Abstract
This theoretical study conducted an X-ray fluorescence (XRF) analysis on specimen variation, with emphasis on variations on the thicknesses, density and particle sizes of specimens. The theoretical formula for X-ray fluorescence intensity was derived. These specimen variations were simulated using Monte Carlo Neutron-Particle Transport Code MCNP5. The Cu element X-ray characteristic peak counts were calculated. These variations made a conspicuous impact on the fluorescence intensity X-ray characteristic, in terms of theoretical formulas and calculations. There was a nonlinear relationship between thicknesses and count, except for thin specimens. As the density increased, the count increased in an exponential form for the saturated thick specimens. When the density reached 1 g.cm-3 , the count remained constant. The matrix materials (moisture) could increase the matrix effects. The higher the moisture was, the greater the matrix effect was. Specimen particle size also affects these measurement results. Hence, these specimens must be prepared before measurement. The calculations were consistent with the theoretical formulas.
Highlights
At present, the application of the X-ray fluorescence analysis technique has been widely used, such as in the field of biology, petrochemicals, materials, food and so on [1]-[10]
Depending on the basic radioactive decay law, this study obtains the theoretical formulas for X-ray characteristics fluorescence intensity
The factors of the specimen’s properties were discussed, such as thickness, density, particle size and so on. These factors make a conspicuous impact on X-ray characteristics fluorescence intensity in these theoretical formulas
Summary
The application of the X-ray fluorescence analysis technique has been widely used, such as in the field of biology, petrochemicals, materials, food and so on [1]-[10]. The Monte Carlo Neutron-Particle Transport Code MCNP5, which was produced by Los Alamos National Laboratory, has become one of the important softwares in the field of simulation and analysis in spectroscopy [11] [12] [13] [14] [15]. Different parameters have been set in these models when the physical conditions of the specimen were changed, such as thickness, density, particle size, etc
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
