rigakuXRD

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The goal of the rigakuXRD R package is to import and analyze x-ray diffraction (XRD) and reflectivity (XRR) data from the Rigaku Smartlab x-ray diffractometer; mostly for data sets with low-angle reflectivity data or Bragg-Brentano configuration. X-ray diffraction data contains a spectrum with angles and intensities. This package extracts the spectral data from different types of files and provides tools to visualize and analyze that data.

Installation

You can install the latest version of the rigakuXRD R package from GitHub with:

# install.packages("devtools")
devtools::install_github("thomasgredig/rigakuXRD")

Import XRD Data

The package includes several sample X-ray diffraction (XRD) data files, which can be located using the function xrd_sample_files(). These files are provided i n the .ASC, .RAS, and .RASX formats. XRD data may be imported from these and other supported formats using xrd_import(), which automatically selects the appropriate reader based on the file extension. The following example demonstrates how to load a sample XRD data file:

library(rigakuXRD)
filename = xrd_sample_files('asc')
dXRD = xrd_import(filename, xrd = TRUE)

If xrd is TRUE, then an xrd S3 object is returned, otherwise a data frame with the same data. In the case, of the xrd S3 object, it is more convenient to graph the data quickly on a logarithmic scale:

plot(dXRD)

Alternatively, the data frame can also be graphed using the TwoTheta and I columns.

df = xrd_import(filename)
plot(df$TwoTheta, df$I, log='y')

Peak Finder

The largest peak in a sub data set is found with the xrd_peak_estimate() function. It is not a fit, but an estimate to find the parameters of the largest peak in the data set.

Finding the precise peak position, you need to provide a starting angle (see xrd_peak_estimate()). The xrd_find_peak() function attempts to fit a Gaussian function to the main peak. Here is an example:

# find exact position of the peak
dXRD_40 = xrd_filter(dXRD, 40,50)
plot(dXRD_40)
peakPos = xrd_find_peak(dXRD_40, p$th0)
abline(v=peakPos)

You can search for all the prominent peaks, using the following function, which returns a vector with all the peaks.

xrd.get.AllPeaks(dXRD_60)

Peak Analysis

After finding the peaks, the peak amplitude is compared to the background to check the prominence of the peak, it should rise above 5%:

dXRD_35 = xrd_filter(dXRD, 35,40)
peak_stats = xrd_peak_stats(dXRD_35, peakPos = 38.217)
peak_prom = xrd_peak_prominence(peak_stats)
paste0("Peak prominence: ",signif(peak_prom,3),"%.")

You can also get the thickness or grain size using the Debye-Scherrer analysis. The Debye-Scherrer size may be related to the thickness of the film, given that the film is thin enough.

peak_d = xrd.get.DebyeScherrer(peak_stats)
cat("Debye-Scherrer size from peak:", signif(peak_d/10,4), "nm")

xrd object

The xrd S3 class contains x-ray diffraction spectrum data with a data frame that has the following columns:

• TwoTheta: Bragg angle (two theta)

• I: intensity (counts per seconds)

• I.meas: measured intensity

• loop: separate multiple measurements with a number

You can convert the object to a data frame use as.data.frame() and also print the object. Passing an xrd object to several other functions, makes it easy to analyze the data.

Options

For verbose output, set the verbose option to TRUE.

options(verbose=TRUE)