Computational Chemistry for Organic Chemists
Beräkningskemi för organiska kemister

KAS002F, 7.5 credits

Valid from: Spring 2019
Decided by: Mats Ohlin
Date of establishment: 2018-09-24

General Information

Division: Centre for Analysis and Synthesis (CAS)
Course type: Third-cycle course
Teaching language: English

Aim

The aim of the course is to give deep knowledge in and broad understanding of computational chemistry and principles.

Goals

Knowledge and Understanding

For a passing grade the doctoral student must

• demonstrate understanding of and be able to describe methods available for computational chemistry
• demonstrate understanding of and be able to describe scope and limitations of different methods for computational chemistry

Competences and Skills

For a passing grade the doctoral student must

• be able to describe and discuss orally and in writing computational chemistry methods
• be able to use computational chemistry software
• be able to plan, conduct, and evaluate computational chemistry experiments

Judgement and Approach

For a passing grade the doctoral student must

• be able to value different computational chemistry approaches for addressing a given problem
• be able to judge the validity and quality of output from computational experiments
• be able to analyse his/hers views and arguments for the judgement of a computational chemistry method used and results obtained

Course Contents

The aim of the course is to give practical knowledge about techniques for the calculation and visualization of the structure, conformation, activity and reactivity of small and medium-sized organic molecules, as well as of protein structures and homology models. The course will give an orientation about methods to calculate excited state energy potentials, electronic transitions and transition states. Computational chemistry methods, such as MM, QM, QM-MM, MD, Monte Carlo simulations, and DFT, will be discussed. The course content includes methods for conformational searches and structure-reactivity relationships. The student plans, performs, and evaluates individual computational projects in connection with their research project.

Course Literature

Software and documentation for computational chemistry.

Instruction Details

Types of instruction: Seminars, exercises, project, self-study literature review

Examination Details

Examination formats: Written report, written assignments
Grading scale: Failed, pass
Examiner:

Admission Details

Admission requirements: Admitted as PhD student
Assumed prior knowledge: Basic organic chemistry (KOKA25 or correspodning similar courses) and physical chemistry (KFKA05 och KFKF01 or corresponding similar courses)
Selection criteria: None. All students are accepted.

Further Information

Sufficient demand is five students

Course Occasion Information

Contact and Other Information

Course coordinators: