氚分析的β衰变诱发X射线谱技术研究进展(英文)
Progress on -decay Induced X-ray Spectroscopy for Tritium Analysis
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摘要: 介绍了氚分析的 衰变诱发X射线谱( BIXS) 方法的发展历程和研究现状。叙述了刻度曲线法、解析方法和蒙特卡罗模拟结合Tikhonov 正则法等三种不同解谱技术的BIXS 方法的特点，重点介绍了课题组近年来开展的研究工作和取得的进展，包括蒙特卡罗模拟和Tikhonov 正则法的引入，氚β衰变内韧致辐射、样品表面粗糙度、氚含量以及实验装置几何参数误差对分析结果影响的研究和应用等，同时也提出了BIXS 方法需进一步开展的研究工作。 This paper presents the status and recent progress on -decay induced X-ray spectroscopy (BIXS) for tritium measurements. The development history of BIXS method and its applications on tritium analysis are introduced, and at the same time the characteristics of three kinds of BIXS methods, i:e. calibration curve method, analytical method and Monte Carlo simulations combined with Tikhonov regularization method are also introduced. The recent studies on the BIXS method performed in our group, including the incorporation of Monte Carlo simulation and regularization method, effects of internal bremsstrahlung of tritium -decay, sample surface roughness, tritium content and geometrical parameter’s uncertainty of experimental setup in BIXS method, and the application are mainly presented. Finally, the general comments on the further improvements of the BIXS method are given.Abstract: This paper presents the status and recent progress on -decay induced X-ray spectroscopy (BIXS) for tritium measurements. The development history of BIXS method and its applications on tritium analysis are introduced, and at the same time the characteristics of three kinds of BIXS methods, i:e. calibration curve method, analytical method and Monte Carlo simulations combined with Tikhonov regularization method are also introduced. The recent studies on the BIXS method performed in our group, including the incorporation of Monte Carlo simulation and regularization method, effects of internal bremsstrahlung of tritium -decay, sample surface roughness, tritium content and geometrical parameter’s uncertainty of experimental setup in BIXS method, and the application are mainly presented. Finally, the general comments on the further improvements of the BIXS method are given.
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