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Computer-assisted methods are applied to the development of predictive models for the normal boiling points of diverse sets of pyrans and pyrroles. The models developed employ molecular structure based parameters or descriptors to encode the features of the compounds which determine the boiling point. A set of 20 descriptors is identified that allows for the development of good quality models for the pyrans and for sets of furans, tetrahydrofurans (THFs), and thiophenes, which have been studied previously. A model is presented which yields good predictions for a combined set of pyrans, furans, THFs, and thiophenes. The scope of this work is expanded to include nitrogen-containing heterocycles through the study of a diverse set of pyrroles. As part of this work, a new set of descriptors is developed for the purpose of capturing information concerning the molecular features responsible for intermolecular hydrogen-bonding interactions. Finally, the pyrrole dataset is combined with a large set of furans, THFs, thiophenes, and pyrans for the purpose of producing a more general boiling point prediction equation. The results of these studies are examined to determine their impact on future work.

Many classifications of odors have been proposed, but none of them have yet gained wide acceptance. Odor sensation is usually described by means of odor character descriptors. If these semantic profiles are obtained for a large diversity of compounds, the resulting database can be considered representative of odor perception space. Few of these comprehensive databases are publicly available, being a valuable source of information for fragrance research. Their statistical analysis has revealed that the underlying structure of odor space is high dimensional and not governed by a few primary odors. In a new effort to study the underlying sensory dimensions of the multivariate olfactory perception space, we have applied principal component analysis to a database of 881 perfume materials with semantic profiles comprising 82 odor descriptors. The relationships identified between the descriptors are consistent with those reported in similar studies and have allowed their classification into 17 odor classes.