- Docente: Cristina Puzzarini
- Credits: 6
- SSD: CHIM/02
- Language: Italian
- Teaching Mode: Traditional lectures
- Campus: Bologna
- Corso: Second cycle degree programme (LM) in Chemistry (cod. 8856)
Learning outcomes
- fundaments of statistical thermodynamics and its applications to
classical thermodynamics and spectroscopy
- molecular reaction dynamics and its applications to classical
thermodynamics and spectroscopy
- fundaments of computational chemistry and its applications to
classical thermodynamics and spectroscopy
Course contents
Prerequisites: a good knowledge of fundamental principles of
mathematics, physics, quantum mechanics, thermodynamics, kinetics
and molecular spectroscopy is required.
Program: The main themes treated in this course are statistical
thermodynamics and computational chemistry. The first theme will
allow the student to connect the microscopic worl of quantum
mechanics to the macroscopic world of thermodynamics and kinetics.
The second theme will allow the student to learn how to
quantum-chemically compute the microscopic and macroscopic
properties studied in the first part of the course.
Contents of the theory part.
1) Statistical Themodynamics: fundamentals
- probability and statistics
- statistical ensembles and types of statistics
2) Equilibrium Statistical Themodynamics
- Statistical Themodynamics of ideal gas mixture
- thermodynamic properties
3) Non-Equilibrium Statistical Themodynamics
- chemical reaction kinetics
- chemical reaction dynamics
4) Thermodynamics and Spectroscopy: the computational
approach
- computation: basic concepts
- computation: applications
Contents of the the exercise section.
5) Numerical exercises:
- probability and statistics
- calculation of partition functions (translational, rotational,
vibrational, ...) and of the related properties
- calculation of thermodynamic and kinetic parameters
Contents of the computational lab part.
6) Computational lab practicals:
- quantum-chemical calculation of the spectroscopic properties
required for evaluating the various types of partition
function
- quantum-chemical calculation of thermodynamic properties
Readings/Bibliography
Lecture notes and projected slides play a fundamental role.
These are available on the institutional repositoy for didactic
material (AMS campus).
1) P. Atkins - J. De Paula, Chimica Fisica, Zanichelli (IV edizione italiana)
2) D. A. McQuarrie - J. D. Simon, Chimica Fisica: un approccio molecolare, Zanichelli
3) D. A. McQuarrie, Statistical Mechanics, University Science Books (2000)
4) C. J. Cramer. Essentials of Computational Chemistry. Theories and Models. Wiley - 2nd edition
5) F. Jensen. Introduction to Computational Chemistry. Wiley - 2nd edition
Teaching methods
The course consts of three parts. The first part is a theory part and involves oral lectures supported by video-projection. The second part involves numerical exercises (carried out on the blackboard) aimed at applying the knowledge acquired in the theory part. Finally, the third part involved computational practicals aimed at applying the knowledge acquired in the first part. In detail, four exercitations will be carried out requiring four afternoons.
Assessment methods
Learning assessment is evaluated by means of the final (written) examination and reports on lab laboratory-practical reports (these should be submitted at least 2 days before the written exam). The written exam aims at verifying the student's knowledge and
skills. The duration of this
examination is on average 180 minutes and is organized as
follows:
- Solution of about 15 short numerical exercises (similar to those solved
during the course)
- Answer to about 25 questions (most of them: multiple choice) concerning the theoretical part.
During the written examination the use of the pocket calculator and
text books are allowed (for the numerical exercise solution). The
text book is required in order to consult the fundamental constants
and conversion factors tables.
The final mark is the arithmetic mean of the marks obtained for: (1) numerical exercises, (2) answers to questions and (3) laboratory reports.
Teaching tools
1) Blackboard (lectures and exercises) and video-projector. Lecture
notes
2) computational lab praticals
Office hours
See the website of Cristina Puzzarini