Name
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 SN1 and the SN2 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. |
Year | Venue | Keywords |
|---|---|---|
2007 | KSEM | reaction simulation,chemical process,reaction mechanism,essential chemical fact,ontology-based reasoning framework,novel framework,chemical commonsense,sn2 reaction mechanism,chemical theory,chemical intuition,qualitative model,reaction mechanisms simulation,reaction mechanisms,knowledge base,organic chemistry,qualitative reasoning,ontology |
Field | DocType | Volume |
Qualitative process theory,Chemical process,Ontology,Qualitative simulation,Computer science,Intuition,Cognitive tools,Artificial intelligence,Knowledge base,Machine learning,Qualitative reasoning | Conference | 4798.0 |
ISSN | ISBN | Citations |
0302-9743 | 3-540-76718-5 | 0 |
PageRank | References | Authors |
0.34 | 6 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alicia Y. C. Tang | 1 | 10 | 7.13 |
| Sharifuddin Mohd. Zain | 2 | 0 | 0.68 |
| Noorsaadah Abdul Rahman | 3 | 2 | 1.44 |
| Rukaini Abdullah | 4 | 4 | 2.17 |