Date recorded: June 26 2014Quantitative phase analysis using X-ray diffraction (XRD) became a standard tool for process optimization and quality control in industrial environments such as mining, metals production or building material industries.
A common method is the full pattern Rietveld quantification using structural methods to extract/predict information from the full pattern using physical models and fitting techniques. Sometimes this approach is stretched to its limits. That usually happens, when no realistic physical model is available, or when the model is either too complex or doesn’t fit to reality.
In such cases there is one very elegant way out: multivariate statistics and Partial Least-Squares Regression. This technique is rather popular in spectroscopy as well as in a number of science fields like biosciences, proteomics and social sciences.
We will show a number of cases where PLSR can be used in industrial environments to easily and precisely predict properties like crystallinity, process parameters, components and more directly from XRD data.
The webinar targets industrial as well as academic XRD users that are familiar with XRD but want to look “out of the box” towards new methods.