This article presents theoretical principles of predictive modeling and with emphasis on environmental and forensic applications.
Predictive modeling of evaporation processes is important in many areas of science and engineering, and a variety of models have been developed; however, successful application of such models generally requires knowledge of the composition and the relevant properties for each constituent in the sample or an estimation of such properties for the bulk sample, so to address these challenges, the current project developed a kinetic model that uses the gas chromatographic retention index as a surrogate property, thereby obviating the need to know the composition and identity of the chemical constituents in the sample. (Published abstract provided)