autumn 2019 KJE-3102 Computational Chemistry - 10 ECTS

Application deadline

Applicants from Nordic countries: 1 June for the autumn semester.

Exchange students and Fulbright students: 15 April for the autumn semester.


Type of course

Theoretical course. The course is available as a singular or elective course independent of study program, also to exchange students. The course is offered on condition that a minimum number of students register for the course.

Admission requirements

Formal prerequisites:

  • A bachelor degree in chemistry or equivalent, with a grade C or better in the Norwegian grading system. 
  • Basic physical chemistry (i.e. KJE-1005 or equivalent).
  • Basic knowledge in calculus (i.e. either MAT-0001 or MAT-1001).

 

Recommended prerequisites:

  • Expanded knowledge in physical chemistry (i.e. KJE-2001, or equivalent).
  • Basic knowledge in quantum chemistry (i.e. KJE-3101 or equivalent).
  • Basic knowledge in physics (elementary classical mechanics and electromagnetism).
  • Calculus 2 and elementary linear algebra (i.e. MAT-1002 and MAT-1004 or equivalent). 

Local admission, application code 9371 - singular courses at Master's level.


Course overlap

If you pass the examination in this course, you will get an reduction in credits (as stated below), if you previously have passed the following courses:

KJE-8102 Computational Chemistry 10 stp

Course content

Computers are nowadays ubiquitous in any chemistry lab. Not only in assisting other more traditional instruments but also as tools in their own right: even small workstations have become so powerful that quantistic modeling of molecules, their structure, properties and behavior can be conveniently carried out on a desktop machine. In addition, most Universities and research facilities offer a High Performance Computing platform where more demanding tasks can be performed. Mastering computational chemistry methods must nowadays be regarded as important as modern spectroscopic techniques.

The goal of the present course is to present the methods of quantum chemistry in a hands-on fashion in order to enable students to make use of them in their master studies and subsequently in their professional activity.

 

The course will start by presenting a general overview of molecular modeling (classical and quantistic) and their current use in chemistry. We will briefly touch upon classical modeling and molecular mechanics. We will then introduce wavefunction theory which is at the foundation of Quantum Chemistry. The main wavefunction methods will be presented highlighting their strengths and weaknesses in connection to their practical use. We will also introduce Density Functional Theory (DFT), which is at present the most widely employed method in quantum chemistry. Optimization methods will be discussed in connection both with wavefunction theory and DFT to find the "optimal" wavefunction and also in relation to geometric problems such as finding the structure of a molecule or a transition state of a reaction. The computation of molecular properties which leads e.g. to the modeling and interpretation of spectroscopic data will also be presented. We will also describe how to use computational results in order to obtain thermodynamic quanitites such as the enthalpy of the free energy of a reaction. As most of chemistry happens in condensed phase, we will dedicate the last part of the course to the methods to deal with the effect of the solvent on molecules and the techniques (both implicit and explicit) to include such a solvent effect in the calculations.

 

All lectures will be followed by computational exercises where the students will be able to use their acquired knowledge on illustrative examples.


Recommended prerequisites

KJE-2001 Molecular physical chemistry and foundations of spectroscopy, KJE-3101 Quantum Chemistry

Objectives of the course

The student will have acquired a solid and broad theoretical basis to understand computational chemistry. This means that the student

 

Knowledge

  • can explain the man features of a molecular mechanics force field, its use and its origin
  • knows the main traits of wavefunction methods
  • can describe the methods above in general terms, pointing out their strengths, weaknesses and applicability
  • can quantitatively understand the foundation of Density Functional Theory
  • can describe the features of the main classes of functionals and knows their use
  • knows the main optimization methods and their use in connection to wavefunction/density minimization and geometry optimization (minima and saddle points)

 

Skills

  • can set up and run single point calculations and check the outcome in terms of achieved convergence of the result
  • can identify the molecular orbitals and explain their meaning, in particular for frontier orbitals (HOMO/LUMO)
  • can run multilevel geometry optimizations and analyze the convergence of the result
  • knows how to assign the bands of an IR spectrum based on the result of a QM calculation
  • can evaluate the convergence of a calculation with respect to the basis set employed
  • can make use of response theory to compute static and frequency-dependent polarizabilities
  • can explain the solvent effect on molecular structure and properties
  • can compute overlap integrals between basis functions 
  • can identify and characterize a reaction path from the reactants through the transition state to the products
  • can compute magnetic properties of molecules such as the NMR shielding constants and the magnetizabilities

 

Competence

  • can employ computational methods in her/his scientific work
  • knows how to make use of computational methods to acquire information about a chemical system: structure, spectroscopic and thermodynamic properties, reactivity
  • knows how to identify the best computational strategy in order to investigate the problem at hand
  • can explain the outcome of a computation
  • can evaluate the quality and the reliability of the obtained results
  • can write a report describing the work done and analysis of the results


Language of instruction and examination

The language of instruction is English and all of the syllabus material is in English. The reports must be written in English. 

Teaching methods

Lectures: 30 h, Seminars: 30 h, PC lab exercises

Assessment

Evaluation of reports. Letter grades A-E, F - fail. 

Coursework requirements:

  • Compulsory attendance in 8 computational exercises.  
  • For each exercise the student will have to write a report explaining the theoretical background, the computational strategy adopted and the obtained results. 

 

Candidates that receive the grade F can resubmit an improved version of their reports the following semester.


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  • About the course
  • Campus: Tromsø |
  • ECTS: 10
  • Course code: KJE-3102