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Abstract

This work deals with the optimisation of the eluent composition for the separation
of anions using Ion Chromatography, specifically using an Iterative Interpretive
Optimisation Strategy.
Firstly a series of retention models is introduced that are suitable for use in an
Interpretive Optimisation strategy. These models include the Linear Solvent
Strength model (Dominant Equilibrium and Competing Ion Effective Charge
Approaches), Hoover model, Dual Eluent Species model, Kuwamoto model,
Extended Dual Eluent Species model, Multiple Species Eluent/Analyte model and
the newly developed Empirical End Points model. Also included is the
commercially available 3-point model of DryLab. The theory and mathematics
behind these models are also discussed.
These models have been critically compared to determine their suitability for use
in an Iterative Interpretive Optimisation strategy. This comparison is broken into
three parts, non-suppressed ion chromatography, suppressed ion
chromatography, and single eluent species ion chromatography. For single eluent
species ion chromatography the list of models was reduced to the Linear Solvent
Strength model, the Empirical End Points model and the 3-point model of DryLab,
which were found to be the only models suitable for this type of chromatography.
The 3-point model of DryLab was found to be unsuitable for multiple species
eluent ion chromatography.
A number of trends were noted across the comparison, the most significant of
which were that the Empirical End Points and Linear Solvent Strength models
were the only two models that were applicable to the entire data set. The Empirical
End Points model was consistently the best performed model while the Linear
Solvent Strength model was consistently the worst, and the solution requirements
for the Empirical End Points model were found to be the most suitable for an
optimisation process. Thus the Empirical End Points model was chosen as the
retention model for the optimisation process.
Next, a procedure for an Iterative Interpretive Optimisation process was developed
and a computer program written to handle the large number of calculations
required for the process. The computer program was for the Iterative Interpretive Optimisation process of the eluent concentration only. A case study using a
carbonate eluent was conducted to test the program and procedure, resulting in
the separation of 20 anions within 12 minutes.
Finally, the use of an Artificial Neural Network as a retention model was studied.
Artificial Neural Networks were found to require a large amount of training
compared with theoretical retention models, but their high level of accuracy and
low system knowledge requirements make them a prospect worthy of further
evaluation.

Item Type:	Thesis - PhD
Authors/Creators:	Madden, John
Keywords:	Ion exchange chromatography, Interpreters (Computer programs), Anion separation, Mathematical models
Copyright Holders:	The Author
Copyright Information:	Copyright 1998 the Author - The University is continuing to endeavour to trace the copyright owner(s) and in the meantime this item has been reproduced here in good faith. We would be pleased to hear from the copyright owner(s).
Additional Information:	Thesis (Ph.D.)--University of Tasmania, 1999. Includes bibliographical references
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