Surface statistical properties of ZnO thin films ...

Scientia Iranica F (2013) 20 (3), 1071–1075

Sharif University of Technology Scientia Iranica Transactions F: Nanotechnology www.sciencedirect.com

Research note

Surface statistical properties of ZnO thin films produced by magnetron sputtering at different rates M. Mirzaee, A. Zendehnam, S. Miri ∗ Thin Film Laboratory, Physics Department, Science Faculty, Arak University, Arak 38156-8-8349, Iran Received 10 August 2012; revised 26 October 2012; accepted 6 December 2012

KEYWORDS ZnO; Si substrate; Deposition rate; Fractal analysis; Morphology.

Abstract Nano layers of zinc, which were deposited by magnetron sputtering on Si (100) substrate, thermal oxidation exposed to the air at 400 °C, were employed to produce ZnO thin films. In order to study the influence of the deposition rate on surface morphology, samples with different deposition rates (1.2–4.5 nm/s) were produced. The surface characteristics of these ZnO thin films are then evaluated against data which result from Atomic Force Microscopy (AFM). The results demonstrate that the film deposited with higher rates has higher surface roughness and grain size. The fractal analysis illustrates that the roughness exponents (α ) for all samples are close. © 2013 Sharif University of Technology. Production and hosting by Elsevier B.V. All rights reserved.

1. Introduction Transparent Conducting Oxides (TCO) have been recently investigated for their interesting optical, mechanical and electrical performance [1,2]. Zinc oxide (ZnO) is an important basic material for the construction of nanoscale structures. ZnO is a II–VI compound semiconductor and an important semiconductor with excellent chemical and thermal stability. At room temperature, ZnO shows a wide band gap (3.37 eV) and large exciton binding energy (60 meV) [3,4]. Zinc oxide can be used in nano-electronic and optoelectronic applications. It is well known that the surface roughness of ZnO thin films is an important feature in many applications, such as gas and biological sensors, solar cells, piezoelectricity and etc [5–8]. The surface, which is the first interface of the material, has an important role to play in the interaction between the material and the environment [9]. Surface roughness has an enormous influence on many important physical phenomena, such as mechanical contact, sealing, adhesion, wave scattering and friction [10]. Most surfaces in nature are rough, and this fact is a motivation that can be studied as a random process. In fact, a surface

∗

Corresponding author. E-mail address: [email protected] (S. Miri). Peer review under responsibility of Sharif University of Technology.

for a special application requires specified statistical properties. ZnO thin films have been prepared by many techniques, such as Pulsed Laser Deposition (PLD), electron beam evaporation, magnetron sputtering, Chemical Vapor Deposition (CVD), molecular beam epitaxy (MBE) and the sol–gel method [11–14]. The roughness of the interfaces can directly control many physical and chemical properties of the films. In the present work, zinc oxide thin films have been produced by thermal oxidation of sputtered zinc films on a Si (100) substrate with 100 nm thickness. We employ Atomic Force Microscopy (AFM) to investigate surface characterizations. Surface roughness, roughness exponents, and correlation length have been measured. In previous work we investigated the photoluminescence spectra of these samples [15]. 2. Experimental details DC magnetron sputtering was employed to deposit thin layers of Zn on Si (100) substrate. A Si (100), n type wafer was cut to the required dimensions (1 cm × 1 cm) with 1 mm thickness and then used as substrate for deposition of Zn thin films. Before being used, all Si substrates were ultrasonically cleaned by heated acetone and then by ethanol for 2 min. A vacuum system (Hind High Vacuum, H.H.V, 12′′ MSPT) with 10−6 mbar base pressure was employed, and a circular flat disc (3 mm thickness, and 125 mm diameter) of pure zinc (99.9%, MERCK) was fabricated and used as the sputtering target. Substrate temperature was fixed (300 K) and measured using an exact digital thermocouple. A conventional oven in open air with average humidity

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M. Mirzaee et al. / Scientia Iranica, Transactions F: Nanotechnology 20 (2013) 1071–1075

of 60% (INDOSAW MODEL SK 012) was used for thermal oxidation of Zn films, and sample oxidation took place at a temperature of 400 ° C. In this work, five samples with different deposition rates were produced. To change the deposition rate of zinc (1.2–4.5 nm/s), the discharge current was altered from 400 to 1200 mA, and zinc thin films with 100 nm thickness were produced. AFM images were employed using a force constant mode and digitized into 256 × 256 pixels. A commercial standard pyramidal Si3N4 tip was used. All AFM images were acquired in ambient air. For a better comparison of the effects of different interfaces, we kept all other experimental parameters unchanged. These samples were produced under similar conditions (Ar pressure (5 × 10−2 m bar), substrate temperature (300 K), oxidation temperature (400 ° C), and heating period (15 min) and substrate to target distance (12 cm)). To investigate the surface morphology of these ZnO thin films, atomic force microscopy (AFM) (Park Scientific Instrument Auto Probe model CP) was employed using a force constant mode. In this paper, we investigate the deposition process as a stochastic process. Scanning electron microscopy (SEM) of the samples was also carried out (HITACHI MODEL S-4160). To analyze the AFM images, the topographic image data were converted into ASCII data. AFM images of samples indicated changes in the surface behavior of the films. This deposition technique presents interesting advantages, such as high deposition rates, low substrate temperatures, good adhesion of thin films to Si substrate, and finally, films with good packing density. 3. Statistical analysis A random rough surface can be described mathematically as h(i, j), where h(i, j) is the height of the surface with respect to the reference level at point r (i, j), where r (i, j) is the position on the surface. We assume that the distance between two adjacent discrete positions is d, and the number of surface points is N. The average surface height is the arithmetic average of surface heights. Analytically, it can be expressed, for a digitized surface, as: N 1 

⟨h⟩N =

N2

h(i, j).

(1)

i,j=1

Root Mean Square (RMS) roughness is one of the most important parameters for characterizing a rough surface. Analytically, it can be estimated as:

⟨w⟩N =

1 N



N 

.

(2)

i,j=1

The height–height correlation function can be expressed as [16]: H (md) =

N N −m   (h(i + m, j) − h(i, j))2

1

N (N − m) j=1 i=1

m = 0, 1, 2, . . . .

(3)

For self-affine surfaces, the dynamic scaling hypothesis suggests that the height–height correlation function H (l) has the scaling form of: H (l) =



(ρ l)2α 2w 2

forl ≪ l0 forl ≫ l0

Samples

Electrical power (W) Current (mA)

E1 E2 E3 E4 E5

184 288 408 530 672

400 600 800 1000 1200

Deposition rat (nm/s) 1.2 1.95 2.75 3.75 4.5

where ρ = w 1/α /l0 is the local slope, and α is the roughness exponent that describes how locally ‘‘wiggly’’ the sample surface is, or to what degree the surface is randomly fluctuated in a short range, and l0 is the lateral correlation length, which is defined as the largest distance at which the height is still correlated. The roughness exponent, α , is directly related to the fractal dimension, Df , of the random surface by Df = E + 1 −α , with 0 < α < 1, where E + 1 is the dimension of the embedded space (E = 1 for a profile; E = 2 for a plan). A larger value of α corresponds to a locally smooth surface structures while α smaller than 1 corresponds to a more locally jagged morphology [17]. The height distribution function provides a complete specification of the random variable, h(l), at position l. Although different rough surfaces may have different height distributions, the most generally used height distribution is the Gaussian height distribution. The statistical analysis of AFM data was done using the height distribution histograms. Height asymmetry is described by statistical parameters, such as surface skewness and kurtosis. Unlike RMS roughness, skewness is dimensionless. Skewness is a measure of the symmetry of a distribution about a mean surface level. Kurtosis is also a dimensionless quantity. It is a measure of the sharpness of the height distribution function. These two parameters represent the shape of the surface height distribution and can be estimated as [16]: Rsk =

Rku =

N 

1

(h(i, j) − ⟨h⟩N )3 ,

3 N i ,j = 1

N ⟨w⟩ 1

N 

(h(i, j) − ⟨h⟩N )4 .

N ⟨w⟩4N i,j=1

(5)

(6)

For comparison of these parameters for all samples, we used the central limit theorem. This theorem gives the mean of a sufficiently large number of independent random variables, each with finite mean and variance, which will approximately have a normal distribution [18]. 4. Results and discussions

1/2 (h(i, j) − ⟨h(i, j)⟩)2

Table 1: Produced samples with different deposition rates.

(4)

In order to study the effects of zinc deposition rates on the surface morphology of ZnO nano layers, five samples with the following conditions (which are presented in Table 1) were prepared. Figure 1 shows two and three dimensional AFM images of E1 , E3 and E5 samples. According to AFM images, using low deposition rates will lead to a reduction in the vertical (roughness) and lateral (correlation length) grain size. The AFM images indicate that, by altering the sputtering rate, the grain size and surface roughness change. Therefore, it seems that by choosing a suitable deposition rate, the grain size and roughness may be controlled. The SEM images of the samples are given in Figure 2, which show the uniformity of the surface and grains that are obtained on the produced samples. Given the statistical parameters introduced in the previous section, it is possible to obtain some quantitative information


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Figure 1: Two and three dimensional AFM surface images of ZnO thin films deposited by rate of 1.2, 2.75, 4.5 nm/s.

Figure 2: SEM images of ZnO thin films deposited at different rates 1.2, 2.75, 4.5 nm/s.

about the effect of deposition rates on the surface topography of ZnO thin films. For obtaining the mean height, RMS roughness, and height–height correlation function of samples, Eqs. (1)–(3) are used, respectively. The height–height correlation function, H (l), is calculated along the x direction. The measurement results in Figure 3 show the AFM images of ZnO thin films in x and y directions. As we see, the forms of the grain in x and y directions are uniform and similar, so that there is no difference between Figure 3(a) and (b) in the direction, and we can choose one direction. Figure 3 shows the height–height correlation function as a function of position, lx , for sample E1 . The slope of each curve at small scale yields the roughness exponent, (2α), of the corresponding surface. The correlation length achieved by the height–height correlation function is represented in Figure 3. The saturation limit in this curve is the correlation length, which is the lateral size of the grains. For deposition rate 1.2 nm/s, the RMS roughness and correlation length are very low (7 nm, 115 nm, respectively). When the sputtering rate is increased to 4.5 nm/s, the value of RMS roughness and the correlation length rises to 42 nm and 196 nm, respectively. Two-dimensional images of specimens obtained using the software, Suffer, show an increase in particle size with increasing deposition rate (Figure 1(b)). The increase of surface roughness and correlation length with increasing deposition rate may be due to the increasing

Figure 3: Log–log plot of the height–height correlation function versus lx for sample deposited with rate of 1.2 nm/s.

energy of condensing particles and particle number plucked from the target during the sputtering process. As seen in Table 2, the mean height, RMS roughness and correlation length of samples are increased at higher rates. The one-dimensional cross-section scans of surface profiles for E1 , E3 , and E5 are also plotted in Figure 4. As can be seen, two typical morphological features are recognized readily by a visual inspection of

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Table 2: Statistical parameters for all samples. Samples

⟨w⟩N (nm)

E1 E2 E3 E4 E5

7±1 9±1 23 ± 1 42 ± 1 42 ± 1

⟨h⟩N (nm) 25 ± 1 39 ± 1 91 ± 1 134 ± 1 136 ± 1

l0 (nm)

Df

115 ± 15 137 ± 15 176 ± 15 215 ± 15 196 ± 15

2.20 ± 0.1 2.13 ± 0.1 2.09 ± 0.1 2.18 ± 0.1 2.17 ± 0.1

Figure 5: Height–height correlation functions H (l) versus position (a) lx and (b) ly for samples deposited by rates of 1.2, 1.95, 2.75, 3.75, 4.5 nm/s.

Figure 4: One-dimensional AFM surface profile along the r direction scans of ZnO thin films deposited at different rates 1.2, 2.75, 4.5 nm/s.

Figures 1 and 4. The granules of various scales exist in all surfaces and are distributed evenly in some ranges. Indeed, the active surface has different meanings, according to its application to different kinds of devices [17]. Figure 5 shows the height–height correlation function for all samples. The roughness exponents for all samples are close, which comes

from the slopes of the log–log plots at the small l region. When the sputtering rate is very high (samples E4 and E5 ), the high energy and momentum of particles can cause an adverse change in surface morphology, although the slope of the diagram is the same as the previous model, and the overlapping effect does not change the correlation length. This can be due to surface diffusion at high sputtering rate (For more details refer to Table 2). This suggests that the dynamics of roughness formation may be quite similar for ZnO thin films during the production process. The height asymmetry is described by the surface statistical parameters, such as skewness and kurtosis. These parameters are calculated by Eqs. (5) and (6), respectively. Figure 6 indicates the height distribution histograms for samples acquired from AFM analysis, which is normalized using the central limit theorem. Table 3 shows the values of these parameters for the produced samples. Film surfaces with positive skewness (larger than 0.2) and high kurtosis (larger than 3.0) values are favourable for tribological applications (e.g. low friction bearings) [19]. ZnO thin films are potential materials suitable for tribological applications. Samples which are deposited with rates of 1.2 and 1.95 nm/s seem appropriate in these terrains. For many device fabrications, such as gas and light sensors, an increase in the active surface is required. The active surface is proportional to roughness parameters, such as standard deviation (which indicates vertical grain size), roughness exponent and correlation length (which indicates lateral grain size). So, the deposition rate is an important parameter for controlling surface activity.


Figure 6: Height distribution histograms from AFM analysis for samples deposited by rates of 1.2, 1.95, 2.75, 3.75, 4.5 nm/s. Table 3: Values of the skewness and kurtosis. Samples E1 E2 E3 E4 E5

Rsk 0.58 0.26 0.16 0.11 0.15

Rku 3.23 3.87 3.12 3.27 3.1

5. Conclusions The ZnO nano films were prepared on Si substrates with different Zn deposition rates by DC magnetron sputtering. AFM analysis has been carried out to characterize the thin films morphologies. Surface morphologies associated with different deposition rates have been investigated, and the results provided evidence that the deposition rates greatly affect the final surface morphology of ZnO thin films. AFM images (Figure 1) illustrate that using different deposition rates will lead to changes in vertical (roughness) and lateral (correlation length) grain size. The increase of the deposition rate from 1.2 to 4.5 nm/s leads to larger vertical and lateral grain sizes. The fractal dimensions were estimated by applying the height–height correlation function method. The fractal dimension, Df , corresponds to changes in the surface morphology that occur due to altering the deposition rate. In this study, it was shown that both interface width and lateral correlation length, l0 , are strongly affected by variations in deposition rate. Similar values of roughness exponents for all samples suggest that the dynamics of roughness formation may be quite similar. Acknowledgments The authors greatly appreciate the financial assistance rendered by Arak University and the Iran Nano-Technology Initiative.

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Mehdi Mirzaee received his B.S. and M.S. degrees in Atomic Physics, and Solid State Physics, from Iran University of Science and Technology, in 1997 and 1999, respectively, and his Ph.D. degree in Theoretical Physics; Quantum Information, from Tabriz University, Iran, in 2004. He is currently Assistant Professor of Physics in Arak University, Iran. He is the author or co-author of 8 peer-refereed articles, and his research interests include: quantum information and computing, biophysics, interaction between atom and field, quantum tomography, and quantum optics.

Akbar Zendehnam received his B.S. degree in Physics, in 1982, and M.S. and Ph.D. degrees in Atomic Physics and Spectroscopy, in 1984 and 1986, respectively, from North London University. Since 1986, he has been Associate Professor of Physics at Arak University, Iran. He is author and co-author of 38 published papers, and his research interests include: optical and Spectral properties of thin films.

References [1] Kammler, D.R., Mason, T.O. and Poeppelmeier, K.R. ‘‘Bulk phase relations, conductivity, and transparency in novel bixbyite transparent conducting oxide solution in the cadmium-indium-tin oxide system’’, J. Am. Ceram. Soc., 84, pp. 1004–1009 (2001).

Sadegh Miri received his B.S. degree in Solid State Physics, in 2008, from Iran University of Science and Technology, and his M.S. degree in Atomic Physics, in 2011, from Arak University, Iran. His research interests include: surface morphology of rough surfaces.