title: [The Study of Advanced Fundamental Parameter Method in EDXRFA].
abstract: The X-ray Fluorescence Analysis(XRFA) is an important and efficient method on the element anylsis and is used in geology, industry and environment protection. But XRFA has a backdraw that the determination limit and accuracy are effected by the matrix of the sample. Now the fundamental parameter is usually used to calculate the content of elements in XRFA, and it is an efficient method if the matrix and net area of characteristic X-ray peak are obtained. But this is invalide in in-stu XRFA. Also the method of net area and the "black material" of sample are the key point of the fundamental parameter method when the Energy Dispersive X-ray Fluorescence Analysis(EDXRFA) method is used in the low content sample. In this paper a advanced fundamental parameter method is discussed. The advanced fundamental parameter method includes the spectra analysis and the fundamental parameter method, which inserts the overlapping peaks separation method into the iteration process of the fundamental parameter method. The advanced method can resolve the net area and the quantitative analysis. The advanced method is used to analyse the standard sample. Compare to the content obtained from the coefficient method, the precision of Cu, Ni and Zn is better than coeffieciency method. The result shows that the advanced method could improve the precision of the EDXRFA, so the advanced method is better than the coefficient method.
authors.forename: Feng
authors.initials: F
authors.lastname: Cheng
authors.forename: Qing-xian
authors.initials: QX
authors.lastname: Zhang
authors.forename: Liang-quan
authors.initials: LQ
authors.lastname: Ge
authors.forename: Yi
authors.initials: Y
authors.lastname: Gu
authors.forename: Guo-qiang
authors.initials: GQ
authors.lastname: Zeng
authors.forename: Yao-yao
authors.initials: YY
authors.lastname: Luo
authors.forename: Shuang
authors.initials: S
authors.lastname: Chen
authors.forename: Lei
authors.initials: L
authors.lastname: Wang
authors.forename: Jian-kun
authors.initials: JK
authors.lastname: Zhao