Applications of machine learning in chemistry are many and varied, from prediction of structure-property relationships, to modeling of potential energy surfaces for large scale atomistic simulations. We describe a generalized approach for the application of machine learning to the classification of spectra which can be used as the basis for a wide…

In chemistry, reasoning about the underlying mechanisms of observed phenomena lies at the core of scientific practices. The process of uncovering, analyzing, and interpreting mechanisms for explanations and predictions requires a specific kind of reasoning: mechanistic reasoning. Several frameworks have already been developed that capture the…

Suggests a method for solving verbal problems in chemistry using a linguistic algorithm that is partly adapted from two artificial intelligence languages. Provides examples of problems solved using the mental concepts of translation, rotation, mirror image symmetry, superpositioning, disjoininng, and conjoining. (TW)