The Historical Applications of Kinetic Modeling

The Historical Applications of Kinetic Modeling 1. Predictive vs. Postdictive Models 

Chemical kinetic models play multiple roles. In the 20th century, these models were most often used to assist in the interpretation of experimental data, and for the interpolations used in process optimization and control. Kinetic models also played an essential role in the process of generalizing new chemical knowledge from experimental results. In both of these applications, a large amount of experimental data were measured first and then kinetic models were used to rationalize or interpolate between these experimental data. It would not be too unfair to characterize most of this work as postdictive , i.e. the modelers were 

Of course, chemical kinetic models would be even more useful if they could accurately predict the behavior of reacting systems under conditions significantly different from those that have already been measured. If these extrapolative predictions were accurate enough, chemical kinetic models could become valuable tools in process and product design, and by reducing the need to do so many experiments in order to gain a small amount of information, the models could accelerate the pace of innovation. Reliable predictive kinetic models would be particularly helpful in situations where it is impractical to do the experiments, e.g. in the public policy arena, where a failed experiment could be prohibitively costly, or in situations where the experiment is impossible (e.g. predicting what happens in very slow or very fast processes). 

In recent years, it has become possible to extrapolate accurately using detailed chemical kinetic models to predict quantitatively the behavior of some rather complicated chemical systems. The most famous examples of this success are the detailed atmospheric chemistry models whose predictions underlie the Montreal Protocol on ozone-depleting chemicals. However, these atmospheric chemistry models were developed through a huge international effort over several decades, based heavily on a large number of laboratory experiments. Much more rapid and efficient methods of model development are required for detailed predictive chemical kinetics to become a practical everyday design tool for chemical engineering. 

With this history of difficulties in mind, in the next section we reconsider what are the real goals of chemical kinetic modeling. 

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