Methods of Molecular Simulation
Module CH3334
This module handbook serves to describe contents, learning outcome, methods and examination type as well as linking to current dates for courses and module examination in the respective sections.
Module version of SS 2018
There are historic module descriptions of this module. A module description is valid until replaced by a newer one.
Whether the module’s courses are offered during a specific semester is listed in the section Courses, Learning and Teaching Methods and Literature below.
| available module versions | |||
|---|---|---|---|
| WS 2021/2 | WS 2020/1 | SS 2020 | SS 2018 |
Basic Information
CH3334 is a semester module in English language at Master’s level which is offered in summer semester.
This Module is included in the following catalogues within the study programs in physics.
- Catalogue of non-physics elective courses
| Total workload | Contact hours | Credits (ECTS) |
|---|---|---|
| 150 h | 60 h | 5 CP |
Content, Learning Outcome and Preconditions
Content
1. Local and global geometry optimization
2. Ab initio thermodynamics
3. Molecular dynamics
4. Monte Carlo approaches
5. Free energy simulation methods
6. Long-time scale simulation and kinetic Monte Carlo
2. Ab initio thermodynamics
3. Molecular dynamics
4. Monte Carlo approaches
5. Free energy simulation methods
6. Long-time scale simulation and kinetic Monte Carlo
Learning Outcome
Upon successful completion of the module students are able to list basic techniques and algorithms of molecular simulation and state their qualitative concepts.
They know the use and contribution of these techniques to address chemical problems.
They can classify the applicability and limitations of the different techniques.
They are able to use the acquired methods to perform simple simulations.
They know the use and contribution of these techniques to address chemical problems.
They can classify the applicability and limitations of the different techniques.
They are able to use the acquired methods to perform simple simulations.
Preconditions
The modules Mathematics (CH0105, CH0112), Quantum Mechanics (CH4108), and Molecular Structure and Statistical Mechanics (CH4113) from the TUM Chemistry Bachelor course.
Courses, Learning and Teaching Methods and Literature
Courses and Schedule
| Type | SWS | Title | Lecturer(s) | Dates | Links |
|---|---|---|---|---|---|
| VI | 4 | Methods of Molecular Simulation | Reuter, K. Scheurer, C. |
Tue, 14:00–16:00 Thu, 16:00–18:00 |
eLearning |
Learning and Teaching Methods
The module consists of a lecture course with acompanying exercise classes in small tutor groups. The presence time in lectures and exercises is comparable in order to balance the acquisition of conceptual knowledge with that of practical skills. Lectures introduce the various topical units. The students deepen their understanding during guided self-study time, based on the material provided in the e-learning course. Practical exercises allow students to self-assess their competence level, apply their knowledge to jointly solve representative example problems, and receive immediate feedback from a tutor.
Media
Scripts, e-learning course, exercise portfolio, blackboard, PowerPoint
Literature
1) C.J. Kramers, Essentials of Computational Chemistry
2) F. Jensen, Introduction to Computational Chemistry
3) D. Frenkel and B. Smit, Understanding Molecular Simulation: From Algorithms to Applications
2) F. Jensen, Introduction to Computational Chemistry
3) D. Frenkel and B. Smit, Understanding Molecular Simulation: From Algorithms to Applications
Module Exam
Description of exams and course work
The module examination consists of a single written exam (90 minutes) in which the students have to recall different theoretical approaches and methods and their respective applicability in molecular simulation. They have to solve simple problems by computation without any external aids. The answers to questions for background knowledge can be given partially as free text or in multiple choice form. The free text allows students to express their understanding at their personal competence level in their own words. Through the computational problems students can show that they can formalize and apply this understanding in mathematical language.
Exam Repetition
There is a possibility to take the exam in the following semester.