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J. Phys. Chem. C 2007, 111, 14098-14104

Controlling Nanosized ZnO Growth Kinetics Using Various Zn:OH Concentration Ratios Anthony S. Ratkovich and R. Lee Penn* Department of Chemistry, UniVersity of Minnesota, 207 Pleasant St. S.E., Minneapolis, Minnesota 55455 ReceiVed: February 22, 2007; In Final Form: June 29, 2007

Zinc oxide particle growth from homogeneous solution was monitored using in situ UV-vis spectroscopy. Final particle size and overall growth rates increased with increasing zinc to hydroxide concentration ratio and with the use of acetate as compared to tribromoacetic acid as surfactant additive. Particle growth was fit using three models: (1) the commonly used linear coarsening model, (2) the classic coarsening model, and (3) the simultaneous coarsening and oriented aggregation model. Both the classic coarsening and the simultaneous coarsening and oriented aggregation model produce reasonable fits of the data. In the case of the classic coarsening model, a value of n ) 3, which is consistent with diffusion-limited coarsening, produced the best fit. However, the simultaneous coarsening and oriented aggregation model was slightly better at describing the early stages of growth, which is indicative of a substantial contribution to growth by oriented aggregation. High-resolution transmission electron micrographs confirm oriented aggregation at the early stages of growth, and the degree of oriented aggregation was substantially higher for experiments using tribromoacetic acid as compared to acetate.

1. Introduction Zinc oxide is an attractive material for a broad range of electronic, optical, and piezoelectric applications due to its direct band gap and excellent thermal, chemical, and piezoelectric properties. For example, ZnO has been suggested for use in applications such as solar cells,1 sensors,2 light emitting diodes,3 and many other devices. In particular, dye-sensitized solar cells can be constructed using nanosized ZnO particles with dye molecules adsorbed to their surfaces. Solar cells using this technology are potentially more efficient and cost-effective than current solar cell designs.4 Zinc oxide nanostructures are typically produced using a solid-vapor phase thermal sublimation technique, an expensive, high-temperature process.5 Solution-phase synthesis of ZnO is an area of intense interest, as it provides a low-temperature, economical way to produce various ZnO nanostructures. Growth from solution typically starts with nucleation and is followed by growth of the nuclei by addition of dissolved species until the metal cation concentration reaches the solubility of the oxide. Then particle growth proceeds by two primary mechanisms, coarsening and aggregation. Coarsening involves growth of larger, more stable particles at the expense of smaller, less stable particles, and aggregation is growth by combination of primary particles into larger secondary particles. Oriented aggregation is a special case of aggregation whereby primary crystallites combine to form secondary crystals.6 Previously, coarsening and oriented aggregation have been shown to operate simultaneously during particle growth from homogeneous solution.7 Solution conditions such as temperature,8 water concentration,9 ions present in solution,10,11 and solvent12 have been shown to impact particle nucleation and growth. Understanding how these factors enhance or inhibit one growth mechanism over another will lead to improved and more economical methods for producing functional nanoparticles and specialized nanostructures. This work employs in situ UV-vis * Corresponding author. E-mail: [email protected].

spectroscopy to quantify particle size as a function of time in order to study the growth kinetics of ZnO. Data were fit to three growth models: the linear coarsening model, the classic coarsening model, and the simultaneous coarsening and oriented aggregation model. 2. Experimental Section 2.1. Experimental Design. ZnO nanoparticles were synthesized from homogeneous solutions of precursors, and particle size was monitored by in situ UV-vis spectroscopy. For these experiments, the Zn2+:OH- concentration ratio (Zn:OH) and type of surfactant were varied in order to examine the effects of these variables on ZnO nanoparticle growth. Zinc perchlorate hexahydrate was employed as the zinc source because the perchlorate anion has been shown to have a weaker affinity for the ZnO surface than other anions commonly used in the synthesis of ZnO nanoparticles, such as acetate and bromide.10 Surfactant-free controls demonstrate limited particle stability with visible precipitates forming within 10 min. 2.2. Materials. Reagents used in this study were zinc perchlorate (17-18% Zn complexometric), sodium hydroxide (99%), isopropyl alcohol (IPA) (99.9%), glacial acetic acid (AA) (99%), and tribromoacetic acid (TBAA) (99%). All chemicals were purchased from Aldrich Chemical Co. and used as received. All glassware used in reagent preparation was soaked overnight in 4 M nitric acid and rinsed with purified water followed by a rinse with IPA. The quartz cuvettes used for in situ growth reactions were soaked for 24 h in concentrated oxalic acid, rinsed with purified water (18 MΩ cm, Millipore Corp.), and finally rinsed with IPA. 2.3. Reagent Preparation. All solutions were prepared by dissolution of solids or liquids in IPA at room temperature. The sodium hydroxide solution was heated to 65 °C for 3 h to speed dissolution. Surfactant solutions were neutralized by combining equimolar sodium hydroxide/IPA and surfactant/IPA solutions. Neutralization was performed prior to the reaction in order to ensure careful control of Zn:OH. The total water content in the

10.1021/jp071500i CCC: $37.00 © 2007 American Chemical Society Published on Web 09/05/2007

Controlling ZnO Growth with Zn:OH Ratios

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reaction was kept constant at approximately 0.04 M, taking into account water from the zinc perchlorate hexahydrate, neutralized surfactant solutions, and water impurities found in isopropyl alcohol. 2.4. Particle Synthesis. This synthesis was adapted from Bahnemann et al.13,14 The balanced chemical equation for the nucleation reaction can be written as IPA

Zn(ClO4)2 + 2NaOH 98 ZnO(s) + H2O + 2NaClO4

(1)

The solutions of sodium hydroxide and surfactant in IPA were transferred to a quartz cuvette and brought to the desired reaction temperature. The reaction was initiated by injection of the zinc perchlorate solution into the cuvette, and the solution was vigorously stirred at all times using a Teflon-coated magnetic stir bar. Zn:OH was varied by keeping the zinc perchlorate concentration constant at 0.001 M and varying the sodium hydroxide concentration from 0.00125 to 0.00222 M. In order to study the effect of Zn:OH on particle growth, six ratios were used in the range from 0.45 to 0.8. Two different surfactant systems were used to study the effects of surfactant identity on particle growth: acetic acid and tribromoacetic acid. The concentration of surfactant was kept constant at 3.474 × 10-4 M during particle growth. This concentration was estimated to correspond to approximately two monolayers of surface coverage on a 4 nm particle, assuming all Zn2+ reacted to form ZnO and using four surface sites per square nanometer. 2.5. In Situ UV-Vis Spectroscopy and Particle Size Characterization. Particle growth was monitored in situ using an Agilent 8453 UV-vis spectrometer equipped with a Peltier temperature controller and magnetic stirrer. Growth reactions were performed in a quartz cuvette fitted with a Teflon stopper to prevent solvent evaporation and interference from moisture in the atmosphere. Atmospheric moisture affects reproducibility as it accumulates in stock solutions and reaction mixtures and causes variability in growth. Solution preparation and growth reactions were performed in a humidity-controlled environment, with relative humidity maintained at less than 10%. Absorbance spectra were acquired between 190 and 1200 nm every minute for the first 15 min, every 5 min for the next 45 min, and every 15 min through 6 h. The average band gap for each sample was determined by finding the inflection point of the absorption edge using the second derivative of the UV-vis spectrum. The effective mass model was employed to calculate the average particle size from the average band gap using  ) 8.5, me ) 0.26, mh ) 0.59, and Egbulk ) 3.2 eV. Due to the relatively small effective masses for ZnO, quantum size effects are expected to occur for particles sizes up to ∼8 nm.8-12,15,16 Average sizes were calculated using a minimum of three trials per specified condition, and the experimental error discussed is the experimental uncertainty determined at the 95% confidence interval for the sample. 2.6. Characterization by High-Resolution Transmission Electron Microscopy (HRTEM). Samples were prepared for HRTEM by dipping a 3 mm copper HRTEM grid coated with a holey carbon film (SPI Supplies) into the reaction mixture at the appropriate time. The resulting grid was then allowed to air-dry in the humidity controlled environment. Samples were examined using an FEI Tecnai F30 FEGTEM. Images were collected using a charge-coupled device (CCD) camera and analyzed using Gatan Digital Micrograph software.

Figure 1. Representative TEM images for ZnO particles: (a) 0.625 Zn:OH TBAA at 15 min and (b) 0.625 Zn:OH TBAA at 120 min. The average particle sizes obtained from counting 160 particles for each sample are 4.1 ( 0.3 and 4.9 ( 0.5 nm. Examples of primary particles are outlined in white and examples of oriented aggregates are outlined in black. Lattice fringes analyzed in HRTEM images were consistent with zinc oxide with the wurtzite structure (a ) 3.25 Å, c ) 5.21).

3. Results and Discussion ZnO particle growth depends strongly on both Zn:OH and the surfactant employed. Figure 1 shows particle diameter as a function of time for ZnO particles synthesized using Zn:OH ratios of 0.50-0.71 and either AA (Figure 1A) or TBAA (Figure 1B). Each data point represents the average of a minimum of three trials, and the average experimental uncertainty is 0.09 nm. This data demonstrates a high degree of reproducibility. Figure 1 shows representative HRTEM images of ZnO particles prepared using 0.625 Zn:OH and TBAA after 15 min (Figure 2A) and 120 min (Figure 2B). The average particle sizes, as determined by measuring 160 particles from calibrated HRTEM images, are 4.1 ( 0.3 and 4.9 ( 0.4 nm, respectively. These sizes agree well with those determined using the effective mass model, 4.3 and 5.3 nm, respectively. The differences in particles sizes are typical when using these two methods, with the effective mass model resulting in a slightly larger particle sizes than HRTEM.8 The degree to which the Zn:OH ratio affects particle growth is dependent on the type of surfactant employed. In the case of AA, nucleation and growth were observed for Zn:OH ratios ranging from 0.55 to 0.71, although colloidal scattering was observed after 1 h for 0.71. In the case of TBAA, ZnO nucleation and growth was observed for ratios ranging from 0.5 to 0.71, and all suspensions were stable up to 6 h. Thus, use of TBAA substantially expands the employable range of Zn:OH ratio. In addition, growth at later stages (i.e., beyond 1 h) is substantially faster with AA (0.5 nm/h on average) than with TBAA (0.2 nm/h), and the final particle size is substantially larger with AA (6.8-8.8 nm) than with TBAA (5.5-6.4 nm).

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Ratkovich and Penn TABLE 1: Percentage of Particles with Morphology Consistent with Oriented Aggregationa

surfactant

time (min)

min estimate (%)

max estimate (%)

15 120 15 120

8.4 7.9 1.7 2.0

15.4 15.0 3.4 3.6

TBAA AA

a Experimental conditions for these samples were Zn:OH ) 0.625 and 65 °C.

TABLE 2: Relative Particle Size Distributions at t ) 60 min as a Function of Surfactant and Zn:OH Ratio surfactant AA TBAA

ratio

D60 (nm)

fwhm (nm)

fwhm/D60 (%)

0.55 0.625 0.50 0.55 0.625 0.71

5.6 6.6 4.6 4.7 5.1 5.3

0.84 1.2 0.91 0.93 1.1 1.2

11 ( 2 13 ( 2 19 ( 2 19 ( 2 23 ( 2 22 ( 2

3.1. Particle Size Distribution. Pesika et al. showed that particle size distributions can be determined from the absorption edges of the UV-vis spectra using eq 2, in which dA/dr is the first derivative of the spectrum with respect to particle radius (r).16

n(r) ∝ -

Figure 2. Average diameter vs time for ZnO particle growth using various Zn:OH ratios and the following surfactants: (a) AA and (b) TBAA. These growth curves represent the average of three trials for each condition specified. The experimental uncertainty for these reactions is 0.09 nm. All reactions were performed at 65 °C.

We hypothesize that the binding of TBAA to the ZnO surface is substantially stronger than that of AA. This results in increased colloidal stability, leading to slower growth and increased longterm stability for growth using TBAA. Overall most ZnO nanocrystals are sphericaly shaped, and in some cases, irregular morphologies consistent with oriented aggregation (Figure 1) are observed. Minimum estimates for the percentage of particles with morphologies consistent with oriented aggregation (OA%) were determined by counting the number of obvious oriented aggregates with visible lattice fringes divided by the total number of particles in the HRTEM image (with or without lattice fringes). Maximum estimates for OA% were determined by dividing the total number of oriented aggregates with visible lattice fringes by the total number of particles with visible lattice fringes. Maximum and minimum estimates are reported in Table 1. Particles grown at constant conditions (0.625 Zn:OH and 65 °C) show a higher OA% (∼815%) when using TBAA as compared to AA (∼2-3%), and OA% does not increase between the 15 min sample and the 120 min samples, implying that oriented aggregation predominantly occurs during the early stages of growth.

dA/dr 4πr3/3

(2)

Here n(r) is the relative number of particles of radius, r, and plotting n(r) versus r yields a particle size distribution. In order to facilitate comparisons between samples with different average particle sizes, the full widths at half-maximum of the particle size distributions (fwhm) were determined using spectra collected at 60 min and are reported in Table 2 as a percentage of the average diameter ((fwhm/D) × 100). Table 2 shows the fwhm/D × 100 as a function of Zn:OH and surfactant. fwhm/D × 100 for experiments employing TBAA were substantially larger than for those employing AA. This can be attributed to the slower saturation rate for TBAA, which can be discerned by measuring the time until the maximum in absorbance is observed (Figure 3) and to the larger fraction of particles that are oriented aggregates. The maximum absorbance occurs when no new ZnO is being produced and the suspension is saturated with respect to ZnO. Saturation of the absorbance measurements occurs between 1 and 2 min for AA and at 40 min for TBAA. Saturation times were found to be independent of Zn:OH ratio, and the particle size distributions were constant over the reaction time within an experimental error of (2%. 3.2. Modeling ZnO Particle Growth Using the Linear Coarsening Model. The experimental data was fit using three models in order to obtain growth rate constants for ZnO particle growth to elucidate the growth mechanisms controlling nanoparticle size. The first model employed is a simplified version of the classical coarsening model and is employed in a manner similar to that used previously.8-11 Equation 3 represents the simplified coarsening model commonly employed in describing oxide nanoparticle growth using solvothermal conditions8-11 and is referred to hereafter as the linear coarsening model.

rt3 ) r03 + kLt

(3)

In eq 3, rt is the particle radius at time t, r0 is the particle radius at time zero, t is time, and kL is the growth rate constant

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Figure 3. In situ UV-vis spectroscopy of ZnO particle growth using (a) AA and (b) TBAA. Absorbance measurements become saturated for AA between 1 and 2 min and after 40 min for TBAA. These reaction were performed using 0.625 Zn:OH at 65 °C.

for the linear coarsening model. The linear coarsening model, which is typically used to fit only the “linear” portion of the size versus time data, is commonly applied after nucleation is complete and particle growth has begun.8-10,15 In the data described in this work and shown in Figure 4A, growth data from 60 to 360 min were determined to comprise the linear region and used to determine the linear coarsening rate constants for systems containing both AA and TBAA. For ZnO nucleation and growth with AA, nucleation and saturation is complete within 1-2 min of initiation (Figure 3), as discussed above. However, when the linear coarsening model is applied to all but the first 2 min of data, fits are especially poor during the early stages of growth (Figure 4A). The model is a simplification of the classic coarsening model and makes a number of assumptions that lead to a poor description of growth for early times as can be seen when comparing the fits from the different models in Figure 4.17 While this model does not describe the overall growth data well and does not elucidate the mechanisms of ZnO nanoparticle growth beyond its assumption of diffusionlimited coarsening, it is suitable for comparing relative growth rates as a function of solvothermal conditions. In order to further investigate the growth mechanisms at work under these solvothermal conditions, activation energies (Ea) for growth were determined. Experiments were performed at temperatures ranging from 35 to 75 °C. Rate constants for

Figure 4. Growth rate constants vs Zn:OH Ratio. Rate constants (A) k1, (B) k2, (C) kc, and (D) kL are shown to increase with Zn:OH ratio. (9) AA, (green triangle) TBAA, (red triangle) TBAA 40-360 min.

growth were determined by minimizing the unsigned mean error between fitted values and the experimental values determined

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Ratkovich and Penn

TABLE 3: Activation Energies for ZnO Particle Growth Ea (eV) growth system

kL

kc

k1

k2

AA, 0.625 AA, 0.55 TBAA, 0.625 TBAA, 0.55 TBAA, 0.625 (40-360 min) TBAA, 0.55 (40-360 min)

0.39 0.39 0.33 0.39 NA NA

0.17 0.17 0.18 0.19 0.09 0.09

NA NA NA NA NA NA

0.18 0.20 0.15 0.20 0.09 0.09

via in situ particle size measurements. Activation energies for growth determined from the temperature dependence of kL using the Arrhenius equation are shown in Table 3. Activation energies obtained using the linear coarsening rate constants are on the order expected for diffusion-limited reactions10 and show little variation with the different experimental conditions used, suggesting similar growth mechanisms for the various experimental conditions employed here. Rate constants for these systems were found to increase with increasing Zn:OH (Figure 5A). The rate constant for growth by coarsening, kL, is shown as eq 4,18,19

8γVm2cr)∞ kc,L ) 54πηaNA

(4)

where γ is the surface energy, Vm is molar volume, cr)∞ is bulk solubility, NA is Avogadro’s number, η is solvent viscosity, and a is the solvated ion radius. Of the parameters that significantly affect the coarsening rate constant for growth, surface energy, molar volume, solubility, and viscosity are all expected to be constant at a constant temperature and consequently are unlikely to contribute to the change in rate constant for these experimental conditions. The change in rate constant is therefore likely due to the change in the solvation layer surrounding the particle as a result of changing the Zn:OH ratio. An increase in the Zn: OH ratio results in an increase in the concentration of excess Zn2+ present after nucleation. As predicted by double layer theory, smaller concentrations of excess Zn2+ (low Zn:OH) will result in a thicker double layer,20 causing larger impedance for incoming monomers. This results in slower particle growth, as indicated by the decreasing rate constants for growth as a function of Zn:OH ratio. Conversely, a larger excess Zn2+ concentration results in a thinner solvation layer, causing faster growth and larger final particle sizes. 3.3. Modeling ZnO Particle Growth Using the Classic Coarsening Model. Equation 5 represents the classic

Dt ) D0 + kct1/n

(5)

coarsening model.21 This model describes growth solely by coarsening, and Dt is the particle diameter at time t, D0 is the particle diameter at time zero, t is time, kc is the growth rate constant, and n is a parameter that describes the coarsening mechanism for the system. The classic coarsening model was applied to the range of data collected after saturation for both AA and TBAA: 2-360 min for AA and 40-360 min for TBAA. The best fits of the experimental data resulted when using n ) 3, which corresponds to growth by volume-limited diffusion and is consistent with previous results.16,17 Activation energies calculated using kc were found to be on the order of that for diffusion-limited coarsening in the case of AA. Performing a similar calculation for the case of TBAA presents a challenge, since saturation did not occur until after 40-60 min, depending on temperature. Interestingly, the classic coarsening model produces good fits and activation energies

Figure 5. Plots showing particle growth using acetic acid and a Zn: OH ratio of 0.625 at 65 °C. The data was modeled using the following three different models: (A) linear coarsening, (B) classic coarsening, and (C) simultaneous coarsening/oriented aggregation. The fits are shown as solid lines. The unsigned mean error after fitting the experimental data with the model is shown for each point in time.

that are essentially the same for the case of TBAA as for AA when using data from 5 to 360 min (pre- and postsaturation data). Alternatively, the data can be fit using only the postsaturation data (Table 3), but then direct comparison to the experiments using AA is not possible.

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As with the linear coarsening model, rate constants generally increased with Zn:OH for experiments using AA and TBAA. Since kc is of the same form as kL, the increase in kc can be interpreted in a fashion similar to the discussion in section 3.2. 3.4. Modeling ZnO Particle Growth Using the Simultaneous Coarsening Oriented Aggregation Model. The third model employed was proposed by Huang et al.7 and describes growth as simultaneous coarsening and oriented aggregation.

D0(x2k1t + 1) 3

Dt )

(k1t + 1)

+ k2t1/n

(6)

Here Dt is the particle diameter at time t, D0 is the diameter at time zero, k1 is the rate constant for oriented aggregation, k2 is the rate constant for simultaneous coarsening and oriented aggregation, n is a parameter describing the mechanism limiting particle growth, and t is time. This model predicts that growth is initially dominated by oriented aggregation, resulting in very fast growth. As the reaction proceeds, growth by coarsening becomes the more dominant mechanism, eventually becoming the primary mode of growth. Representative fits for each model are shown in Figure 5 for the AA system. Examining the magnitude of the unsigned mean error over the entire data range, the data are best fit using either the classic coarsening model or the simultaneous coarsening and oriented aggregation model. Close examination of the fit and data shows that the fit using the classic coarsening model during the earliest stage of growth is not as good as for the later stages of growth (e.g., after 20 min in Figure 5B). Close examination of the data and fits at the early stages of growth (i.e., the first 20 min of data) shows that the fit using the simultaneous coarsening and oriented aggregation model is somewhat better than using the classic coarsening model. This is consistent with the expectation that oriented aggregation dominates nanoparticle growth at the early stages as discussed earlier. Rate constants for growth for the simultaneous coarsening oriented aggregation model were determined and are plotted versus Zn:OH in Figure 4C,D. In general, k2 increased with Zn:OH ratio. The rate constant k2 is similar to the rate constants for coarsening (kL and kc). In fact, fits using the TBAA postsaturation data (t > 40 min) yielded k2 values that matched kc, which makes sense, because the simultaneous coarsening and oriented aggregation model becomes mathematically equivalent to the classic coarsening model at later times. In addition, the activation energies determined from k2 show the same trends as activation energies determined using kc. Fits using data for experiments employing TBAA present a similar challenge as do fits using the classic coarsening model. As expected, fits using postsaturation data (i.e., t g 40 min) yielded k2 values that were identical to the corresponding kc values. However, when the early growth data is included (i.e., 5-360 min for TBAA experiments) a trend of increasing k1 with increasing Zn:OH is observed. While the fit using the simultaneous coarsening and oriented aggregation model neglects the stage of particle growth leading up to saturation, employing the model may enable a semiquantitative measure of growth by oriented aggregation. Indeed, the increase in k1 with increasing Zn:OH is consistent with a decrease in solvation layer thickness caused by increasing excess Zn2+ (i.e., increasing Zn:OH). Furthermore, OA%, which was determined by HRTEM image analysis, confirmed a relatively high degree of oriented aggregation at the early stages of growth and confirmed that oriented aggregation is more prevalent in ZnO grown with

TBAA as compared to AA (Table 1, Figure 4C). Thus, we assert that the use of the combined model may provide a means by which growth by oriented aggregation may be semiquantitatively detected at the early stages of growth. Ongoing work is aimed at improving the model for cases in which the time to saturation is relatively long. In the case of the simultaneous coarsening and oriented aggregation model, rate constants for oriented aggregation (k1) show no discernible trend as a function of temperature. Likely explanations for this are that the stage of growth dominated by oriented aggregation is short (∼15 min), which effectively means a relatively small number of data points are used in determining the value of k1. Furthermore, no explicit form of this rate constant has been proposed to date. Recently, Penn et al. have experimentally demonstrated that the rate constant for growth by oriented aggregation decreases exponentially with increasing nanoparticle size and have shown that this trend is predicted by DLVO theory.22 Thus, k1 is expected to be strongly dependent on nanoparticle size, which means that k1 will decrease with time. Improved fits to the early stage of nanoparticle growth will likely result with improvements in the models. 4. Conclusions ZnO nanoparticle growth was monitored by in situ UV-vis spectroscopy. In general, nanoparticle growth rates and final particle sizes increase with increasing Zn:OH. Experimental data was fit using the commonly employed linear coarsening model, the classical coarsening model, and the simultaneous coarsening and oriented aggregation model. Both the classic coarsening and the simultaneous coarsening and oriented aggregation models produced reasonable fits. In the case of the classic coarsening model, a value of n ) 3, which is consistent with diffusion-limited coarsening, produced the best fit. However, the simultaneous coarsening and oriented aggregation model fit better at early stages of growth, which is indicative of a substantial contribution to growth by oriented aggregation. HRTEM characterization confirmed oriented aggregation at the early stages of growth. Coarsening growth rate constants and final particle sizes were smaller for experiments employing TBAA as compared to AA. Finally, the growth rate constants for growth by oriented aggregation were substantially larger for experiments employing TBAA as compared to AA, and the degree of oriented aggregation as determined from the HRTEM images demonstrated the same trend. Although the simultaneous coarsening and oriented aggregation model neglects the stage of particle growth leading up to saturation, employing the model may enable a semiquantitative measure of growth by oriented aggregation. Acknowledgment. We acknowledge the University of Minnesota and the National Science Foundation (Career-036385 to R.L.P. and MRI EAR-0320641 for the purchase of TEMs) for funding. References and Notes (1) O’Regan, B.; Gra¨tzel, M. Nature 1991, 353, 737. (2) Yang, M.; Wang, D.; Peng, L.; Zhao, Q.; Lin, Y.; Wei, X. Sens. Actuators B 2006, 117, 80-85. Rout, C. S.; Raju, A. R.; Govindaraj, A; Rao, C. N. R. Solid State Commun. 2006, 136-138. (3) Colvin, V. L.; Schlamp, M. C.; Alivisatos, A. P. Nature 1994, 370, 354. (4) Westermark, K.; Rensmo, H.; Siegbahn, H.; Keis, K.; Hagfeldt, A.; Ojamae, L.; Persson, P. J. Phys. Chem. B 2002, 106, 10102-10107. (5) Wang, Z. L. J. Phys. Condens. Matter 2004, 16, R829-R858. (6) Penn, R. L. J. Phys. Chem. B 2004, 108, 12707-12712.

14104 J. Phys. Chem. C, Vol. 111, No. 38, 2007 (7) Huang, F.; Zhang, H.; Banfield, J. J. Phys. Chem. B 2003, 107 (38), 10470-10475. (8) Wong, E. M.; Bonevich, J. E.; Searson, P. C. J. Phys. Chem. B 1998, 102, 7770-7775. (9) Hu, Z.; Escamilla Ramirez, D. J.; Heredia Cervera, B. E.; Oskam, G.; Searson, P. C. J. Phys. Chem. B 2005, 109, 11209-11214. (10) Hu, Z.; Oskam, G.; Penn, R. L.; Pesika, N.; Searson, P. C.; J. Phys. Chem. B. 2003, 107, 3124-3130. (11) Hu, Z.; Herrera Santos, J. F.; Oskam, G.; Searson, P. C.; J. Colloid Interface Sci. 2005, 288, 313-316. (12) Hu, Z.; Oskam, G.; Searson, P. C. J. Colloid Interface Sci. 2003, 263, 454-460. (13) Bahnemann, D. W.; Kormann, C.; Hoffmann, R. J.; J. Phys. Chem. 1987, 91, 3789-3798.

Ratkovich and Penn (14) Meulenkamp, E. A.; J. Phys. Chem. B 1998, 102, 5566-5572. (15) Brus, L. E. J. Phys. Chem. B 1986, 90, 2555. (16) Pesika, N. S.; Stebe, K. J.; Searson, P. C. J. Phys. Chem. B 2003, 107, 10412-10415. (17) Talapin, D. V.; Rogach, A. L.; Haase, M.; Weller, H. J. Phys. Chem. B 2001, 105, 12278-12285. (18) Lifshitz, I. M.; Slyozov, V. V. J. Phys. Chem. Solids 1961, 19, 35. (19) Wagner, C. Z. Electrokem 1961, 65, 581. (20) Jolivet, J.-P. Metal Oxide Chemistry and Synthesis-From Solution to Solid State; John Wiley & Sons: Chichester, 2003; pp 257-283. (21) Banfield, J. F.; Zhang, H. ReV. Miner. Geochem. 2001, 44, 1-58. (22) Penn, R. L.; Erbs, J.; Tanaka, K., J. Phys. Chem. C Submitted for publication.