Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-27T15:07:07.843Z Has data issue: false hasContentIssue false

Mathematical Modeling of XRF Matrix Correction Algorithms With an Electronic Spreadsheet

Published online by Cambridge University Press:  06 March 2019

Anthony J. Klimasara*
Affiliation:
OSRAM SYLVANIA INC. (formerly GTE Electrical Products) technical Assistance Laboratory Danvers, MA 01923
Get access

Abstract

It will be demonstrated that the Lachance-Traill, and Lucas-Tooth and Price matrix correction algorithms can easily be applied to spreadsheet stored XRF data.

The structure of spreadsheet stored data in Quantitative XRF Analysis, the utilization of built-in spreadsheet functions essential for data processing and the utilization of Spreadsheet Graphics for plotting of corrected and uncorrected XRF data will be presented.

Development of modern Electronic Spreadsheets has reached the point where they can readily be used for almost any type of laboratory task, including: Data Plotting, Statistical Data Analysis, Report Writing and Publishing, Slide Presentations, etc. This valuable tool can easily be added to older equipment that usually lacks sophisticated XRF software. It can also become an auxiliary tool to modern XRF spectrometers equipped with advanced XRF software.

The spreadsheet approach gives the analyst freedom of choice to process data according to personal/analytical preferences circumventing the rigidity of software supplied with the equipment. The spreadsheet approach also possesses educational value since it presents the basic ingredients of Matrix Correction in clear and concise table fashion. Addrtionaliy, the spreadsheet program is an excellent tool for demonstrating and evaluating different matrix correction models commonly used in X-ray Spectroscopy.

It will also be shown tliat Spreadsheet Graphics are capable of handling the two-theta scans of XRF or XRD data gathered from older DEC/PDP-11 based Rigaku Equipment. This results in excellent hard copies of the two-theta scans, regardless of the output device.

A mathematical background leading to the spreadsheet approach was partially presented in the paper “A mathematical comparison of the Lachance-Traill Matrix correction procedure with statistical multiple linear regression analysis in XRF applications” (41st Annual Denver X-ray Conference, Colorado Springs, 1992).

Type
Research Article
Copyright
Copyright © International Centre for Diffraction Data 1993

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Lachance, G. R.. “Introduction to Alpha Coefficients,” Corporation Seientifique Claisse, Inc., Sainte-Foy, Quebec (1986).Google Scholar
2. Tertian, R. and Claisse, F.. “Principles of Quantitative X-ray Fluorescence Analysis,” Heyden & Son Ltd., (1982).Google Scholar
3. Klimasara, A. J.. “Automated Quantitative XRF Anaiysis Software in Quality Control Applications,” Vol. 35, Advances in X-ray Analysis, Plenum Publ. Corp., NY (1992).Google Scholar
4. Klimasara, A. J.. “A mathematical comparison of the Lachance-Traill Matrix correction procedure with statistical multiple linear regression analysis in XRF applications,” Vol. 36, Advances in X-ray Analysis, Plenum Publ. Corp., NY (1993).Google Scholar
5. Borland International, Inc., “QuattroPro - Version 4.0 “ software manual, CA (1992).Google Scholar
6. Parks, R. G.. “Quattro Pro for Scientific and Engineering Spreadsheets,” Springer-Verlag, NY (1992).Google Scholar
7. Orvis, W. J..”1-2-3 for Scientists and Engineers,” SYBEX (1987).Google Scholar
8. Mezei, L. M.. “Practical Spreadsheet Statistics and Curve Fitting for Scientists and Engineers,” Prentice Halt, Englcwootl CUfs, NJ (1990).Google Scholar
9. Kral, L. H.. “The Excel Spreadsheet for Engineers and Scientists,” Prentice Hall, Engiewood Clifs, NJ (1992).Google Scholar
10. Chatterjee, S. and Price, B.. “Regression Analysis by Example,” John Wiley & Sons, NY (1977).Google Scholar
11. Daniel, C. and Wood, F. S.. “Fitting Equations to Data” - Computer Analysis of Multifactor Data, John Wiley & Sons, NY (1980).Google Scholar
12. Maindonald, J. H.. “Statistical Computations,” John Wiley & Sons, NY (1984).Google Scholar
13. Jennings, A., “Matrix Computation for Engineers and Scientists,” John Wiley & Sons, NY (1980).Google Scholar