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powdR: Full Pattern Summation of X-Ray Powder Diffraction Data

Overview

powdR is an implementation of the full pattern summation approach to quantitative mineralogy from X-ray powder diffraction data (Chipera and Bish 2002, 2013; Eberl 2003).

powdR has several advantages over the excel based implementations of full pattern summation such as FULLPAT (Chipera and Bish 2002) and RockJock (Eberl 2003). First, computation is faster and, when quantifying multiple samples, can be used in combination with other packages (e.g foreach and doParallel) for parallel processing. Secondly, powdR can be run via a Shiny web application, which offers a user friendly interface for fast and iterative mineral quantification. Lastly, R represents a powerful tool for data manipulation, allowing users to creatively adapt, pre-treat and visualise their data.

Installation

The stable version of powdR is on CRAN:

install.packages("powdR")

Alternatively, the development version can be downloaded from GitHub

#Install devtools if you don't already have it on your machine
install.packages("devtools")

devtools::install_github('benmbutler/powdR')

Usage

library(powdR)
#> powdR: Full Pattern Summation of X-Ray Powder Diffraction Data

#Load some soils to quantify
data(soils)

#Load a powdRlib reference library of pure patterns
data(minerals)

#Quantify a sample
q <-  fps(lib = minerals,
          smpl = soils$sandstone,
          refs = minerals$phases$phase_id,
          std = "QUA.1")
#> 
#> -Aligning sample to the internal standard
#> -Interpolating library to same 2theta scale as aligned sample
#> -Optimising...
#> -Removing negative coefficients and reoptimising...
#> -Computing phase concentrations
#> -Internal standard concentration unknown. Assuming phases sum to 100 %
#> ***Full pattern summation complete***

#Inspect the phase concentrations (summarised by name)
q$phases_grouped
#>       phase_name phase_percent
#> 1         Illite        1.2599
#> 2     K-feldspar        1.2666
#> 3      Kaolinite        1.3476
#> 4 Organic-Matter       41.2340
#> 5    Plagioclase        1.1540
#> 6         Quartz       53.7379

#Inspect the quantification
plot(q, wavelength = "Cu")

Alternatively, plot(q, wavelength = "Cu", interactive = TRUE) provides an interactive plot for better inspection of the fit. More detailed usage instructions are provided in the package vignette.

The powdR Shiny app

To run powdR via the Shiny app, use run_powdR(). This loads the application in your default web browser. The application has eight tabs:

  1. Reference Library Builder: Allows you to create and export a powdRlib reference library from two .csv files: one for the XRPD measurements, and the other for the ID, name and reference intensity ratio of each pattern.
  2. Reference Library Viewer: Facilitates quick inspection of the phases within a powdRlib reference library.
  3. Reference Library Editor: Allows the user to easily subset a powdRlib reference library .
  4. Full Pattern Summation: A user friendly interface for iterative full pattern summation of single samples.
  5. Automated Full Pattern Summation: A user friendly interface for automated full pattern summation of single samples.
  6. Results viewer: Allows for quick inspection of results derived from full pattern summation.
  7. Results editor: Allows for results from previously saved powdRfps and powdRafps objects to be edited via addition or removal of reference patterns to the fitting process.
  8. Help Provides a series of video tutorials (via YouTube) detailing the use of the powdR Shiny application.

Please note that the powdR Shiny app may not work in the Microsoft Edge internet browser.

References

Chipera, Steve J., and David L. Bish. 2002. “FULLPAT: A full-pattern quantitative analysis program for X-ray powder diffraction using measured and calculated patterns.” Journal of Applied Crystallography 35 (6): 744–49. https://doi.org/10.1107/S0021889802017405.

———. 2013. “Fitting Full X-Ray Diffraction Patterns for Quantitative Analysis: A Method for Readily Quantifying Crystalline and Disordered Phases.” Advances in Materials Physics and Chemistry 03 (01): 47–53. https://doi.org/10.4236/ampc.2013.31A007.

Eberl, D. D. 2003. “User’s guide to ROCKJOCK - A program for determining quantitative mineralogy from powder X-ray diffraction data.” Boulder, CA: USGS.

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Install

install.packages('powdR')

Monthly Downloads

293

Version

1.1.0

License

GPL-2 | file LICENSE

Issues

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Maintainer

Benjamin Butler

Last Published

January 10th, 2020

Functions in powdR (1.1.0)

subset.powdRlib

Subset a powdRlib object
powdR

powdR: Full Pattern Summation of X-Ray Powder Diffraction Data
rockjock

RockJock reference library
rockjock_mixtures

RockJock synthetic mixtures
powdRlib

Create an XRD reference library
run_powdR

Run the powdR shiny app
soils

Example soil XRPD data
plot.powdRfps

Plotting elements of a powdRfps object
plot.powdRlib

Plotting elements of a powdRlib object
afps.powdRlib

Automated full pattern summation
summarise_mineralogy

Summarise the mineralogy from multiple powdRfps and powdRafps outputs
plot.powdRafps

Plotting elements of a powdRafps object
afps

Automated full pattern summation
bkg

Fit a background to XRPD data
fps

Full pattern summation
minerals_xrd

A table of 14 reference patterns and their corresponding two theta scale that can be combined with the minerals_phases table to create a powdRlib object when using the powdRlib constructor function. Use the same layout to create custom reference libraries.
minerals_phases

A table of associated data for the minerals_xrd table, which can be be combined with a xrd data table to create a powdRlib object when using the powdRlib constructor function. Use the same layout to create custom reference libraries.
plot.powdRbkg

Plotting a powdRbkg object
minerals

An example powdRlib reference library
fps.powdRlib

Full pattern summation