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Publication# Growth of high-density Ru- and RuO2-composite nanodots on atomic-layer-deposited Al2O3 film

Abstract

Growth of Ru- and RuO2-composite (ROC) nanodots on atomic-layer-deposited Al2O3 film has been studied for the first time using ion-beam sputtering followed by post-deposition annealing (PDA). X-ray photoelectron spectroscopy analyses reveal that RuO2 and Ru co-exist before annealing, and around 10% RuO2 is reduced to metallic Ru after PDA at 900 degrees C for 15 s. Scanning electron microscopy measurements show that well-defined spherical ROC nanodots are not formed till the PDA temperature is raised to 900 degrees C. The mean diameter of the nanodots enlarges with increasing PDA temperature whereas the nanoclot density decreases, which is attributed to coalescence process between adjacent nanodots. It is further illustrated that the resulting nanodot size and density are weakly dependent on the annealing time, but are markedly influenced by the decomposition of RuO2. In this article, the ROC nanodots with a high density of 1.6 x 10(11) cm(-2), a mean diameter of 20 nm with a standard deviation of 3.0 nm have been achieved for the PDA at 900 degrees C for 15 s, which is promising for flash memory application.

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In statistics, the standard deviation is a measure of the amount of variation or dispersion of a set of values. A low standard deviation indicates that the values tend to be close to the mean (also called the expected value) of the set, while a high standard deviation indicates that the values are spread out over a wider range. Standard deviation may be abbreviated SD, and is most commonly represented in mathematical texts and equations by the lower case Greek letter σ (sigma), for the population standard deviation, or the Latin letter s, for the sample standard deviation.

The average absolute deviation (AAD) of a data set is the average of the absolute deviations from a central point. It is a summary statistic of statistical dispersion or variability. In the general form, the central point can be a mean, median, mode, or the result of any other measure of central tendency or any reference value related to the given data set. AAD includes the mean absolute deviation and the median absolute deviation (both abbreviated as MAD). Several measures of statistical dispersion are defined in terms of the absolute deviation.

In statistics, the median absolute deviation (MAD) is a robust measure of the variability of a univariate sample of quantitative data. It can also refer to the population parameter that is estimated by the MAD calculated from a sample. For a univariate data set X1, X2, ..., Xn, the MAD is defined as the median of the absolute deviations from the data's median : that is, starting with the residuals (deviations) from the data's median, the MAD is the median of their absolute values. Consider the data (1, 1, 2, 2, 4, 6, 9).

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