PST MBH & CO. KG | TU BERGAKADEMIE FREIBERG

Evaluation of extensive series of diffractograms with the aid of factor analysis

$Possible applications of factor analysis for evaluating extensive series of diffractograms$ All authors

1 Possible applications of factor analysis for evaluating extensive series of diffractograms

All authors

$From diffractograms to score values using the example of hydrating mortar$

2 From diffractograms to score values using the example of hydrating mortar – a series of diffractograms arranged from front to back in chronological order

$From diffractograms to score values using the example of hydrating mortar$

3 From diffractograms to score values using the example of hydrating mortar – absolute intensities over a period of 20 h for 150 diffraction angles in the range around 18 °2θ

$From diffractograms to score values using the example of hydrating mortar$

4 From diffractograms to score values using the example of hydrating mortar – standardized intensities over a period of 20 h for 150 diffraction angles in the range around 18 °2θ

$From diffractograms to score values using the example of hydrating mortar$

5 From diffractograms to score values using the example of hydrating mortar – standardized intensities overlaid by the score values of the two factors

6 Quantitative analysis of mixtures of cement and granulated blastfurnace slag by calibration: comparison of actual (weighed) slag content and analyzed slag content

$Changes in diffractograms during the hydration of a high-performance mortar$

7 Changes in diffractograms during the hydration of a high-performance mortar. The upper diagram shows the first 400 consecutive diffractograms and the lower one shows the last 400 consecutive diffractograms

8 Curves of the cumulative heat flow and the change in length during the hydration of high-performance mortar

$Results of the factor analysis of virtually continuously measured X-ray diffraction data of hydrating high-performance mortar$

9 Results of the factor analysis of virtually continuously measured X-ray diffraction data of hydrating high-performance mortar; representation of the score and loading values of the three factors. The score values are shown in the left-hand section and the loadings in the right-hand section

$Results of the regression analysis of virtually continuously measured X-ray diffraction data of hydrating high-performance mortar$

10 Results of the regression analysis of virtually continuously measured X-ray diffraction data of hydrating high-performance mortar; comparison of the measured and calculated cumulative heat flows

$Results of the regression analysis of virtually continuously measured X-ray diffraction data for a hydrating high-performance mortar$

11 Results of the regression analysis of virtually continuously measured X-ray diffraction data for a hydrating high-performance mortar; comparison of the measured and calculated changes in length

The use of statistical factor analysis for evaluating X-ray diffraction data is illustrated using two examples. These show that it is possible to calibrate complete diffractograms instead of individual peaks for quantitative analysis. Processes that cause systematic changes in the samples can be identified and described with the aid of virtually continuous measurements.

1 Introduction

This article uses two examples to show possible applications of statistical factor analysis for evaluating X-ray diffraction data (Figure 1). X-ray diffraction analysis is a valuable tool in both the production and development of building materials. Modern evalu-ation methods, such as the Rietveld method, permit very precise phase analysis and make it possible to draw conclusions about raw materials and methods of production and processing.

Conventional evaluation methods start from diffractograms that were measured under favourable conditions for which, for example, a narrow...

TEXT Dipl.-Geol. Dr. Torsten Westphal¹, Prof. Dr.-Ing. Thomas A. Bier²
¹PST mbH & Co. KG, Bernburg/Germany, ²TU Bergakademie Freiberg, Freiberg/Germany