The development of intelligent components for the automated analysis of samples by inductively coupled plasma (ICP) Spectrometry is presented. An expert system for diagnosing an ICP atomic emission spectrometry (AES) system using a blank solution was developed as a warning system. This expert system was able to warn the system of major malfunctions and was able to identify most problems. Three pattern recognition techniques were compared in their ability to recognize similar geological samples in small databases. Two of these techniques, k-Nearest Neighbours and Bayesian Classification, worked extremely well with over 96% success. The development of an objective function for multi-element optimizations in ICP-AES is presented. Various aspects of the application of a Simplex optimization were explored for the optimization of the ion optics of an ICP-mass spectrometry (MS) system. An algorithm for the automatic selection of internal standards for analytes in difficult samples in ICP-MS is presented.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.35610 |
| Date | January 1998 |
| Creators | Sartoros, Christine. |
| Contributors | Salin, Eric D. (advisor) |
| Publisher | McGill University |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Format | application/pdf |
| Coverage | Doctor of Philosophy (Department of Chemistry.) |
| Rights | All items in eScholarship@McGill are protected by copyright with all rights reserved unless otherwise indicated. |
| Relation | alephsysno: 001641569, proquestno: NQ44574, Theses scanned by UMI/ProQuest. |
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