The influence of peak area determination bias in quantitative gamma-ray spectrometry in the presence of true coincidence summing

Blaauw, M.; Gelsema, S.J.

doi:10.1016/s0168-9002(98)01109-7

Cited by 4 publications

(1 citation statement)

References 7 publications

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“…The INAA method is, from first principles, linear in that the induced radioactivity is linear proportional to the amount of element present. This linearity applies also to the measured peak area, and the algorithm that determines the peak area [ 7 , 8 ]. The Laboratory for INAA’s requirement for the linearity therefore is more stringent than for the trueness: the contribution of non-linearity to the bias at any concentration level must be smaller than 0.25%.…”

Section: Quality Assessmentmentioning

confidence: 99%

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

Bode

Blaauw

2011

J Radioanal Nucl Chem

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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.

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Section: Quality Assessmentmentioning

confidence: 99%