Blank samples assessed through multivariate control chart as an internal quality control tool of ICP-MS

Gomez, Filipe; Gueifão, Sandra; Cabral, Izunildo; Castanheira, Isabel; Matos, Ana Sofia

http://hdl.handle.net/10400.18/6714

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Abstract(s)

Inductively coupled plasma mass spectrometry (ICP-MS) is one of the most suitable analytical techniques used to quantify inorganic components at trace concentrations. Being considered one of the key activities in a Quality Assurance system, the Internal Quality Control (IQC) reveals is of utmost importance when ICP-MS is used. Involving a continuous and critical assessment of the analytical methods and work routines of an analytical chemistry laboratory, the main propose of IQC is to continuously monitor the developed methodologies, as well as, to assess the reliability of the results. Within the IQC, the blank sample is an excellent tool, allowing to evaluate and monitor the quality of reagents, identify possible contaminations from the analytical processes resulting from the method and analytical processes, as well as to estimate the detection limits and the quantification limits for the trace elements analysed by ICP-MS. This study presents a methodology based on multivariate control (T2) charts for monitoring and assessing the stability of blank samples for Copper, molybdenum and lead. The proposed methodology grounds on the Statistical Process Control, where the T2 chart was designed to detect possible contaminations that may occur during the analytical method. To validate this approach, three univariate control charts, based on the Z scores, were built for each element and compared with the multivariate control chart output. The data analysis was performed using a set of blank samples collected between the years 2016 and 2018. Based on the data analysis results, the T2 chart was built and then validated through the correspondent three univariate Z charts. By comparing this set of charts it is possible to conclude that the T2 chart is in accordance with the results obtained by the three univariate charts. Although the mathematical complexity is high, this T2 chart revealed to be an appropriate IQC tool, when multi-elemental analyses are performed by ICP-MS.