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Third-Cycle Courses

Faculty of Engineering | Lund University

Details for the Course Syllabus for Course KAS002F valid from Spring 2019

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General
  • English
  • If sufficient demand
Aim
  • The aim of the course is to give deep knowledge in and broad understanding of computational chemistry and principles.
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.
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
Types of Instruction
  • Seminars
  • Exercises
  • Project
  • Self-study literature review
Examination Formats
  • Written report
  • Written assignments
  • Failed, pass
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.
Literature
  • Software and documentation for computational chemistry.
Further Information
  • Sufficient demand is five students
Course code
  • KAS002F
Administrative Information
  •  -09-24
  • Mats Ohlin

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