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用于中子活化分析的多用户、多光谱仪系统的性能与稳健性。

Performance and robustness of a multi-user, multi-spectrometer system for INAA.

作者信息

Bode Peter, Blaauw Menno

机构信息

Reactor Institute Delft, Faculty of Applied Sciences, Delft University of Technology, Mekelweg 15, 2629JB Delft, The Netherlands.

出版信息

J Radioanal Nucl Chem. 2012;291(2):299-305. doi: 10.1007/s10967-011-1178-8. Epub 2011 Jun 1.

DOI:10.1007/s10967-011-1178-8
PMID:26224912
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4514465/
Abstract

The laboratory for instrumental neutron activation analysis at the Reactor Institute Delft, Delft University of Technology uses a network of 3 gamma-ray spectrometers with well-type detectors and 2 gamma-ray spectrometers with coaxial detectors, all equipped with modern sample changers, as well as 2 spectrometers with coaxial detectors at the two fast rabbit systems. A wide variety of samples is processed through the system, all at specific optimized (and thus different) analytical protocols, and using different combination of the spectrometer systems. The gamma-ray spectra are analyzed by several qualified operators. The laboratory therefore needs to anticipate on the occurrence of random and systematic inconsistencies in the results (such as bias, non-linearity or wrong assignments due to spectral interferences) resulting from differences in operator performance, selection of analytical protocol and experimental conditions. This has been accomplished by taking advantage of the systematic processing of internal quality control samples such as certified reference materials and blanks in each test run. The data from these internal quality control analyses have been stored in a databank since 1991, and are now used to assess the various method performance indicators as indicators for the method's robustness.

摘要

代尔夫特理工大学反应堆研究所的仪器中子活化分析实验室使用了一个由3台配备井型探测器的伽马射线光谱仪、2台配备同轴探测器的伽马射线光谱仪组成的网络,所有这些仪器都配备了现代样品更换器,此外在两个快速兔系统中还有2台配备同轴探测器的光谱仪。各种各样的样品通过该系统进行处理,所有样品都按照特定的优化(因而不同)分析方案,并使用光谱仪系统的不同组合。伽马射线光谱由几位合格的操作人员进行分析。因此,该实验室需要预测由于操作人员表现、分析方案选择和实验条件的差异而导致的结果中随机和系统不一致情况的出现(例如偏差、非线性或由于光谱干扰导致的错误赋值)。这是通过在每次测试运行中对内部质量控制样品(如标准参考物质和空白样品)进行系统处理来实现的。自1991年以来,这些内部质量控制分析的数据已存储在一个数据库中,现在用于评估各种方法性能指标,作为该方法稳健性的指标。