NON-L INEAR CURVE F ITT ING US ING MICROSOFT EXCEL SOLVER

evaluated for solving non-linear equations. Test and experimental data sets have been processed, and the results suggest hat solver can be successfully used for modelling data obtained in many analytical situations (e.g. chromatography and FIA peaks, fluorescence decays and ISE response characteristics). The relatively simple user interface, and the fact that Excel is commonly bundled free with new PCs makes it an ideal tool for those wishing to experiment with solving non-linear equations without having to purchase and learn a completely new package. The dynamic display of the iterative search process enables the user to monitor location of the optimum solution by the search algorithm. This, together with the almost universal availability of Excel, makes olver an ideal vehicle for teaching the principles of iterative non-linear curve fitting techniques. In addition, complete control of the modelling process lies with the user, who must present the raw data and enter the equation of the model, in contrast to many commercial packages bundled with instruments which perform these operations with a 'black-box ' approach. Recent rends in data generation, owing in part to the computerization of instrumentation, have led to larger and more complex data sets. Traditional approaches to experimental dat