In an effort to engage students more deeply in their laboratory work and provide them with valuable learning experiences in the applications and limitations of computational chemistry as a research tool, students are instructed to carry out a computational pre-lab exercise. Before carrying out a laboratory experiment that investigates the mechanism for the formation of N-t-butylbenzamide, students construct and obtain heats of formation for reactants, products, postulated reaction intermediates, and one transition state structure for each proposed mechanism. This is designed as a companion to an open-ended laboratory experiment that hones skills learned early in most traditional organic chemistry courses. The incorporation of a preliminary computational exercise enables students to move beyond guessing what the outcome of the reaction will be. It challenges them to test what they believe they "know" about such fundamental concepts as stability of carbocations, or the significance and utility of thermodynamic data relative to kinetic data. On the basis of their computations and their own experimental data, students then verify or dispute their hypothesis, finally arriving at a defensible and logical conclusion about the course of the reaction mechanism. The manner of implementation of the exercise and typical computational data are described.
To introduce computational chemistry into our five-year chemical technology curriculum, an elective course was designed and offered to students who had completed a full year of organic chemistry but who did not have extensive mathematical or physical chemistry background. The course used PC-based software in a classroom setting. It was hands-on and interactive. To give students an appreciation for the wide range of applications computational methods have, current news items on computational topics were included, and a variety of exercises reflecting inorganic, organic, biochemistry, and vibrational spectroscopy were carried out in in-class working sessions and out-of-class assignments. The course culminated with the submission of student portfolios. A set of problems reflecting a range of difficulty was provided. Within guidelines, students selected from the set and carried out the computations required to answer the questions associated with each problem using their analysis of the computed data. This article describes the course goals and format.
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