IDENTIFYING DATA 2013_14
Subject (*) ADVANCED THERMODYNAMICS AND MOLECULAR SIMULATION Code 20695102
Study programme
Chemical Engineering (2013)
 Cycle 2nd
Descriptors Credits Type Year Period
6 Compulsory First Only annual
Language
Anglès
Department Chemical Engineering
Coordinator
MACKIE ., ALLAN DONALD
 E-mail allan.mackie@urv.cat
yachong.guo@urv.cat
Lecturers
MACKIE ., ALLAN DONALD
GUO ., YACHONG
Web
General description and relevant information This course gives a brief introduction to Statistical Mechanics and an overview of molecular simulation techniques relevant for applications in Chemical Engineering

Competences
Type A Code Competences Specific
 A1 A1.1 Effectively apply knowledge of basic, scientific and technological materials pertaining to engineering.
 A2 A1.2 Design, execute and analyze experiments related to engineering.
 A4 A1.4 Know how to establish and develop mathematical models by using the appropriate software in order to provide the scientific and technological basis for the design of new products, processes, systems and services and for the optimization of existing ones. (G5)
 A10 A3.3 Conceptualize engineering models and apply innovative problems solving methods and appropriate IT applications to the design, simulation, optimization and control of processes and systems (I3).
Type B Code Competences Transversal
 B1.1 B1.1 Communicate and discuss proposals and conclusions in a clear and unambiguous manner in specialized and non-specialized multilingual forums (G9).
Type C Code Competences Nuclear
 C1.1 Have an intermediate mastery of a foreign language, preferably English
 C1.2 Be advanced users of the information and communication technologies

Learning outcomes
Type A Code Learning outcomes
 A1 Coneix les eines per modelar el comportament macroscòpic de sistemes d'interès en Enginyeria Química a partir d'un punt de vista microscòpic
 A2 Comprova a través de la simulació per ordinador els fonaments teòrics explicats a l'aula.
 A4 Domina la dinàmica molecular.
 A10 Domina la simulació pel mètode de Monte Carlo.
Type B Code Learning outcomes
 B1.1 Intervé de forma efectiva i transmet informació rellevant.
Prepara i realitza presentacions estructurades complint amb els requisits exigits.
Planifica la comunicació: genera idees, busca informacions, selecciona i ordena la informació, fa esquemes, determina el tipus de públic i els objectius de la comunicació, ...
Redacta documents amb el format, contingut, estructura, correcció lingüística, registre adequats i il • lustra conceptes utilitzant correctament les convencions: formats, títols, peus, llegendes, ...
Utilitza estratègies per presentar i dur a terme les seves presentacions orals (ajuts audiovisuals, mirada, veu, gest, control de temps, ...).
Utilitza un llenguatge apropiat a la situació.
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 the basic ideas of radio and television programmes.
Understand routine information and articles.
Understand the general meaning of texts that have non-routine information in a familiar subject area.
Take notes during a class.
Write letters or take notes about foreseeable, familiar matters.
 C1.2 Understand basic computer hardware.
Understand the operating system as a hardware manager and the software as a working tool.
Use software for off-line communication: word processors, spreadsheets and digital presentations.
Use software for on-line communication: interactive tools (web, moodle, blogs, etc.), e-mail, forums, chat rooms, video conferences, collaborative work tools, etc.

Contents
Topic Sub-topic
1. Thermodynamic Postulates
2. Classical mechanics and quantum mechanics. Statistical Mechanics
3. The Monte Carlo technique. Importance sampling
Metropolis algorithm
Basic Monte Carlo algorithm
Trial moves
4. Monte Carlo simulation in different ensembles Microcanconical
Isothermal-isobaric
Grand canonical
4. Molecular dynamics Intergration of the equations of motion
Estimation of statistical information

Planning
Methodologies  ::  Tests
  Competences (*) Class hours
 Hours outside the classroom
 (**) Total hours
Introductory activities
1 1 2
Lecture
A1
C1.1
 17 34 51
Problem solving, classroom exercises
A1
B1.1
C1.1
 10 20 30
Practicums/Case studies
A1
A2
A4
A10
B1.1
C1.1
C1.2
 30 30 60
Personal tuition
1 1 2
 
Oral tests
B1.1
C1.1
 1 4 5
 
(*) 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 An overview of the course
Lecture Lectures on the course material based on material from the recommended books
Problem solving, classroom exercises exercises in order to gain a better understanding of the material given in the lectures
Practicums/Case studies molecular simulation case studies to be solved during the laboratory sessions
Personal tuition personal questions and doubts to be resolved on an individual basis

Personalized attention
Description
Individual Tutorials: during office hours

Assessment
Methodologies Competences Description Weight        
Lecture
A1
C1.1
 A written exam of the entire course content 30
Problem solving, classroom exercises
A1
B1.1
C1.1
 Exercises to be handed based on work done both inside and outside of class 20
Practicums/Case studies
A1
A2
A4
A10
B1.1
C1.1
C1.2
 Individual written reports based on simulation exercises carried out in the computer laboratory 30
Oral tests
B1.1
C1.1
 A selected research article where Statistical Thermodyamics is used will be presented in front of the class during a short talk 20
Others  
 
Other comments and second exam session

During any test or exam, mobile telephone, tablets and other electronic devices not explicitly authorised should be turned off and kept out of sight.

Sources of information

Basic D. Frenkel and B. Smit, Understanding Molecular Simulation, Academic Press,
B Widom, Statistical Mechanics: A Concise Introduction for Chemists, Cambridge University Press,

Complementary D. A. McQuarrie, Statistical Thermodynamics, University Science Books,
J-P. Hansen and I.R. McDonald, Theory of Simple Liquids, Academia Press,
D. Chandler, Introduction to Modern Statistical Mechanics, Oxford University Press,
P. Ungerer, B.Tavitian and A. Boutin, Applications of Molecular Simulation in the Oil and Gas Industry. Monte Carlo Methods, Editions Technip,
M. P. Allen and D.J. Tildesley, Computer Simulation of Liquids, Oxford Science Publications,

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.