Impacts on the Ratio of Peak to Total and Peak to Source for Si-PIN Detector Through the Monte Carlo Method in XRF Analysis
This basic study investigates the ratio of peak to total ( ) and peak to source ( ) for Si-PIN detectors in X-ray fluorescence (XRF) analysis, with emphasis on analysis the parameters for and using the Monte Carlo method. Many XRF system models have been simulated using the Monte Carlo Neutron-Particle Transport Code MCNP5. Various parameters are set to calculate the detection efficiency in those models, such as the desired X-ray collection angle, thickness, density, moisture content, X-ray angles, geometric distance, and so on. These parameters can impact and in the exponential form to some extent. This study provides a convenient and reliable method for the passive calibration of XRF measurements. INTRODUCTION The X-ray fluorescence (XRF) analysis technique has been widely applied, such as in the field of biology, petrochemical, materials, food and so on 1-11 . Detection efficiency is obtained through efficiency calibration curves in general cases, which is drawn by standard samples. In practice, this efficiency calibration curves are applied in samples similar to standard samples, or similar ingredients. However, the sample’s ingredients remain uncertain. The composition and material structure in unknown samples is different with standard samples. If the same efficiency calibration curves are used for every unknown sample, large errors would be produced in XRF measurements. In order to improve the accuracy of detection efficiency, Sharshar T. prepared a number of standard samples 12 , which had different compositions and material structures, in order to meet the actual needs of the XRF analysis. Obviously, this approach was a huge workload. This study calculates the detection efficiency for Si-PIN detector using the Monte Carlo method. Many XRF system models have been simulated using the Monte Carlo Neutron-Particle Transport Code MCNP5. Various parameters have been set to calculate the detection efficiency in those models, such as the desired X-ray collection angle, thickness, density, moisture content, incident angles, geometric distance, and so on. This study provides a convenient and reliable method for the passive calibration of XRF measurements. First author, Hefan-LIU, Chengdu Research Academy of Environmental Sciences, 8th, Fanglin Road, Qingyang District, Chengdu, China