Data analysis and data treatment

Resources for Data Analysis and Data Treatment

Probe for EPMA Manuals and User Forum:

 

Probelab ReImager:

  • Probelab ReImager: https://reimager.probelab.net/ Reference: Kraft, N., & Von der Handt, A. (2021).
  • Probelab ReImager: An Open-Source Software for Streamlining Image Processing in an Electron Microscopy Laboratory. Microscopy Today, 29(2), 38-41. doi:10.1017/S1551929521000481

 

Recent Review on Electron Probe Microanalysis:

  • Llovet, X., Moy, A., Pinard, P.T. and Fournelle, J.H., 2021. Electron probe microanalysis: A review of recent developments and applications in materials science and engineering. Progress in Materials Science, 116, p.100673.

 

Literature on Uncertainty in EPMA:

  • Marinenko, R.B. and Leigh, S., 2010, Uncertainties in electron probe microanalysis. In IOP Conference Series: Materials Science and Engineering (Vol. 7, No. 1, p. 012017). IOP Publishing.
  • Merlet, C. and Llovet, X., 2012, March. Uncertainty and capability of quantitative EPMA at low voltage–A review. In IOP Conference Series: Materials Science and Engineering (Vol. 32, No. 1, p. 012016). IOP Publishing.
  • Ritchie, N.W. and Newbury, D.E., 2012. Uncertainty estimates for electron probe X-ray microanalysis measurements. Analytical chemistry, 84(22), pp.9956-9962.
  • Ritchie, N.W., 2020. Embracing Uncertainty: Modeling the Standard Uncertainty in Electron Probe Microanalysis—Part I. Microscopy and Microanalysis, 26(3), pp.469-483.
  • Ritchie, N.W., 2021. Embracing Uncertainty: Modeling Uncertainty in EPMA—Part II. Microscopy and Microanalysis, 27(1), pp.74-89. GUM: Guide to the Expression of Uncertainty in Measurement: https://www.bipm.org/en/publications/guides/gum.html

 

EPMA data recalculation spreadsheets:

  • Locock, A.J., 2014. An Excel spreadsheet to classify chemical analyses of amphiboles following the IMA 2012 recommendations. Computers & Geosciences, 62, pp.1-11.
  • Locock, A.J., 2008. An Excel spreadsheet to recast analyses of garnet into end-member components, and a synopsis of the crystal chemistry of natural silicate garnets. Computers & Geosciences, 34(12), pp.1769-1780.

 

Data visualization:

  • Parish, C.M & Edmondson, P. D. (2019): Data visualization heuristics for the physical sciences, Materials & Design, Volume 179, 107868, https://doi.org/10.1016/j.matdes.2019.107868.