidal stability, of A90 increases, viscosity sharply increases. For suspensions, changes in viscosity are often assumed to reflect changes in the state of dispersion. With this assumption in mind, viscosity should exhibit a minimum (i.e., reflecting the least amount of aggregation) when ζ is at a maximum at constant ionic strength, or, similarly, at the lowest ionic strength when pH is held constant. Since A90 exhibits the reverse behavior, a deviation from DLVO appears to exist. However, the often-applied assumption that viscosity is a direct reflection of the state of aggregation (or, by inference, colloidal stability) is not strictly valid. Viscosity is a macroscopic property, and as such it will be influenced by any chemical or physical process that alters the structural or hydrodynamic conditions of the system. Hence, factors such as particle crowding, particle ordering and electroviscous effects will also impact viscosity, in addition to aggregate or network formation. In order to more properly analyze the results of Figs. 1 and 2, it helps to first lay out the physical dimensions of the system as depicted in Fig. 3. The mean interparticle center-to-center separation distance (dc2c ) is defined as dp /Φ1/2 , where dp is the primary particle diameter and Φ is the particle volume fraction. The mean interparticle surface-tosurface separation distance (ds ) is dc2c −dp . As Φ increases, the system dimensions, ds and dp , eventually become of com-
parable length (ds /dp ∼1), which can lead to constrained motion and excluded volume effects. That is, other particles may be excluded from the interparticle space once the average separation distance is of the order of the particle size, thereby reducing the number of possible positions each particle is able to sample during Brownian motion. Furthermore, each particle with a surrounding volume of liquid defines a spherical cell. Fig. 4 shows the average cell radius, rcell = dc2c /2, and ds as a function of Φ and dp . As dp decreases or Φ increases, ds becomes smaller. This has important implications for nanosize particles, and helps to explain why it is so difficult to obtain low-viscosity concentrated nanosols in aqueous systems. This explanation may not be immediately obvious, since the critical Φ corresponding to ds /dp = 1 occurs at about 13% irrespective of particle size. However, the distance over which hydrodynamic and electrostatic forces act in solution is more or less independent of particle size at first approximation. As a result, when the average separation distance between particles is rather large, these forces dissipate before they can influence neighboring particles. As a result, particle motion is independent and the rheological behavior is Newtonian so long as the particles remain stable and do not aggregate. On the other hand, as the average separation distance is reduced, these forces begin to
Fig. 4. Calculated average cell radius (open) and surface-to-surface separation distance (filled) as a function of particle volume fraction and particle size for silica.
208
U. Paik et al. / Materials Chemistry and Physics 91 (2005) 205–211
influence nearest neighbors, and the motion of nearby particles becomes coupled. Coupling leads to an increase in suspension structure, which provides an additional mechanism for viscous dissipation [22]. In the present context, structure refers to the formation of stable physical bonds between particles or to the ordering or alignment of particles in the fluid. In either case, the structure is altered or disrupted by the application of shear forces, resulting in energy dissipation. In aqueous nanosols, the effects of electrostatic forces on structure can be particularly strong as dp and ds approach the length scale over which short-range repulsive interactions are active. For the case of 20 nm A90 at Φ = 13.2%, we obtain a value of 39 nm for dc2c and 19 nm for ds . Hence, the mean separation distance between A90 particles is roughly the same as the particle diameter. If we consider also the impact of the electrical double layer surrounding the charged particles, we anticipate the appearance of particle crowding effects at a value of Φ that is lower than what would be predicted for a simple hard-sphere system. This is because the short-range electrostatic forces extend the influence of each particle beyond its actual diameter, thereby effectively decreasing the value of ds . The contribution of the double layer in the effective hard-sphere model has been discussed in previous publications [23,24]. Briefly, the electrical double layer thickness can be estimated using the Debye–H¨uckel screening length, 1/κ, where 1/2 F 2 i Ni z2i κ= εr ε0 kT and Ni and zi are the number density and valence, respectively, of the counterions of type i, and F is the Faraday constant. The double layer thickness is therefore primarily a function of ionic strength, although the magnitude of the repulsive force will depend on the surface charge density as well. For a simple 1:1 electrolyte at 25 ◦ C in water √ κ = 3.288 I (nm−1 ) where I is the ionic strength in mol L−1 . When salt is added to the suspension, it results in compression of the double layer as represented by a decrease in 1/κ. At low ionic strengths, the presence of the double layer contributes to the effects of particle crowding. At sufficiently high particle concentrations, the electrostatic interactions enhance the formation of ordered structures and viscoelasticity in a manner that is analogous to the secondary electroviscous effect [22,25,26]. According to DLVO theory, with the addition of electrolyte, the range and magnitude of the repulsive interactions are diminished. This permits a higher sticking frequency during particle collisions and leads to the formation of aggregates. Aggregation in turn is manifested by higher viscosities and shear thinning behavior. Based solely on a classical DLVO interpretation, the trend observed for the viscosity of A90 as a function of shear rate and with increasing electrolyte concentration in Fig. 2 gives
the impression that the low ionic strength nanosol is less stable than its high ionic strength counterpart. If we consider the influence of the double layer in crowded systems, as described above, a different interpretation is then possible. Krieger and Eguiluz [25] working with polymer latices demonstrated that strong repulsive interactions can result in increased structure, leading to higher viscosities and a shear-dependent flow behavior, without impacting stability per se. For a concentrated system, compression of the double layer can have a substantial impact on viscosity. Therefore, the higher suspension viscosity of A90 in the absence of added electrolyte is attributed to the development of structure resulting from the reduction in the effective average interparticle separation distance by a factor comparable to 1/κ. Shear flow alters this ordered structure, leading to the observed shear thinning response. At high shear rates, a limiting linear relation between shear stress and shear rate was observed, indicating that additional changes in structure do not occur beyond a critical shear. Addition of electrolyte causes the double layer to collapse, resulting in loss of structure, and a corresponding loss of viscosity and shear thinning behavior. On the other hand, the lower viscosity and lack of shear thinning at high electrolyte concentration (e.g., 0.5 mol L−1 ) in Fig. 2 would seem to indicate excellent colloidal stability in spite of strong electrostatic screening. This behavior, like the increase in viscosity at low ionic strength, appears to contradict DLVO predictions, but, in fact, it can be understood within the DLVO framework. Although Healy [10] explained the unusually stability of silica by invoking a surface steric barrier containing polysilicates and bound cations, Dumont [28] approached this issue by consideration of silica’s comparatively low Hamaker constant and the relative importance of the static (dielectric) term in the silica–water–silica system. The Hamaker constant reflects the magnitude of the London–van der Waals attractive forces between two particles of a given material separated by a vacuum or other medium. A comparison of Hamaker constants for several common ceramic materials across water (A131 ) is shown in Table 1. Clearly, the attractive force, and hence the driving force for aggregation, is an order of magnitude lower for silica compared with the other ceramic materials. Therefore, the electrostatic repulsive forces should continue to play a significant role for silica stability, even under conditions where the surface potential is well screened. Table 1 Hamaker constants (non-retarded) for various ceramic materials across water, calculated using the Lifshitz theory [29] Material
A131 (10−20 J)
SiO2 (amorphous) ␥-Al2 O3 ␣-Al2 O3 BaTiO3 (average) TiO2 (average)
0.46 3.48a 3.67 8 5.35
a Calculated from Eq. (8) in [30] using a value of 8.7 for the relative permittivity [31] and 1.7 for the refractive index [32].
U. Paik et al. / Materials Chemistry and Physics 91 (2005) 205–211
Fig. 5. Calculated DLVO pair interaction energy curves for silica and ␥alumina, based on a spherical geometry with a particle diameter of 20 nm and a Stern potential of 85 mV.
Fig. 5 shows the DLVO pair interaction energy calculated as a function of separation distance [27]. DLVO pair interaction energy curves were calculated using the Hamaker constants for silica and ␥-alumina listed in Table 1, and applying a spherical particle geometry. Otherwise, material parameters, such as particle size (10 nm radius), ionic strength (0.001 and 0.5 mol L−1 ), and Stern potential (±85 mV), were chosen based on A90 at pH 8 and used for both sets of calculations in order to stress the impact of the Hamaker constant. The Stern potential was estimated from measurements of ζ. The resulting curves in Fig. 5 for A90 silica are marked (a) and (b), and those for alumina are identified as (c) and (d). At low ionic strength, both systems display large repulsive (positive) energy barriers extending out more than 30 nm from the particle surface, and representing a high degree of stability. At 0.5 mol L−1 calculations show a net attractive (negative) interaction for alumina at all separation distances beyond 1 nm (the net energy approaches zero in the bulk solution), with a primary maximum barely above zero, indicating an unstable system. In contrast, the corresponding curve for silica exhibits a significant, albeit reduced, repulsive barrier that is active over short separation distances (below 2 nm), and which should be sufficient in magnitude (about 30 kT) to prevent extensive aggregation from occurring in this system. The relative heights of the maxima in the pair interaction curves directly reflect the relative degree of colloidal stability. In the case of silica, the maximum is reduced by about 32% upon raising the electrolyte concentration from 0.001 to 0.5 mol L−1 . Additionally, the distance over which the net repulsive interaction is felt is greatly compressed due to screening. Although these calculations are not quantitative with respect to real systems, since they consider explicitly pair interactions and do not take into account multi-particle interactions in crowded systems, they do indicate clear trends and order of magnitude differences, and therefore lend support for our interpretation of the experimental results for both silica and alumina. For experimental confirmation of the DLVO calculations and for comparative purposes, we measured the viscosity of
209
Fig. 6. The effect of electrolyte concentration on the viscosity of 13.2% ␥-alumina at pH 5 as a function of shear rate.
a similar sized and highly charged 13.2% ␥-alumina nanosol at pH 5 (IEP is near pH 9) as a function of electrolyte concentration and shear rate. These results are shown in Fig. 6, and should be compared with the corresponding data for A90 silica shown in Fig. 2. For alumina, the change in viscosity and shear thinning behavior with increasing ionic strength follows the expected monotonic DLVO prediction. That is, with increasing ionic strength, viscosity continually rises and shear thinning becomes more prominent. At 0.5 mol L−1 , the alumina nanosol is highly shear thinning as a result of extensive aggregation in the unstable suspension as predicted by the DLVO calculations in Fig. 5. In Fig. 7, the normalized viscosity for the silica nanosol is plotted as a function of electrolyte concentration and solid volume fraction. In this case, viscosity is normalized to the ‘effective’ volume fraction, which takes into account the thickness, 1/κ, of the electrical double layer, and treats this as a hard sphere extension to the particle diameter. As one can see, the curves are partially superimposable, indicating that the increase in viscosity at very low ionic strength can be
Fig. 7. Viscosity of A90 silica at pH 8 as a function of the actual particle volume fraction and electrolyte concentration and at a shear rate of 26.4 s−1 . Viscosity is normalized to an effective volume fraction that accounts for the thickness of the electrical double layer, 1/κ.
210
U. Paik et al. / Materials Chemistry and Physics 91 (2005) 205–211
4. Conclusions
Fig. 8. The effect of dilution on the viscosity of A90 silica measured at a shear rate of 26.4 s−1 . Particles were first dispersed in deionized water at 13.2% and then diluted to 2%.
at least partially attributed to exclude volume effects resulting from the influence of repulsive interactions, particularly above 13%. However, there is some overcompensation with the low ionic strength suspension at low solids concentrations. Apparently, the influence of the electrical double layer cannot be simply viewed as an extension of the hydrodynamic diameter with the resultant increase in excluded volume. In reality, the effect of the repulsive interactions is only felt if neighboring particles approach to within a separation distance smaller than 2/κ (which occurs more frequently as the volume fraction is increased). Otherwise, the influence on viscosity is insignificant, since at low solids an excluded volume effect is not apparent. Thus normalization at very low solids concentrations (below about 10% in this case) is not appropriate. This is clearly demonstrated by a simple dilution experiment in which suspensions that were prepared in deionized water, without added electrolyte, at 13.2% were then diluted to 2%. The results, shown in Fig. 8, show that the viscosity is dramatically diminished upon dilution, even though 1/κ remains large and relatively constant up to about pH 9. Once diluted, the repulsive interactions no longer contribute significantly to viscosity. On the other hand, the positive deviation from the normalized curves at high solid loadings (>10%) and high electrolyte concentration (0.5 mol L−1 ) shown in Fig. 7 is consistent with an increase in aggregation resulting from the lower repulsive barrier and compressed 1/κ, combined with a higher collision frequency. In this case, the viscosity is still lower than one would expect for a fully destabilized system with high solids concentrations. Clearly, the influence of the electrical double layer is responsible for the effects observed near and above 13% solids under low ionic strength conditions. The present experimental results, particularly the positive correlation between ζ and viscosity in conjunction with the DLVO calculations, demonstrate that classical DLVO theory alone is insufficient to predict the rheological behavior of concentrated silica nanosols. The effects of particle crowding and overlapping electrical double layers on suspension structure must also be taken into account.
The observed influence of solids loading and ionic strength on the rheological behavior of concentrated silica nanosols was rationalized in terms of simple geometric considerations and overlapping electrical double layers at low ionic strength, and by consideration of the relatively low attractive component of the DLVO pair interaction term at high ionic strength. While a straight forward interpretation of the classical DLVO theory works well for larger silica microspheres, the present experimental results, particularly the positive correlation between ζ and viscosity, demonstrates that DLVO theory by itself is insufficient to predict the rheological behavior of concentrated silica nanosols. The effects of particle crowding and electrostatic interactions on suspension structure must be considered for a full accounting of the observed behavior. To some extent these effects can be considered as acting to increase the excluded volume, and appropriate normalization of flow curves to an effective volume fraction causes the curves to collapse into a narrow range; normalization only works when the solids loading reaches the critical volume fraction where the average interparticle separation distance is comparable to the particle diameter. The results point to partial compression of the electrical double layer by salt addition as a viable albeit counter intuitive method for decreasing suspension viscosity in highly charged and concentrated silica nanosols. This method works primarily because of the particularly low Hamaker constant for silica. Salt additions will not work well for most other ceramic–water systems, due to the greater magnitude of the attractive London–van der Waals interaction force. This effect was demonstrated by comparing the calculated DLVO curves for silica and alumina, and by comparison of the measured flow curves as a function of ionic strength.
Acknowledgements This work was financially supported by the Korean Institute of Science and Technology Evaluation and Planning (KISTEP) through the National Research Laboratory (NRL) program in the year of 2004.
References [1] [2] [3] [4] [5] [6] [7] [8] [9]
J. Yang, S. Mei, J.M.F. Ferreira, J. Am. Ceram. Soc. 83 (2000) 1361. L.E. Cross, Ferroelectrics 76 (1987) 241. M. Rozman, M. Drofenik, J. Am. Ceram. Soc. 81 (1998) 1757. P.G. McCormick, T. Tsuzuki, J.S. Robinson, J. Ding, Adv. Mater. 13 (2001) 1008. R.K. Singh, S.-M. Lee, K.-S. Choi, G.B. Basim, W. Choi, Z. Chen, B.M. Moudgil, J. Mater. Res. Bull. 27 (2002) 752. B. Xia, I.W. Lenggoro, K. Okuyama, Chem. Mater. 14 (2002) 2623. L.L. Beecroft, C.K. Ober, Chem. Mater. 9 (1997) 1302. S.R. Raghavan, H.J. Walls, S.A. Khan, Langmuir 16 (2000) 7920. P.C. Hiemenz, R. Rajagopalan, Principles of Colloid and Surface Chemistry, Marcel Dekker, New York, 1997.
U. Paik et al. / Materials Chemistry and Physics 91 (2005) 205–211 [10] T.W. Healy, in: H.E. Bergna (Ed.), The Colloid Chemistry of Silica, American Chemical Society, Washington, 1994, p. 147. [11] J. Depasse, A. Watillon, J. Colloid Interf. Sci. 33 (1970) 430. [12] S.K. Milonjic, Colloids Surf. 63 (1992) 113. [13] J. Mahanty, B.W. Ninham, Dispersion Forces, Academic Press, New York, 1979. [14] J.N. Israelachvili, Intermolecular and Surface Forces, Academic Press, San Diego, 1987. [15] J.A. Lewis, J. Am. Ceram. Soc. 83 (2000) 2341. [16] R.G. Horn, J. Am. Ceram. Soc. 73 (1990) 1117. [17] A.A. Zaman, B.M. Moudgil, A.L. Fricke, H. El-Shall, J. Rheol. 40 (1996) 1191. [18] Z. Zhou, P.J. Scales, D.V. Boger, Chem. Eng. Sci. 56 (2001) 2901. [19] V.A. Hackley, J. Texter, Ultrasonic and Dielectric Characterization Techniques for Suspended Particulates, The American Ceramic Society, Westerville, 1998, p. 191. [20] U. Paik, V.A. Hackley, H.W. Lee, J. Am. Ceram. Soc. 82 (1999) 833. [21] V.A. Hackley, U. Paik, B.H. Kim, S.G. Malghan, J. Am. Ceram. Soc. 80 (1997) 1781.
[22] [23] [24] [25] [26] [27]
[28] [29] [30] [31] [32]
211
W.B. Russel, J. Rheol. 24 (1980) 287. T. Okubo, J. Chem. Phys. 87 (1987) 6733. T. Matsumoto, J. Rheol. 33 (1989) 371. I.M. Krieger, M. Eguiluz, Trans. Soc. Rheol. 20 (1976) 29. R. Buscall, J.W. Goodwin, M.W. Hawkins, R.H. Ottewill, J. Chem. Soc. Faraday Trans. I 78 (1982) 2873. R.V. Linhart, J.H. Adair, STABIL ver. 4.5, University of Florida, Department of Materials Science and Engineering, 1996; R.V. Linhart, J.H. Adair, in: J.H. Adair, J.A. Casey, S. Venigalla (Eds.), Handbook on Characterization Techniques for the Solid–Solution Interface, American Ceramic Society, Westerville, 1993, p. 69. F. Dumont, in: H.E. Bergna (Ed.), The Colloid Chemistry of Silica, American Chemical Society, Washington, DC, 1994, p. 143. L. Bergstr¨om, Adv. Colloid Interf. Sci. 70 (1997) 125. L. Bergstr¨om, N. Meurk, H. Arwin, D.J. Rowcliffe, J. Am. Ceram. Soc. 79 (1996) 339. G.P. Singh, M. von Schickfus, S. Hunklinger, K. Dransfeld, Solid State Commun. 40 (1981) 951. R.H. French, H. M¨ullejans, D.J. Jones, J. Am. Ceram. Soc. 81 (1998) 2549.