Fitting procedure, pitfalls

In addition, models for special substances like carboxylic acids, hydrogen fluoride, formaldehyde, electrolytes, and polymers are introduced and the capabilities of high-precision equations of state and various predictive methods are explained. Recommendations for the parameter fitting procedure and numerous hints to avoid pitfalls during process simulation are given. Because of the space limitation in the book we were not able to cover the whole range of thermodynamics, for example, adsorption has been left out completely as it cannot be presented within a short chapter. 

For other cases, such as La3+ where more detail is required about the nature of the species present in solution, titration data can be computer fit to more complicated multi-equilibrium models containing Mx 1 v( OR)v forms whose stoichiometry is suggested by information gained from independent spectroscopic or kinetic techniques. One must be mindful of the pitfalls of simply fitting the potentiometric data to complex multi-component models for which there is no independent evidence for the various species. Without some evidence for the species put into the fit, the procedure simply becomes an uncritical mathematical exercise of adding and removing various real and proposed components until the goodness of fit is satisfactory. 

The fitting of corresponding feed and copolymer compositions to the copolymer equation to obtain reactivity ratio values is not without pitfalls. Many of the available rj and values in the literature are defective because of unsuspected problems which were involved in estimation procedures, use of inappropriate mathematical models to link polymer and feed compositions, and experimental or analytical difficulties. 

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