Abstract
Many chemistry students have difficulty in understanding an organic chemistry subject called reaction mechanisms. Mastering the subject would require the application of chemical intuition and chemical commonsense adequately. This work discusses a novel framework using Qualitative Reasoning (QR) to provide means for learning reaction mechanisms through simulation. The framework consists of a number of functional components. These include substrate recognizer, qualitative model constructor, prediction engine, molecule update routine, explanation generator, and a knowledge base containing essential chemical facts and chemical theories. Chemical processes are represented as qualitative models using Qualitative Process Theory (QPT) ontology. The construction of these models is automated based on a set of QR algorithms. We have tested the framework on the S N 1 and the S N 2 reaction mechanisms. Representative cases of reaction simulation and causal explanation are also included to demonstrate how these models can serve as a cognitive tool fostering the acquisition of conceptual understanding via qualitative simulation.
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Alicia Tang, Y.C., Zain, S.M., Abdul Rahman, N., Abdullah, R. (2007). An Ontology-Based Reasoning Framework for Reaction Mechanisms Simulation. In: Zhang, Z., Siekmann, J. (eds) Knowledge Science, Engineering and Management. KSEM 2007. Lecture Notes in Computer Science(), vol 4798. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76719-0_6
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DOI: https://doi.org/10.1007/978-3-540-76719-0_6
Publisher Name: Springer, Berlin, Heidelberg
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