IDENTIFYING DATA 2018_19
Subject (*) INTRODUCTION TO COMPUTATIONAL CHEMISTRY Code 20705204
Study programme
Nanoscience, Materials and Processes: Chemical Technology at the Frontier
 Cycle 2nd
Descriptors Credits Type Year Period
6 Optional AN
Language
Anglès
Department Physical and Inorganic Chemistry
Coordinator
BO JANÉ, CARLES
 E-mail antonio.rodriguezf@urv.cat
carles.bo@urv.cat
Lecturers
RODRÍGUEZ FORTEA, ANTONIO
BO JANÉ, CARLES
Web http://moodle.urv.cat/docnet/guia_docent/index.php?centre=13&ensenyament=1368&assignatura=13685101&any_academic=2013_14&idioma_assig=eng
General description and relevant information Computational Chemistry is nowadays a mature area in modern Chemistry that provides information for understanding chemical phenomena at the molecular level, and that has a high predictive power regarding molecular structure, properties and reactivity. This course deals with the description of the theoretical methods that form the basis of Computational Chemistry, and its application to study molecular systems. It will follow a mixed theoretical/practical approach. From basic examples and case studies related to catalysis, students will learn how to use modern software correctly and in a critical manner. The main aim is that students earn knowledge for understanding current scientific literature, and the expertise needed to attack problems in chemical synthesis and catalysis autonomously.

Competences
Type A Code Competences Specific
 A1.1 A1.1. Successfully studying and learning about the chosen research ambit: evaluating the technical and scientific importance, the technological potential and the viability of the nanoscience, design, preparation, properties, processes, developments, techniques and applications of materials.
 A1.3 A1.3 Planning and executing R+D+I projects related to the field of nanoscience, materials and chemical technologies, drawing conclusions and preparing reports.
 A1.4 A1.4. Conceiving, designing, constructing, reformulating and maintaining equipment, applications and efficient designs for experimental and numerical simulation studies in chemical technology.
 A1.6 A1.6. Analyse, identify and evaluate the data obtained from experiments and databases in the field of nanoscience, materials and chemical technology.
 A2.2 A2.2. Critically evaluating the results of research in the field of nanotechnology, materials and products and process design.
Type B Code Competences Transversal
 B4.1 B4.1. Continuously learning.
 B5.3 B5.3. Applying critical, logical and creative thought in a research and innovative context.
Type C Code Competences Nuclear
 C1.1 Have an intermediate mastery of a foreign language, preferably English

Learning outcomes
Type A Code Learning outcomes
 A1.1 A1.1 Are familiar with the theories, models and software specific to computational chemistry.
 A1.3 A1.3 Are capable of using computational chemistry techniques in chemical research.
 A1.4 A1.4 Can critically assess information and incorporate it into their own knowledge.
 A1.6 A1.6 Can interpret the results obtained from the application of computational chemistry software to specific applications.
 A2.2 A2.2 Are open to the new technologies and multidisciplinary work.
A2.2 Can interpret the basic literature and applications in computational chemistry.
Type B Code Learning outcomes
 B4.1 B4.1 Autonomously adopt the appropriate learning strategies in every situation.
B4.1 Set their own learning objectives.
 B5.3 B5.3 Follow a logical method for identifying the causes of a problem.
Type C Code Learning outcomes
 C1.1 Express opinions on abstract or cultural topics in a limited fashion.
Explain and justify briefly their opinions and projects.
Understand instructions about classes or tasks assigned by the teaching staff.
Understand routine information and articles.
Understand the general meaning of texts that have non-routine information in a familiar subject area.
Write letters or take notes about foreseeable, familiar matters.

Contents
Topic Sub-topic
1. Computational software and graphical user interfaces. Visualizers and Builders
2. Classical versus quantum methods Molecular mechanics. Ab initio methods. Semiempirical methods. DFT methods.
3. Molecular structure and energy in gas phase. Potential energy surfaces. Characterization of stationary points.
4. Analysis of the potential energy surface. Vibrational analysis. IR and Raman spectroscopies. Basic thermodynamic functions.
5. Reactivity. Transition state theory. Algorithms and strategies for locating transition states. Selectivity. Enantioselectivity.
6. Calculation of the energy in complex systems. Solvation effects. Large size molecules. Hybrid methods.
7. Classical molecular dynamics. Conformational analysis. Molecular simulations.
8. Advanced spectroscopies and other properties UV, CD, NMR. pK. Redox potentials.
9. Analysis of results (I) Molecular orbital diagrams. Population analysis. Natural orbitals (NBO). Qualitative theories. Woodward-Hoffmann rules. Interaction energy decomposition schemes.
10. Analysis of results (II) Visualization of molecular functions (electronic density, electrostatic potential). Introduction to the theory of atoms in molecules (AIM).

Planning
Methodologies  ::  Tests
  Competences (*) Class hours
 Hours outside the classroom
 (**) Total hours
Introductory activities
1 0 1
Lecture
A1.1
A1.3
A1.4
A1.6
A2.2
B4.1
B5.3
 25 45 70
IT-based practicals in computer rooms
B5.3
 35 0 35
Assignments
A1.3
B4.1
B5.3
C1.1
 1 15 16
Problem solving, exercises
B4.1
B5.3
 1 25 26
Personal attention
2 0 2
 
Short-answer objective tests
A1.1
A1.3
A1.4
A1.6
A2.2
C1.1
 2 0 2
 
(*) On e-learning, hours of virtual attendance of the teacher.
(**) The information in the planning table is for guidance only and does not take into account the heterogeneity of the students.

Methodologies
Methodologies
  Description
Introductory activities Activities designed to make contact with students, collect information from them and introduce the subject.
Lecture Description of the contents of the subject.
IT-based practicals in computer rooms Practical application of the theory of a knowledge area in a particular context. Practical exercises using ICTs.
Assignments Formulation, analysis, resolution and debate of a problem or exercise related to the topic of the subject.
Problem solving, exercises Essays and other work done by the students
Personal attention Time that each teacher has to speak to pupils and resolve their doubts.

Personalized attention
Description
Time that each teacher has to speak to pupils and resolve their doubts before the objective test - Dr. Carles Bo: cbo@iciq.cat - Dr. Antonio Rodríguez-Fortea: antonio.rodriguezf@urv.cat

Assessment
Methodologies Competences Description Weight        
Assignments
A1.3
B4.1
B5.3
C1.1
 No assignments 0
Problem solving, exercises
B4.1
B5.3
 Homework problem solving, individually or in group. 50
Short-answer objective tests
A1.1
A1.3
A1.4
A1.6
A2.2
C1.1
 Test about concepts and knowledge, and practical skills. 50
Others  
 
Other comments and second exam session

Sources of information

Basic

1) Jensen, Frank, Introduction to computational chemistry , 2006, Chichester, England [etc.] : John Wiley & Sons

2) Cramer, Christopher J., Essentials of computational chemistry : theories and models , 2004, West Sussex : John Wiley & Sons
3)Wolfram Koch, Max C. Holthausen, A chemist's guide to density functional theory, 2001, Weinheim : Wiley-VCH
4) Foresman, James B., Exploring chemistry with electronic structure methods, 1996, Pittsburg (PA) : Gaussian, 1996
Complementary

Recommendations
(*)The teaching guide is the document in which the URV publishes the information about all its courses. It is a public document and cannot be modified. Only in exceptional cases can it be revised by the competent agent or duly revised so that it is in line with current legislation.