Zachodniopomorski Uniwersytet Technologiczny w Szczecinie

Wydział Technologii i Inżynierii Chemicznej - Chemical Engineering (S1)

Sylabus przedmiotu Statistical Thermodynamics:

Informacje podstawowe

Kierunek studiów Chemical Engineering
Forma studiów studia stacjonarne Poziom pierwszego stopnia
Tytuł zawodowy absolwenta inżynier
Obszary studiów charakterystyki PRK, kompetencje inżynierskie PRK
Profil ogólnoakademicki
Moduł —
Przedmiot Statistical Thermodynamics
Specjalność przedmiot wspólny
Jednostka prowadząca Katedra Inżynierii Chemicznej i Procesowej
Nauczyciel odpowiedzialny Anna Story <Anna.Story@zut.edu.pl>
Inni nauczyciele Anna Story <Anna.Story@zut.edu.pl>
ECTS (planowane) 5,0 ECTS (formy) 5,0
Forma zaliczenia zaliczenie Język angielski
Blok obieralny 6 Grupa obieralna 2

Formy dydaktyczne

Forma dydaktycznaKODSemestrGodzinyECTSWagaZaliczenie
wykładyW5 30 2,00,50zaliczenie
laboratoriaL5 45 3,00,50zaliczenie

Wymagania wstępne

KODWymaganie wstępne
W-1Principles of Thermodynamics and Chemical Bonding

Cele przedmiotu

KODCel modułu/przedmiotu
C-1The aim of the course is to provide fundamental knowledge of Statistical Thermodynamics. An important aim of the course is to provide in-depth understanding of the concept of entropy and thus bridge the opposition between a microscopic approach (statistical mechanics) and a macroscopic one (thermodynamics). An important aim of the course is to understand how intermolecular interaction affects the properties of matter. After completing the course, student knows: (1) the principles of statistical mechanics on ensembles of molecules, (2) the association between statistical mechanics and thermodynamics, (3) how intermolecular interaction affects the properties of matter. Student is also able to use statistical mechanical software to calculate the properties of macroscopic systems and proper interpretation of the results.

Treści programowe z podziałem na formy zajęć

KODTreść programowaGodziny
laboratoria
T-L-1During the laboratory course selected open-source software will be used to simulate issues of statistical thermodynamics. Modelling will be carried out on the basis of the Monte Carlo methods, as well as the molecular dynamics method, with using selected open-source software, e.g. GROMACS, CP2K, HOOMD-blue, LAMMPS, MOIL, RedMD45
45
wykłady
T-W-1Introduction to the Statistical Thermodynamics. General remarks2
T-W-2Review of classical Thermodynamics. Energy and the First Law of thermodynamics. Entropy and the Second Law of thermodynamics. Thermodynamic functions and equilibrium conditions. Change of phase and phase equilibrium4
T-W-3Fundamentals assumptions of Statistical Thermodynamics. Phase space. Statistical Mechanics Based on Postulates4
T-W-4Discrete theory of probability4
T-W-5Continuous theory of probability4
T-W-6Entropy and ensembles in statistical mechanics. Classical Ensembles (statistical, microcanonical, canonical and grand canonical). Quantum Ensembles (Quantum Canonical Ensemble, Quantum and Classical Statistics, Simple Quantum Systems)4
T-W-7Introduction to Monte Carlo Method. Using Monte Carlo Simulations to Compute Ensemble Averages4
T-W-8Molecular Simulation. Monte Carlo Simulations. Introduction to Molecular Dynamics. Examples of software used in simulations of Statistical Thermodynamics issues4
30

Obciążenie pracą studenta - formy aktywności

KODForma aktywnościGodziny
laboratoria
A-L-1Participation in classes45
A-L-2Preparation of reports30
A-L-3Literature studies10
A-L-4One-on-One Teaching Consultations5
90
wykłady
A-W-1Lecture participation30
A-W-2Individual literature studies15
A-W-3Repetition of the lecture content to the written test8
A-W-4One-on-On Teaching Consultation8
61

Metody nauczania / narzędzia dydaktyczne

KODMetoda nauczania / narzędzie dydaktyczne
M-1Activating methods – lecture and didactic discussion, multimedia presentation
M-2Practical methods – simulations of thermodynamics problems using molecular dynamics and Monte Carlo methods

Sposoby oceny

KODSposób oceny
S-1Ocena podsumowująca: Written final exam based on the lecture contents
S-2Ocena podsumowująca: Written reports

Zamierzone efekty uczenia się - wiedza

Zamierzone efekty uczenia sięOdniesienie do efektów kształcenia dla kierunku studiówOdniesienie do efektów zdefiniowanych dla obszaru kształceniaOdniesienie do efektów uczenia się prowadzących do uzyskania tytułu zawodowego inżynieraCel przedmiotuTreści programoweMetody nauczaniaSposób oceny
ChEn_1A_C17b_W01
Student possesses a general knowledge about the fundamental principles of statistical mechanics,as well as the association between statistical mechanics and thermodynamics. Student knows how intermolecular interaction affects the properties of matter. Student knows different methods of simulations of issues related to statistical thermodynamics		ChEn_1A_W10, ChEn_1A_W15——C-1T-W-1, T-W-2, T-W-3, T-W-4, T-W-5, T-W-6, T-W-7, T-W-8M-1S-1

Zamierzone efekty uczenia się - umiejętności

Zamierzone efekty uczenia sięOdniesienie do efektów kształcenia dla kierunku studiówOdniesienie do efektów zdefiniowanych dla obszaru kształceniaOdniesienie do efektów uczenia się prowadzących do uzyskania tytułu zawodowego inżynieraCel przedmiotuTreści programoweMetody nauczaniaSposób oceny
ChEn_1A_C17b_U01
Student possesses an ability to use specialized software in a way to simulate different issues related to statistical thermodynamics. Student is able to proper interpretation of the obtained results		ChEn_1A_U07, ChEn_1A_U01, ChEn_1A_U03, ChEn_1A_U05, ChEn_1A_U08, ChEn_1A_U16——C-1T-L-1M-2S-2

Zamierzone efekty uczenia się - inne kompetencje społeczne i personalne

Zamierzone efekty uczenia sięOdniesienie do efektów kształcenia dla kierunku studiówOdniesienie do efektów zdefiniowanych dla obszaru kształceniaOdniesienie do efektów uczenia się prowadzących do uzyskania tytułu zawodowego inżynieraCel przedmiotuTreści programoweMetody nauczaniaSposób oceny
ChEn_1A_C17b_K01
Student understands the importance of statistical thermodynamics in different applications. Student has an ability independently or in group to use specialized software as a modeling tool. Student understands the need to train and improve his/her professional and personal competences.		ChEn_1A_K01, ChEn_1A_K03, ChEn_1A_K04, ChEn_1A_K05——C-1T-L-1, T-W-1, T-W-3, T-W-7, T-W-8M-1, M-2S-1, S-2

Kryterium oceny - wiedza

Efekt uczenia sięOcenaKryterium oceny
ChEn_1A_C17b_W01
Student possesses a general knowledge about the fundamental principles of statistical mechanics,as well as the association between statistical mechanics and thermodynamics. Student knows how intermolecular interaction affects the properties of matter. Student knows different methods of simulations of issues related to statistical thermodynamics		2,0Unacceptable understanding of course material
3,0Serious deficiencies in understanding the core subject material
3,5Some deficiencies in understanding the subject material
4,0Some deficiencies in understanding the core subject material
4,5Some mild deficiencies in Mastery of subject material
5,0Complete Mastery of subject material

Kryterium oceny - umiejętności

Efekt uczenia sięOcenaKryterium oceny
ChEn_1A_C17b_U01
Student possesses an ability to use specialized software in a way to simulate different issues related to statistical thermodynamics. Student is able to proper interpretation of the obtained results		2,0Unacceptable understanding of course material
3,0Serious deficiencies in understanding the core subject material
3,5Some deficiencies in understanding the subject material
4,0Some deficiencies in understanding the core subject material
4,5Some mild deficiencies in Mastery of subject material
5,0Complete Mastery of subject material

Kryterium oceny - inne kompetencje społeczne i personalne

Efekt uczenia sięOcenaKryterium oceny
ChEn_1A_C17b_K01
Student understands the importance of statistical thermodynamics in different applications. Student has an ability independently or in group to use specialized software as a modeling tool. Student understands the need to train and improve his/her professional and personal competences.		2,0Unacceptable understanding of course material
3,0Serious deficiencies in understanding the core subject material
3,5Some deficiencies in understanding the subject material
4,0Some deficiencies in understanding the core subject material
4,5Some mild deficiencies in Mastery of subject material
5,0Complete Mastery of subject material

Literatura podstawowa

  1. Keith Stowe, An Introduction to Thermodynamics and Statistical Mechanics, Cambridge University Press, Cambridge, 2007
  2. Gunnar Jeschke, Advanced Physical Chemistry: Statistical Thermodynamics, Swiss Federal Insitute of Technology Zurich, 2015
  3. Normand M. Laurendeau, Statistical Thermodynamics Fundamentals and Applications, Cambridge University Press, Cambridge, 2005

Literatura dodatkowa

  1. Yung-Kuo Lim, Problems and Solutions on Thermodynamics and Statistical Mechanics, World Scientific Publishing Co. Pte. Ltd., Singapore, 1990

Treści programowe - laboratoria

KODTreść programowaGodziny
T-L-1During the laboratory course selected open-source software will be used to simulate issues of statistical thermodynamics. Modelling will be carried out on the basis of the Monte Carlo methods, as well as the molecular dynamics method, with using selected open-source software, e.g. GROMACS, CP2K, HOOMD-blue, LAMMPS, MOIL, RedMD45
45

Treści programowe - wykłady

KODTreść programowaGodziny
T-W-1Introduction to the Statistical Thermodynamics. General remarks2
T-W-2Review of classical Thermodynamics. Energy and the First Law of thermodynamics. Entropy and the Second Law of thermodynamics. Thermodynamic functions and equilibrium conditions. Change of phase and phase equilibrium4
T-W-3Fundamentals assumptions of Statistical Thermodynamics. Phase space. Statistical Mechanics Based on Postulates4
T-W-4Discrete theory of probability4
T-W-5Continuous theory of probability4
T-W-6Entropy and ensembles in statistical mechanics. Classical Ensembles (statistical, microcanonical, canonical and grand canonical). Quantum Ensembles (Quantum Canonical Ensemble, Quantum and Classical Statistics, Simple Quantum Systems)4
T-W-7Introduction to Monte Carlo Method. Using Monte Carlo Simulations to Compute Ensemble Averages4
T-W-8Molecular Simulation. Monte Carlo Simulations. Introduction to Molecular Dynamics. Examples of software used in simulations of Statistical Thermodynamics issues4
30

Formy aktywności - laboratoria

KODForma aktywnościGodziny
A-L-1Participation in classes45
A-L-2Preparation of reports30
A-L-3Literature studies10
A-L-4One-on-One Teaching Consultations5
90
(*) 1 punkt ECTS, odpowiada około 30 godzinom aktywności studenta

Formy aktywności - wykłady

KODForma aktywnościGodziny
A-W-1Lecture participation30
A-W-2Individual literature studies15
A-W-3Repetition of the lecture content to the written test8
A-W-4One-on-On Teaching Consultation8
61
(*) 1 punkt ECTS, odpowiada około 30 godzinom aktywności studenta
PoleKODZnaczenie kodu
Zamierzone efekty uczenia sięChEn_1A_C17b_W01Student possesses a general knowledge about the fundamental principles of statistical mechanics,as well as the association between statistical mechanics and thermodynamics. Student knows how intermolecular interaction affects the properties of matter. Student knows different methods of simulations of issues related to statistical thermodynamics
Odniesienie do efektów kształcenia dla kierunku studiówChEn_1A_W10Has systematic, theory-based knowledge of the kinetics of physical and chemical transformation processes, thermodynamics and engineering of chemical reactors.
ChEn_1A_W15Knows basic methods, techniques, tools and materials used for solving simple engineering tasks within the scope of chemical engineering and technology.
Cel przedmiotuC-1The aim of the course is to provide fundamental knowledge of Statistical Thermodynamics. An important aim of the course is to provide in-depth understanding of the concept of entropy and thus bridge the opposition between a microscopic approach (statistical mechanics) and a macroscopic one (thermodynamics). An important aim of the course is to understand how intermolecular interaction affects the properties of matter. After completing the course, student knows: (1) the principles of statistical mechanics on ensembles of molecules, (2) the association between statistical mechanics and thermodynamics, (3) how intermolecular interaction affects the properties of matter. Student is also able to use statistical mechanical software to calculate the properties of macroscopic systems and proper interpretation of the results.
Treści programoweT-W-1Introduction to the Statistical Thermodynamics. General remarks
T-W-2Review of classical Thermodynamics. Energy and the First Law of thermodynamics. Entropy and the Second Law of thermodynamics. Thermodynamic functions and equilibrium conditions. Change of phase and phase equilibrium
T-W-3Fundamentals assumptions of Statistical Thermodynamics. Phase space. Statistical Mechanics Based on Postulates
T-W-4Discrete theory of probability
T-W-5Continuous theory of probability
T-W-6Entropy and ensembles in statistical mechanics. Classical Ensembles (statistical, microcanonical, canonical and grand canonical). Quantum Ensembles (Quantum Canonical Ensemble, Quantum and Classical Statistics, Simple Quantum Systems)
T-W-7Introduction to Monte Carlo Method. Using Monte Carlo Simulations to Compute Ensemble Averages
T-W-8Molecular Simulation. Monte Carlo Simulations. Introduction to Molecular Dynamics. Examples of software used in simulations of Statistical Thermodynamics issues
Metody nauczaniaM-1Activating methods – lecture and didactic discussion, multimedia presentation
Sposób ocenyS-1Ocena podsumowująca: Written final exam based on the lecture contents
Kryteria ocenyOcenaKryterium oceny
2,0Unacceptable understanding of course material
3,0Serious deficiencies in understanding the core subject material
3,5Some deficiencies in understanding the subject material
4,0Some deficiencies in understanding the core subject material
4,5Some mild deficiencies in Mastery of subject material
5,0Complete Mastery of subject material
PoleKODZnaczenie kodu
Zamierzone efekty uczenia sięChEn_1A_C17b_U01Student possesses an ability to use specialized software in a way to simulate different issues related to statistical thermodynamics. Student is able to proper interpretation of the obtained results
Odniesienie do efektów kształcenia dla kierunku studiówChEn_1A_U07Is able to use computer programs supporting the accomplishment of basic engineering tasks.
ChEn_1A_U01Is able to obtain information from literature, data bases and other sources related to chemical engineering and technology as well as related areas; is able to integrate the obtained information, interpret it, draw proper conclusions and formulate opinions with their justification.
ChEn_1A_U03Is able to prepare, in English or another foreign language, a well-documented study of problems within the scope of chemical and process engineering; is able to develop documentation concerning the accomplishment of an engineering task.
ChEn_1A_U05Has the ability to learn, e.g. to raise professional competences.
ChEn_1A_U08Is able to plan and conduct process experiments, including measurements and computer simulations, as well as to interpret the obtained results and draw conclusions.
ChEn_1A_U16Is able to assess the usefulness of routine methods and tools used for solving a simple engineering task of practical nature characteristic for chemical engineering and technology as well as select and use a proper performance method and tools.
Cel przedmiotuC-1The aim of the course is to provide fundamental knowledge of Statistical Thermodynamics. An important aim of the course is to provide in-depth understanding of the concept of entropy and thus bridge the opposition between a microscopic approach (statistical mechanics) and a macroscopic one (thermodynamics). An important aim of the course is to understand how intermolecular interaction affects the properties of matter. After completing the course, student knows: (1) the principles of statistical mechanics on ensembles of molecules, (2) the association between statistical mechanics and thermodynamics, (3) how intermolecular interaction affects the properties of matter. Student is also able to use statistical mechanical software to calculate the properties of macroscopic systems and proper interpretation of the results.
Treści programoweT-L-1During the laboratory course selected open-source software will be used to simulate issues of statistical thermodynamics. Modelling will be carried out on the basis of the Monte Carlo methods, as well as the molecular dynamics method, with using selected open-source software, e.g. GROMACS, CP2K, HOOMD-blue, LAMMPS, MOIL, RedMD
Metody nauczaniaM-2Practical methods – simulations of thermodynamics problems using molecular dynamics and Monte Carlo methods
Sposób ocenyS-2Ocena podsumowująca: Written reports
Kryteria ocenyOcenaKryterium oceny
2,0Unacceptable understanding of course material
3,0Serious deficiencies in understanding the core subject material
3,5Some deficiencies in understanding the subject material
4,0Some deficiencies in understanding the core subject material
4,5Some mild deficiencies in Mastery of subject material
5,0Complete Mastery of subject material
PoleKODZnaczenie kodu
Zamierzone efekty uczenia sięChEn_1A_C17b_K01Student understands the importance of statistical thermodynamics in different applications. Student has an ability independently or in group to use specialized software as a modeling tool. Student understands the need to train and improve his/her professional and personal competences.
Odniesienie do efektów kształcenia dla kierunku studiówChEn_1A_K01Understands the need of learning and raising professional and personal competences, motivating other colleagues.
ChEn_1A_K03Is able to cooperate and work in a group. Is able to perform the function of a team leader; is able to estimate the time necessary to accomplish the assigned task.
ChEn_1A_K04Is able to determine the priorities used for performance of the tasks of his/her own or other team members in order to achieve the goal set.
ChEn_1A_K05Is able to manage his/her own professional development, taking decisions and solving problems, including interpersonal ones connected with job performance.
Cel przedmiotuC-1The aim of the course is to provide fundamental knowledge of Statistical Thermodynamics. An important aim of the course is to provide in-depth understanding of the concept of entropy and thus bridge the opposition between a microscopic approach (statistical mechanics) and a macroscopic one (thermodynamics). An important aim of the course is to understand how intermolecular interaction affects the properties of matter. After completing the course, student knows: (1) the principles of statistical mechanics on ensembles of molecules, (2) the association between statistical mechanics and thermodynamics, (3) how intermolecular interaction affects the properties of matter. Student is also able to use statistical mechanical software to calculate the properties of macroscopic systems and proper interpretation of the results.
Treści programoweT-L-1During the laboratory course selected open-source software will be used to simulate issues of statistical thermodynamics. Modelling will be carried out on the basis of the Monte Carlo methods, as well as the molecular dynamics method, with using selected open-source software, e.g. GROMACS, CP2K, HOOMD-blue, LAMMPS, MOIL, RedMD
T-W-1Introduction to the Statistical Thermodynamics. General remarks
T-W-3Fundamentals assumptions of Statistical Thermodynamics. Phase space. Statistical Mechanics Based on Postulates
T-W-7Introduction to Monte Carlo Method. Using Monte Carlo Simulations to Compute Ensemble Averages
T-W-8Molecular Simulation. Monte Carlo Simulations. Introduction to Molecular Dynamics. Examples of software used in simulations of Statistical Thermodynamics issues
Metody nauczaniaM-1Activating methods – lecture and didactic discussion, multimedia presentation
M-2Practical methods – simulations of thermodynamics problems using molecular dynamics and Monte Carlo methods
Sposób ocenyS-1Ocena podsumowująca: Written final exam based on the lecture contents
S-2Ocena podsumowująca: Written reports
Kryteria ocenyOcenaKryterium oceny
2,0Unacceptable understanding of course material
3,0Serious deficiencies in understanding the core subject material
3,5Some deficiencies in understanding the subject material
4,0Some deficiencies in understanding the core subject material
4,5Some mild deficiencies in Mastery of subject material
5,0Complete Mastery of subject material