| Educational guide Faculty of Chemistry |
english |
| Synthesis, Catalysis and Molecular Design (2013) |
 Subjects |
| COMPUTATIONAL MODELLING IN CATALYSIS AND MATERIALS SCIENCE |
| Contents |
| IDENTIFYING DATA | 2020_21 |
| Subject | COMPUTATIONAL MODELLING IN CATALYSIS AND MATERIALS SCIENCE | Code | 13685211 | |||||
| Study programme |
|
Cycle | 2nd | |||||
| Descriptors | Credits | Type | Year | Period | ||||
| 4.5 | Optional | AN |
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| Competences | Learning aims | Contents |
| Planning | Methodologies | Personalized attention |
| Assessment | Sources of information | Recommendations |
| Topic | Sub-topic |
| 1. Machine Learning in catalysis: Dataset selection. Descriptors.CoMFA (Comparative Field Analysis) method. Linear and non-linear relationships. Case studies. |
|
| 2. Advance methods for exploring potential energy surfaces: Definitions. Minimization methods. Location of transition states. | |
| 3. Simulation techniques. Definitions. Molecular Dynamics (MD). Monte-Carlo method. Ab initio Molecular Dynamics (AIMD) |
|
| 4. Methods using periodicity. Band theory |
|
| 5. Kinetic analysis of the reaction. Microkinetic analysis. |
