Experimental Validation of the Geometrical Selection Model for

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Experimental Validation of the Geometrical Selection Model for Hydrothermally Grown Zinc Oxide Nanowire Arrays Tammy Y. Olson,† Alexander A. Chernov,† Brent A. Drabek,†,‡ Joe H. Satcher, Jr.,† and T. Yong-Jin Han†,* †

Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, 7000 East Ave L-235, Livermore, California 94550, United States ‡ Department of Chemistry, 2355 Fairchild Drive, Suite 2N225, United States Air Force Academy, Colorado 80840-6230, United States ABSTRACT: Zinc oxide nanowire arrays were hydrothermally grown on a Si(100) substrate coated with randomly oriented seed crystallites to characterize the process of geometrical selection. The theory suggests that randomly oriented rod-like crystallites can be grown into a film or array of nanowires with the maximal growth rate direction approximately normal to the substrate; in the case of ZnO, this is the c-axis direction. To examine this growth phenomenon experimentally, ZnO nanowire arrays with a random initial orientation were grown, and the number of wires that survived the geometrical selection up to a certain distance, h, from the substrate was measured. The resulting number density of the survived wires decreased as h−0.8, while the geometrical selection model predicted the decrease to be ∼h−1. As developed originally, the model can also apply universally to other three-dimensional (3D) crystal ensembles besides ZnO. Understanding geometrical selection will allow assessment of if and when this theory can be used to obtain films with certain characteristics, such as the orientation and scattering of the nanowire array, that is relevant for specific applications. KEYWORDS: zinc oxide, nanowires, geometrical selection, texturing, modeling, array, thin film



INTRODUCTION Zinc oxide belongs to the hexagonal crystal system where the most thermodynamically stable crystal habit exhibits an asymmetric structure. A crystal habit is defined by the crystal faces and their relative areas, which are proportional to their surface energies (thermodynamic) or growth velocities (kinetic), and describes the material’s overall shape. The two basal surfaces of (0001̅) and (0001) planes are built of oxygen or zinc ions, respectively, and the (0001) plane exhibits the fastest crystal growth velocity (V⟨0001⟩ > V⟨01−10⟩ > V⟨0001̅⟩).1 The absence of a center of inversion along the [0001] direction,2 surface polarity of ZnO’s c-axis,3 and screw dislocation driven growth,4−6 are a number of reasons why ZnO favorably grows in one dimension to readily create a nanowire structure. Although the growth mechanism of an individual nanowire is well understood, the growth of an array of nanowires is markedly more rich due to the interaction of each nanowire with its neighbors. In the current study, we focused on the synthesis and growth mechanism of nanowire arrays that are used as a platform for many applications. ZnO’s one-dimensional structure, along with its many desirable materials properties,7 is advantageous for many applications such as dye-sensitized solar cells,8 lasers,9,10 photocatalysis,11 waveguides,12 nanogenerators,13 photodetectors,14 and more. In many of the applications utilizing nanowire arrays, the nanowire’s one-dimensional structure provides the © 2012 American Chemical Society

directionality for migration of electrons (in dye-sensitized solar cells), electromagnetic radiation (in waveguides), and excitons (in lasers). Hence, synthesizing highly oriented structures is of interest. Various groups have investigated the effect of the substrate on the orientation of ZnO nanowire arrays. Cheng et al. grew ZnO nanorods by pulsed laser deposition on glass, Si(111), 6H-SiC(0001), and sapphire(0001). The best ZnO alignment was found on sapphire(0001), explained by its having the best epitaxial relationship to ZnO.15 ZnO seeds of varying orientation were investigated for the affect of orientation on ZnO nanorod formation, and naturally, ZnO nanorods grown from the most oriented seed layer (i.e., a layer expressing a dominant c-axis orientation) had the best vertical alignment.16 Yet, oriented ZnO nanowires have been successfully grown without the lattice match or oriented seed layer, for example, on amorphous glass.17 Vayssieres et al. grew oriented ZnO on substrates of different types and varying degrees of crystallinity and found that they were still able to produce well aligned and oriented ZnO nanowires.18 Similarly, Special Issue: Synthetic and Mechanistic Advances in Nanocrystal Growth Received: March 2, 2012 Revised: July 3, 2012 Published: July 12, 2012 1363

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Figure 1. Top views of ZnO nanowires at the following growth times: (a) 0 min, ZnO seed layer, (b) 20 min, (c) 40 min, (d) 60 min, (e) 180 min, (f) 360 min, (g) 720 min, and (h) 1440 min. All images are at the same magnification of 100K. (i) Graphical representation of crystal density over growth time.

and has the ability to grow on different types of substrates.41−43 Specifically, we utilized a silicon wafer coated with a ZnO seed layer, which was composed of randomly oriented crystallites from which the nanowires grew.41,42,44−46 Given that the crystal habit of ZnO is an intrinsic property of the material, the concept of geometrical selection was understood to apply to nanowire array formation regardless of the method of synthesis. Previous work has recognized the effect of the substrate orientation on the final orientation of the nanowires.15−20 We wish to illustrate here that oriented nanowires can still be formed from noncrystalline substrates, as it follows from the geometrical selection model. The ensemble differences can have a profound effect on the fundamental properties of ZnO,47,48 and understanding the principles that govern the growth of nanowire ensembles will enable the ability to predict the film thickness necessary to obtain a particular degree of mutual orientation of nanowires, allowing the controlled formation of the structure from the bottom up to obtain the desired properties for a specific application.

perpendicular nanowires were shown to grow regardless of how the initial seed layer was made,19 and ZnO nanowires from a single crystalline and polycrystalline ZnO surface showed that both attained well aligned nanowire arrays, although the polycrystalline substrate first had randomly grown crystals near the surface.20 To explain this discrepancy, a systematic study of ZnO nanowire growth was performed. The concept of geometrical selection using experimental results of ZnO nanowires grown in a batch setup is used to explain the aligned growth behavior of ZnO nanowires. Geometrical selection is a growth phenomenon that has been observed in thin films,21 shells,22 and minerals.23 Randomly oriented seeds evolving into an oriented thin film by geometrical selection are characterized by three stages of growth: isolated, competitive, and parallel.23 During the isolated stage, crystallites are randomly oriented and are represented by the initial seed layer. As the crystallites are allowed to grow, they begin to impinge on one another and enter the competitive stage where those crystallites without optimal orientation are selectively eliminated. The duration of the competitive stage depends on various factors such as the crystal habit and relative growth rates of the crystal faces.24 The parallel growth stage is established when the surviving crystals continue to grow without further hindrances due to neighboring crystals. While numerous attempts have been made to model this growth behavior,24−26 we focused on the original work by Kolmorgorov27 and Gray28 to compare with experimental results. Many methods exist for synthesizing uniform, ordered, and highly crystalline ZnO nanowires from a surface, including chemical vapor deposition, pulsed laser deposition, vapor− liquid−solid processes, and electrodeposition.29−34 Epitaxial growth of ZnO is possible using a material with close crystal match such as galium nitride, sapphire, spinel, and single crystal ZnO.10,20,35−40 We focused on a solution-based, hydrothermal method, which is markedly simpler, low temperature, scalable,



EXPERIMENTAL SECTION

Materials and Instrumentation. Zinc sulfate (ACS grade) and ammonium chloride (ACS grade) were purchased from EMD Chemicals, zinc acetate (min. 98%) and ethanolamine (min. 98%) were purchased from Sigma Aldrich, and 2-methoxyethanol (ACS, 99.3+%) was purchased from Alfa Aesar. The reagents were used as received and 18.2 MΩ water was used when needed. A Laurell Technologies spin coater was used to fabricate the ZnO thin films, while a JEOL 7401-F scanning electron microscope operated at 5−10 keV and a Bruker D8 Advance X-ray diffractometer were used to analyze the structure and crystallinity of ZnO. For Raman spectroscopy, a Thermo Electron Nicolet Almega XR Dispersive Raman spectrometer was utilized with 16% laser power (approximately 1.7 mW) and 50 μm pinhole. ZnO Thin Film (Seed Layer). A 3-in. (100) silicon wafer was cut into square pieces of approximately 2 cm in length using a diamond tip pen. These substrates were then washed by sonicating them consecutively in 1 M nitric acid, water, acetone, and methanol and 1364

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subsequently dried with a nitrogen gun. The procedure by Znaidi, et al. was followed to spin coat a ZnO seed layer on the silicon substrates.49 A 0.75 M zinc acetate solution in 2-methoxyethanol (total volume of 10 mL) was prepared in a vial and heated to 80 °C in an oil bath. A predetermined volume of ethanolamine was then added to the solution to attain a zinc/amine ratio was 1:1. Upon the addition of ethanolamine, the solution was vortexed to ensure complete dissolution of the zinc acetate solids. After aging the solution for 2 h in the oil bath, the solution was cooled to room temperature and filtered using a 0.45 μm cellulose membrane. The filtered, zinc solution was spin coated on top the silicon wafer at 3000 rpm for 30 s. Two layers were applied, and a hot plate heated to 135 °C ± 5 °C was used after each layer application to evaporate the solvent. The coated silicon substrates were finally baked at 550 °C for 2 h using a temperature ramp rate of 40 °C/min. After the thin film substrates were baked and cooled, they were cut into smaller, rectangular pieces of approximately 3 mm × 1 cm to use for the nanowire growth experiments. ZnO Nanowire Growth. The ZnO nanowire growth solution was prepared by slightly modifying a published procedure.50 A solution with final concentration of 0.01 M ZnSO4 and 0.2 M NH4Cl was prepared by first dissolving the ZnSO4 into 1/3 the total volume and dissolving the NH4Cl into the remaining 2/3 volume separately. The pH of the NH4Cl solution was adjusted to 9.50 using 10 M NaOH. After the pH adjustment, the ZnSO4 solution was quickly added to the NH4Cl solution being stirred on a stir plate. The final pH was measured to be close to 9.3. The growth solution (2 mL) was then added to a 1-dram vial and the ZnO thin film substrate was placed inside the vial with the seeds facing down. The nanowire growth was initiated by placing the vial in a 60 °C oven. We have found that the growth solution was extremely sensitive to mixing order and pH. If care was not taken during the preparation, a white, fluffy precipitation formed, which was identified by X-ray diffraction (XRD) as simonkolleite (Zn5(OH)8Cl2H2O). Precipitation in the growth solution adversely affected the ZnO’s ability to grow long nanowires, as the growth nutrients were consumed by the precipitation. One piece of thin film substrate per growth time of 0 min, 20 min, 40 min, 1 h, 3 h, 6 h, 12 h, and 24 h was used. We made certain that these ZnO thin film samples were cut from the same piece of silicon wafer coated with the ZnO seed layer. Small differences in wafer geometry, solvent evaporation, etc. can affect the ZnO thin film application, so using the same source of ZnO seeds ensured that direct comparison between the ZnO samples grown at different times was possible. After the nanowire growth for a specified time, the samples were taken out of the oven, rinsed with water, and left to dry. At least 50 separate length measurements were taken from the scanning electron microscopy (SEM) images, and at least five different areas on the substrate were used to measure the nanowire density. Photoshop and ImageJ were used to accurately obtain the length and density values.

each growth time is shown in Figure 2. The increasing peak signal for the c-axis illustrates the selective growth of the

Figure 2. XRD of ZnO nanowires at the following growth times: (a) 3, 6, 12, and 24 h, (b) 40 and 60 min, and (c) 0 and 20 min. ZnO seed layer shows peaks corresponding to all three low-index faces. Increase in c-axis peak (highlighted) indicates selective growth of ZnO nanowires with c-axis perpendicular to surface.

crystals with optimal orientation (their c-axis normal to the surface). Up to 1 h of growth, XRD peaks corresponding to (100) and (101) are seen. After 3 h of growth, only the c-axis peak is generated. Each ZnO sample was cut in half to measure the nanowire lengths, as shown in Figure 3. The nanowires grew to a maximum length of 3 μm, but interestingly, the length decreased between 12 and 24 h of growth. While we expect the nanowire growth to level off as the growth nutrients are being consumed, decreasing nanowire length suggests that dissolution is taking place. Geometrical Selection. Various groups have observed the growth phenomenon where optimally oriented nanowires continue to grow (in the case of ZnO, with their c-axis perpendicular to the surface) whereas misaligned crystals are impinged by their neighbors and physically limited.51−53 Decreasing crystal density over time is associated with this growth event, but no one has attributed this to geometrical selection. Theoretical models for this phenomenon have existed since the 1940s but no experimental comparison has been made for a nanowire system to the best of our knowledge. The density of nanowires during growth provides a quantitative value of the surviving crystals. A relationship between the number of surviving crystals, T, and the distance from the growth substrate, h, was developed by Kolmorgorov27 and stated as c T (h , λ ) = as hλ → ∞ (1) hλ



RESULTS AND DISCUSSION Nanowire Growth with Time. Top view SEM images of the ZnO samples grown at different times are shown in Figure 1. At 0 min, the ZnO seed layer with a density of approximately 965 crystals/μm2 can be seen with crystallites on the order of 50 nm in diameter. With longer growth times, the crystallites began to resemble nanowire structures, first with needle-like ends, which developed into flat tops. The change in morphology is indicative of the reducing supersaturation with time, where the flat tops form due to the reduced growth rate of the c-axis relative to the other facets. At 24 h of growth, the beginning of secondary nucleation was seen as small dots on the basal plane. Figure 1 includes a graph illustrating a quantitative measurement of the nanowire density over growth time, which depicts the density quickly diminishing by an hour of growth. Within an hour, the density falls drastically from 965 crystals/μm2 to 121 crystals/μm2 (87% of the original seeds have been eliminated). The XRD of the nanowire samples at

where λ is the initial crystal density and c is a geometry constant. As hλ approaches infinity, the relationship shown in 1365

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in the two-dimensional case). Deriving from the work by Laemmlein54 and later efforts by Kolmorgorov, Gray simulated the simultaneous growth of randomly oriented and spaced needle-like crystals from an infinite line grown in a 2D plane,28 as shown in Figure 4a. This simulation essentially depicts the geometrical selection phenomenon and appears very similar to the sideways image of a nanowire array, as shown in Figure 4b. The chaotic region just above the line of initial growth is commonly observed in growth experiments and represents the competitive growth stage of geometrical selection. Even though the region above the competitive region is defined as parallel, competition will still continue infinitely as the wire array is not a true single crystal. When crystals of random orientation are allowed to grow simultaneously, the crystals with their fastest growth facet perpendicular to the substrate grow uninhibited while their neighbors of less optimal orientation collide into one another and are eventually blocked from growing. In the case of ZnO, the c-axis is the fastest growth facet. Therefore, crystallites with their c-axis oriented perpendicular to the substrates are the ones that survive the growth process. By recording the height at which the crystals became truncated, Gray was able to generate the probability of a crystal with a given orientation to attain a specific height (Figure 4c). The crystal orientation was identified by β, which was the angle measured from the perpendicular line. As expected, when β is 0°, the probability of the crystal to attain any height is maximal, since in this scenario, the crystal is oriented perpendicularly to the substrate. As β begins to deviate from 0°, the curve begins to show an exponentially decaying behavior. When β reaches 90°, the probability of the crystal to become any height is essentially zero, which depicts a crystal oriented with its growth facet sideways and blocked from growing due to its neighbors. A nanowire that was impinged by a neighbor was found at 1 h of growth and shown in Figure 4d. The orientation and height of this nanowire was measured to compare with the probability calculations. The impinged nanowire was oriented at 25° from the perpendicular line and found to have grown 345 nm which is 11% of the total nanowire array height after 24 h (3 μm). The side view image of the nanowires shown in Figure 4d was taken from a sample that was cleaved in half and imaged with SEM. We note that the exact angle of the nanowire with respect to the perpendicular line depends on how the nanowire is oriented in the imaging plane. Since the SEM image depicts a 2D surface, the measured angle of 25° is an approximation, since it does not take into account possible deviations of the nanowire from the plane from which it was measured. These measurements are not exact and are an approximation, so that comparison with theory was possible. According to the probability calculation shown in Figure 4c, the probability approaches zero at a value of 70 on a scale of 100. An experimental measurement of 11% falls much lower than this predicted calculation. A lower probability of survival for the experimental nanowire compared to the simulation suggests that additional factors influence the survival of a crystal. The discrepancy can be due to a number of reasons such as initial crystal density, intrinsic crystal growth properties of ZnO, and most significantly, on the difference between a 2D (simulation scenario) and three-dimensional (3D) growth (experimental scenario). In a 2D setup, a wire is simulated to grow and is confined to a single plane (2D), where the parameter is the initial crystal density, λ, and the variable is height, h. In a 3D system, a wire is not confined to grow in a single plane; the parameters are λ and the thickness of the wire, with height, h, as

Figure 3. Side views of ZnO nanowires at the following growth times: (a) 0 min, ZnO seed layer, (b) 20 min, (c) 40 min, (d) 60 min, (e) 180 min, (f) 360 min, (g) 720 min, and (h) 1440 min. All images are at the same magnification of 15K. (i) Graphical representation of nanowire length over growth time.

eq 1 holds true. In other words, eq 1 describes the system more precisely when the height, h, is large compared to the average distance between the nuclei (1/λ), which is equivalent to stating that λh ≫ 1. By taking the limit as hλ approaches infinity, the resulting function describes the approach to an advanced stage of geometrical selection in mathematical terms. The geometry constant, c, has no physical meaning; it is a collection of constants depending on the system of interest and typically lies between 1.1 and 1.2, as defined originally by Kolmorgorov. It is neither a parameter nor variable. The unit for λ in the twodimensional (2D) case is cm−1 and that for h is cm, which cancels the units under the square root. In three dimensions, the initial crystal density, λ, will have units of cm−2 (versus cm−1 1366

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Figure 4. (a) Simulation of randomly oriented crystals grown simultaneously. (b) SEM image of nanowires to compare with Figure 4a. Dashed lines mark the isolated, competitive, and parallel regions. (c) Calculated probability, P, of a crystal attaining a height, h, with an orientation, β. Star and red line corresponds to nanowire analyzed in part d. (d) SEM image of ZnO nanowires grown at 1 h. Dashed line outlines a nanowire, which has been impinged by its neighbor. At an orientation of 25°, the nanowire reached 11% of the total height attained by the nanowire array. The simulation in part c predicted a growth of close to 70%, which is much higher than nanowire shown in part d. (Parts a and c reprinted with permission from ref 28. Copyright 1984, SpringerLink.)

the variable. The additional parameter of wire thickness in the 3D case is an important distinction. Infinitely thin wires in the 2D case will always intersect eventually, whereas in the 3D case, they do not. In three dimensions, the wires are not confined to a single plane and hence their chance of intercepting one another depends on the wire thickness. The 3D scenario is more consistent with an experimentally grown wire array. There is currently no distribution function (as shown in Figure 4c) for a 3D system, so experimental comparison can only be made with simulation performed under 2D conditions. Kolmorgorov developed eq 1 for 2D growth as simulated by Gray, but he also formulated a relationship for 3D growth as stated as

T (h , λ ) =

c λh

(2)

Examination of the two equations indicates that, by graphing the natural log of the number of surviving crystals (i.e., density), ln(T), against the natural log of the inverse of height, ln(1/h), the slope of this line will equal the exponential factor of h. In the case of 2D growth, this factor will be 0.5 (as depicted in eq 1), where as in 3D growth, this factor would be 1 (as depicted in eq 2). Figure 5a shows the graph of ZnO density versus ZnO nanowire length, and Figure 5b corresponds to the ln(density) versus ln(1/h). Fitting the graph to a linear line generated a slope value of 0.8. The fact that the slope is less than 1 indicates that there was less geometrical selection than theory anticipated, or in other words, the graph shown in Figure 5a has a lesser degree of asymptotic behavior than theory predicts. There are a number of reasons why the experimental data reflected this deviation from theory. First of all, for the 3D case, Kolmorgorov employed a system of infinity thick wires, in which case the slope will be 1. Since the experimental ZnO nanowires have a finite thickness, the slope will be less than one. Second, the theory applies to an advanced stage of geometrical selection. As mentioned, the current batch experimental setup prevents the nanowires from growing any longer. In a continuous flow setup where the nanowires are permitted to grow longer, the slope value is expected to approach closer to 1. Third, the degree of asymptotic behavior

Figure 5. (a) ZnO Density as a function of ZnO NW length. (b) ln(density) versus ln(1/h). Slope of the line approximated the extent to which experimental results followed model based on geometrical selection.

depends on the crystal diameter with respect to the intercrystalline distance. For infinitely thin wires in a 3D system, they do not intersect, in which case there exists an independence of crystal density from crystal height. Without the wires ever intersecting one another, no impingement occurs and hence, no crystals are selectively eliminated. Therefore, when the crystal diameter is much smaller than the intercrystalline distance, the asymptotic behavior seen in geometric selection becomes less pronounced. Fourth, crystal “thickening” must be considered in 3D growth. This effect can be seen by the increase in crystal diameter as growth proceeds. While the [0001] direction is the fastest growing, the {101̅0} faces of ZnO continue to grow, contributing to the increasing diameter of the nanowire over time. In the current case, the crystallites start with a diameter of approximately 50 nm and, by 24 h of growth, the diameter doubles to approximately 100 nm. Crystals that have a higher thickening rate will exhibit more 1367

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zinc ions were consumed and the zinc ion concentration at 24 h was approximated at 7.1 mM. We note here that even with a relatively high zinc ion concentration after 24 h of growth, the nanowires that have collided stay prevented from growing even with access to the still remaining growth nutrients in the solution. The disappearance of the nanowires of less optimal orientation continues to be hindered by geometrical selection and not due to a diffusion limitation of the growth nutrients to those now embedded nanowires. Visual MINTEQ was utilized to simulate the solution chemical species in solution as the zinc ions were consumed during ZnO nanowire formation. The chemical species with a positive saturation index was graphed as a function of zinc concentration and shown in Figure 6. For the

geometrical selection. The higher the anisotropy of the relative growth rates, the sharper the decline in crystal density.24 Lastly, we cannot rule out the possibility that geometrical selection has already begun to take place during the formation of the ZnO seed layer. The XRD spectrum of the ZnO seeds (Figure 2a) exhibited all three low-index facets; however, the intensity ratios between the three low index XRD peaks are different from what is expected from randomly oriented ZnO powder, which is truly random. Hence, the analysis did not take into account the selection process that may have occurred during the ZnO seed formation. Texturing of a ZnO seed layer was observed and found to be dependent on the baking temperature when conversion of the precursors to ZnO takes place.42,55−57 Investigating the seed layer formation in more detail may reveal whether geometrical selection is part of the mechanism for the texturing of the seed layer. A slope value of greater 0.5 indicates that the system is not represented by a 2D system, as expected. This result affirms the discrepancy in the probability that was measured and compared in Figure 4c and d. To summarize, we found the experimental results of ZnO nanowire growth to match Kolmorgorov’s theory of geometrical selection in three dimensions with the degree of selection dependent on (1) crystal height (i.e., growth opportunity to attain advanced stage of geometrical selection), (2) crystal diameter with respect to intercrystalline distance, (3) thickening rate of the crystals, and (4) degree of randomness for the starting seed layer. By systematically investigating the growth process of randomly oriented ZnO crystallites, we found that geometrical selection is a viable model that provides a unifying explanation of why an ordered array of nanowires can arise from a substrate regardless of the substrate’s material, crystallinity, and orientation. Certainly, the substrate can influence the nanowire growth by providing a means for the initial crystal to orient itself by the epitaxial effect. For instance, ZnO that is grown epitaxially on a substrate such as GaN will see less geometrical selection in order to achieve highly oriented nanowire arrays. However, randomly oriented crystals on any substrates can still produce highly aligned ZnO nanowire arrays due to geometrical selection process by exclusively eliminating the growth of crystals that are not optimally aligned. In both cases however, the end result is an oriented nanowire array; hence, solely analyzing the final structure’s orientation will not determine the influence from the substrate. By analyzing the nanowire density and height over time (i.e., graphing ln(density) versus ln(1/h)), a quantitative measurement of the degree of geometrical selection can be determined, and a more precise comparison of the effect of growth substrate can be made. Implications of Batch Growth. Due to the fact that the geometrical selection theory is best applied to an advanced stage of growth, it was crucial for our nanowire system to have the ability to grow to sufficient heights. However, we encountered limitations in a batch setup, which prohibited the continued growth of the ZnO nanowires even while high zinc ion concentration remained. To address this in more detail and in order to understand the solution condition during the growth of the zinc oxide nanowires, an approximation of the zinc concentration after 24 h of growth was made. The zinc oxide nanowire array was imagined as a solid block with an area of the substrate and thickness equal to the average height of the nanowires at 24 h. Based on this calculation, 28% of the starting

Figure 6. Saturation indexes of zincite and zinc hydroxide species calculated by Visual MINTEQ.

concentration that was calculated for a growth time of 24 h, the saturation index for both zincite and zinc hydroxide species is still positive, indicating supersaturation. Due to the fact that the zinc nanowire length starts to level even with a supersaturated system, we believe poisoning of the basal plane is taking place. This possibility concurs with the presence of secondary nucleation that forms at 24 h of growth. Upon further nanowire growth of up to 72 h, a substantial amount of secondary nucleation was found. The secondary nucleation was seen as a layer grown directly on top of the nanowire array with sharp, razor-like morphology. This layer was analyzed with SEM, XRD, and Raman spectroscopy, as shown in Figure 7. Only zincite XRD peaks were identified; however, there are a number of reasons why a different zinc specie could not be detected: there may not have been enough material present, the XRD peaks from the secondary growth could be eclipsed by the strong zincite peaks and unable to be resolved from the background, and the secondary growth may be of amorphous structure in nature. For further analysis, Raman spectroscopy was also conducted and shown in Figure 7c. ZnO Raman peaks58 at 334 and 437 cm−1 are present, as well as a peak at 388 cm−1, which is attributed to the Zn−OH bond.59 The O− H vibration peak60 expected at 3500 cm−1 was not observed; however, this is possibly due to the detector sensitivity at that range. From the weak Zn−OH Raman peak, we have tentatively assigned the secondary specie to be of a zinc hydroxide specie. Since this Zn−OH peak is very weak and not always present, possibly due to very little material with respect to the ZnO, a conclusive identification is ongoing. A number of other Raman peaks were observed and attributed to the phonon modes of silicon.61 The poisoning theory has a number of implications, for instance, the limitation in nanowire height even with zinc oxide supersaturation. A drawback of a batch process is the changing solution condition with time, which contributes to the nonconstant growth rate as depicted in Figure 3. The growth rate is initially quite stable at 8 nm/min until 6 h. After 6 h, the 1368

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Figure 7. (a) SEM of ZnO nanowires grown for 72 h showing jagged secondary growth. (b) XRD spectrum of sample shown in part a. Zincite peaks are seen. (c) Raman spectrum of sample shown in part a. ZnO and Zn−OH peaks are observed.

nanowire length levels off drastically. The drawback of a batch process can be mitigated as shown by Richardson et al. who developed a continuous circulation reactor to maintain a steady state condition to obtain constant nanowire growth rate.62 Another outcome worth noting from Visual MINTEQ is the supersaturation of four different zinc hydroxide species even at the start of nanowire growth. Based on the SEM results, the onset of secondary nucleation is delayed. Visual MINTEQ is based on thermodynamic data, and hence, the absence of zinc hydroxide at the beginning of zinc oxide growth was initially speculated to be due to kinetic limitation. We tested this theory by increasing the growth solution volume from 2 to 10 mL. If the zinc hydroxide formation were kinetically limited, we expected secondary nucleation to occur at 24 h, regardless of the change in volume. Figure 8 shows the SEM images of ZnO nanowires grown in 10 mL of volume at growth times of 24 h, 48 h, and 72 h. At 2 mL of solution volume, the onset of secondary nucleation began at 24 h (shown in Figure 1h). At 10 mL of solution volume, the onset of secondary nucleation begins at 48 h of growth. This observation suggested that, rather than a kinetically driven event, the secondary nucleation occurs due to changes in solution (i.e., decreasing zinc concentration) as ZnO is being formed. At 24 h of growth with 10 mL of growth solution, the nanowire length was more than double in height, measured at 6.52 μm, compared to the sample grown for 24 h with 2 mL of solution. At 48 h of growth with 10 mL of growth solution, the nanowires decreased in height to 5.15 μm. Decrease in height was also observed for the growth series with 2 mL of growth solution, except this occurrence was between 12 and 24 h of growth. When the zinc concentration begins to decrease during ZnO nanowire formation, a sequence of nanowire dissolution followed by secondary nucleation is observed. In a batch setup,

Figure 8. ZnO nanowires in a larger solution volume grown for (a) 24 h (inset: sideways view), (b) 48 h (inset: sideways view), and (c) 72 h. Secondary nucleation begins to show at 48 h of growth.

the changing solution conditions during growth is believed to contribute to a series of complex solution chemistry, resulting in poisoning of the ZnO surface and ultimately secondary nucleation. 1369

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(13) Wang, Z. L.; Song, J. H. Science 2006, 312, 242−246. (14) Lin, C. C.; Lin, W. H.; Li, Y. Y. J. Nanosci. Nanotechnol. 2009, 9, 2813−2819. (15) Cheng, H. M.; Hsu, H. C.; Yang, S.; Wu, C. Y.; Lee, Y. C.; Lin, L. J.; Hsieh, W. F. Nanotechnology 2005, 16, 2882−2886. (16) Baruah, S.; Dutta, J. J. Sol−Gel Sci. Technol. 2009, 50, 456−464. (17) Zhang, H. Z.; Sun, X. C.; Wang, R. M.; Yu, D. P. J. Cryst. Growth 2004, 269, 464−471. (18) Vayssieres, L.; Keis, K.; Lindquist, S. E.; Hagfeldt, A. J. Phys. Chem. B 2001, 105, 3350−3352. (19) Guo, M.; Diao, P.; Cai, S. M. J. Solid State Chem. 2005, 178, 1864−1873. (20) Kawano, T.; Yahiro, J.; Maki, H.; Imai, H. Chem. Lett. 2006, 35, 442−443. (21) Yarbrough, W. A.; Messier, R. Science 1990, 247, 688−696. (22) Ubukata, T. Palaeontology 1994, 37, 241−261. (23) Dickson, J. A. D. J. Sediment. Petrol. 1993, 63, 1−17. (24) Rodriguez-Navarro, A.; Garcia-Ruiz, J. M. Eur. J. Mineral. 2000, 12, 609−614. (25) Rodriguez-Navarro, A. B. Thin Solid Films 2001, 389, 288−295. (26) Thijssen, J. M.; Knops, H. J. F.; Dammers, A. J. Phys. Rev. B 1992, 45, 8650−8656. (27) Kolmorgorov, A. N. Dokl. Akad. Nauk SSSR 1949, 65, 681−684. (28) Gray, N. H. Math. Geol. 1984, 16, 91−100. (29) Park, W. I.; Yi, G. C.; Kim, M. Y.; Pennycook, S. J. Adv. Mater. 2002, 14, 1841−1843. (30) Wu, J. J.; Liu, S. C. Adv. Mater. 2002, 14, 215−+. (31) Sun, Y.; Fuge, G. M.; Ashfold, M. N. R. Chem. Phys. Lett. 2004, 396, 21−26. (32) Wang, X. D.; Summers, C. J.; Wang, Z. L. Nano Lett. 2004, 4, 423−426. (33) Yang, P. D.; Yan, H. Q.; Mao, S.; Russo, R.; Johnson, J.; Saykally, R.; Morris, N.; Pham, J.; He, R. R.; Choi, H. J. Adv. Funct. Mater. 2002, 12, 323−331. (34) She, G. W.; Zhang, X. H.; Shi, W. S.; Chen, H.; Fan, X.; Chang, J. C. J. Nanosci. Nanotechnol. 2009, 9, 1832−1838. (35) Yan, M.; Zhang, H. T.; Widjaja, E. J.; Chang, R. P. H. J. Appl. Phys. 2003, 94, 5240−5246. (36) Fons, P.; Iwata, K.; Yamada, A.; Matsubara, K.; Niki, S.; Nakahara, K.; Tanabe, T.; Takasu, H. Appl. Phys. Lett. 2000, 77, 1801− 1803. (37) Fan, H. J.; Fleischer, F.; Lee, W.; Nielsch, K.; Scholz, R.; Zacharias, M.; Gosele, U.; Dadgar, A.; Krost, A. Superlattices Microstruct. 2004, 36, 95−105. (38) Kim, J. H.; Kim, E.-M.; Andeen, D.; Thomson, D.; DenBaars, S. P.; Lange, F. F. Adv. Funct. Mater. 2007, 17, 463−471. (39) Andeen, D.; Loeffler, L.; Padture, N.; Lange, F. F. J. Cryst. Growth 2003, 259, 103−109. (40) Richardson, J. J.; Lange, F. F. Cryst. Growth Des. 2009, 9, 2570− 2575. (41) Greene, L. E.; Law, M.; Goldberger, J.; Kim, F.; Johnson, J. C.; Zhang, Y. F.; Saykally, R. J.; Yang, P. D. Angew. Chem., Int. Ed. 2003, 42, 3031−3034. (42) Greene, L. E.; Law, M.; Tan, D. H.; Montano, M.; Goldberger, J.; Somorjai, G.; Yang, P. D. Nano Lett. 2005, 5, 1231−1236. (43) Greene, L. E.; Yuhas, B. D.; Law, M.; Zitoun, D.; Yang, P. D. Inorg. Chem. 2006, 45, 7535−7543. (44) Wang, M.; Ye, C. H.; Zhang, Y.; Hua, G. M.; Wang, H. X.; Kong, M. G.; Zhang, L. D. J. Cryst. Growth 2006, 291, 334−339. (45) Tak, Y.; Yong, K. J. J. Phys. Chem. B 2005, 109, 19263−19269. (46) Sun, Y.; Fuge, G. M.; Fox, N. A.; Riley, D. J.; Ashfold, M. N. R. Adv. Mater. 2005, 17, 2477−2481. (47) Kumar, R. T. R.; McGlynn, E.; McLoughlin, C.; Chakrabarti, S.; Smith, R. C.; Carey, J. D.; Mosnier, J. P.; Henry, M. O. Nanotechnology 2007, 18, 215704. (48) Sim, A. Y. L.; Goh, G. K. L.; Tripathy, S.; Andeen, D.; Lange, F. F. Electrochim. Acta 2007, 52, 2933−2937. (49) Znaidi, L.; Illia, G.; Benyahia, S.; Sanchez, C.; Kanaev, A. V. Thin Solid Films 2003, 428, 257−262.

CONCLUSION ZnO nanowire arrays grown from randomly oriented seed layer have shown that crystallites with c-axis oriented perpendicular to the substrate outgrow those that are not as optimally aligned. As less optimally aligned crystallites are eliminated by the geometrical selection process, a highly oriented nanowire array is realized, composed of the surviving crystallites with proper initial orientation. ZnO nanowire array growth in a batch setup was shown to follow the theory of geometrical selection closely and the extent to which experiments followed the model depended on numerous factors. The factors included how long the nanowires were able to grow, the ratio of crystallite size to the intercrystallite distance, the crystal growth rate in the radial direction, and the degree of randomness in the starting crystallites of the substrate. Poisoning of the ZnO surface was observed when the zinc ion concentration reached a certain level during nanowire formation. This prevented the nanowires from growing any longer, and secondary nucleation, believed to be zinc hydroxide, began to form. The systematic study of ZnO nanowire array growth and comparison to theory help to understand and properly interpret the substrate’s effect on the nanowire array, which ultimately allow better control of creating ZnO structures with specific materials properties. The geometrical selection model can also be applied to other nanowire systems beyond ZnO and such mechanistic understanding will be of benefit for controlled structural fabrication of these nanomaterials.



AUTHOR INFORMATION

Corresponding Author

*Email: [email protected]. Notes

The authors declare no competing financial interest.



ACKNOWLEDGMENTS This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory (LLNL) under Contract DE-AC52-07NA27344. The project was funded by the University of California Laboratory Fees Research Grant and the Laboratory Directed Research and Development Program (09-LW-024) at LLNL. We thank Dr. Christine A. Orme and Ms. Kristen E. Murphy for their helpful discussions.



REFERENCES

(1) Li, W. J.; Shi, E. W.; Zhong, W. Z.; Yin, Z. W. J. Cryst. Growth. 1999, 203, 186−196. (2) Vayssieres, L.; Keis, K.; Hagfeldt, A.; Lindquist, S. E. Chem. Mater. 2001, 13, 4395−4398. (3) Wang, Z. L.; Kong, X. Y.; Zuo, J. M. Phys. Rev. Lett. 2003, 91, 185502. (4) Morin, S. A.; Jin, S. Nano Lett. 2010, 10, 3459−3463. (5) Brenner, S. S.; Sears, G. W. Acta Metall. 1956, 4, 268−270. (6) Fan, D. H.; Zhu, Y. F.; Shen, W. Z.; Lu, J. J. Mater. Res. Bull. 2008, 43, 3433−3440. (7) Wang, Z. L. J. Phys.: Condens. Matter. 2004, 16, R829−R858. (8) Baxter, J. B.; Aydil, E. S. Appl. Phys. Lett. 2005, 86, 053114. (9) Govender, K.; Boyle, D. S.; O’Brien, P.; Binks, D.; West, D.; Coleman, D. Adv. Mater. 2002, 14, 1221−1224. (10) Huang, M. H.; Mao, S.; Feick, H.; Yan, H. Q.; Wu, Y. Y.; Kind, H.; Weber, E.; Russo, R.; Yang, P. D. Science 2001, 292, 1897−1899. (11) Yang, J. L.; An, S. J.; Park, W. I.; Yi, G. C.; Choi, W. Adv. Mater. 2004, 16, 1661−1664. (12) Lee, J.; Yoon, M. J. Phys. Chem. C 2009, 113, 11952−11958. 1370

dx.doi.org/10.1021/cm300679x | Chem. Mater. 2013, 25, 1363−1371

Chemistry of Materials

Article

(50) Yamabi, S.; Imai, H. J. Mater. Chem. 2002, 12, 3773−3778. (51) Baxter, J. B.; Walker, A. M.; van Ommering, K.; Aydil, E. S. Nanotechnology 2006, 17, S304−S312. (52) Tian, Z. R. R.; Voigt, J. A.; Liu, J.; McKenzie, B.; McDermott, M. J.; Rodriguez, M. A.; Konishi, H.; Xu, H. F. Nat. Mater. 2003, 2, 821− 826. (53) Wang, M.; Ye, C.-H.; Zhang, Y.; Wang, H.-X.; Zeng, X.-Y.; Zhang, L.-D. J. Mater. Sci.: Mater. Electron. 2008, 19, 211−216. (54) Laemmlein, G. G. Dokl. Akad. Nauk SSSR 1945, 48, 168−171. (55) Bouderbala, M.; Hamzaoui, S.; Amrani, B.; Reshak, A. H.; Adnane, M.; Sahraoui, T.; Zerdali, M. Phys. B 2008, 403, 3326−3330. (56) Ohyama, M.; Kozuka, H.; Yoko, T. Thin Solid Films 1997, 306, 78−85. (57) Znaidi, L.; Illia, G.; Le Guennic, R.; Sanchez, C.; Kanaev, A. J. Sol−Gel Sci. Technol. 2003, 26, 817−821. (58) Hugotlegoff, A.; Joiret, S.; Saidani, B.; Wiart, R. J. Electroanal. Chem. 1989, 263, 127−135. (59) Yatsimirskii, K. B.; Volkov, S. V.; Evtushenko, N. P. Theor. Exp. Chem. 1972, 8, 418−422. (60) Marchebois, H.; Joiret, S.; Savall, C.; Bernard, J.; Touzain, S. Surf. Coat. Technol. 2002, 157, 151−161. (61) Menon, R. M. R.; Gupta, V.; Tan, H. H.; Sreenivas, K.; Jagadish, C. J. Appl. Phys. 2011, 109, 064905. (62) Richardson, J. J.; Lange, F. F. Cryst. Growth Des. 2009, 9, 2576− 2581.

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