SubjectsSubjects(version: 963)
Course, academic year 2021/2022
  
Estimation of Physico-chemical Properties from Molecular Structures - AP403003
Title: Estimation of Physico-chemical Properties from Molecular Structures
Guaranteed by: Department of Physical Chemistry (403)
Faculty: Faculty of Chemical Engineering
Actual: from 2019
Semester: summer
Points: summer s.:0
E-Credits: summer s.:0
Examination process: summer s.:
Hours per week, examination: summer s.:2/1, other [HT]
Capacity: unlimited / unlimited (unknown)
Min. number of students: unlimited
State of the course: taught
Language: English
Teaching methods: full-time
Teaching methods: full-time
Level:  
Note: course is intended for doctoral students only
can be fulfilled in the future
Guarantor: Fulem Michal prof. Ing. Ph.D.
Růžička Květoslav prof. Ing. CSc.
Interchangeability : P403003
Examination dates   Schedule   
Annotation -
The estimation methods and theoretical predictions of physicochemical properties show a rapid development as documented by a high number of scientific papers published on the subject in recent years. This is due to an enormous increase in the number of newly synthesized chemicals for which the basic physicochemical properties required in a variety of applications and processes are not available. During the course, PhD students will get oriented in a high number of published estimation methods and acquire knowledge on applying various types of predictive models. Emphasis is placed on the use of quantum chemistry and statistical thermodynamics methods in areas where these methodologies provide results with uncertainty comparable to experimental uncertainty, such as the calculation of gas-phase thermochemical properties or modeling of thermodynamic properties of crystals. Furthermore, methods based on a group contribution concept, quantitative structure-property relationship methods and methods used for prediction of physicochemical data for multicomponent complex mixtures are discussed. In the frame of the course, PhD students will elaborate and defend a project on the prediction of physicochemical quantities for selected systems.
Last update: Fulem Michal (21.05.2019)
Aim of the course -

Students will be able to:

PhD students will get an overview about estimation methods and program tools for prediction of physico-chemical properties

PhD students will be able to apply estimation methods and computational chemistry for prediction of physicochemical data for chemical engineering and environmental applications

Last update: Fulem Michal (20.05.2019)
Literature -

R: Baum, E. J. Chemical property estimation: theory and practice, Lewis Publishers: Boca Raton, 1998, 0873719387

A: Kolská, Z.; Zábranský, M.; Randová, A. Group Contribution Methods for Estimation of Selected Physico-Chemical Properties of Organic Compounds, Thermodynamics - Fundamentals and Its Application in Science, Ricardo Morales-Rodriguez (Editor), InTech, Rijeka, 2012, 9789535107798.

A: Poling, B. E.; Prausnitz, J. M.; O'Connell, J. P. Properties of Gases and Liquids, McGraw-Hill: 2001, 0070116822.

A: Mackay, D.; Boethling R.S. Handbook of Property Estimation Methods for Chemicals: Environmental and Health Sciences, Lewis Publishers: Boca Raton, 2000, 1566704561.

A: Irikura, K. K.; Frurip, D. J., Computational thermochemistry: prediction and estimation of molecular thermodynamics, American Chemical Society: Washington, USA, 1998.

A: Selected recent scientific articles.

Last update: Fulem Michal (04.09.2019)
Syllabus -

1. Introduction to estimation methods. Basic types of estimation methods, their importance and development, estimation of uncertainty of predicted values. Demonstration of the procedure for developing a new estimation method. Overview of tools for searching physicochemical data, overview of databases of physico-chemical quantities and software tools for their prediction.

2. Calculation of thermodynamic properties of ideal gas (heat capacity, entropy, Gibbs energy etc.) and formation enthalpy using methods of quantum chemistry and statistical thermodynamics.

2. Modeling of thermodynamic properties of molecular crystals, calculation of cohesive energy, sublimation thermodynamic properties and heat capacities of crystal phase using methods of quantum chemistry and statistical thermodynamics.

3. Group contribution estimation methods: their classification and fields of application. Various molecular representations (SMILES, InChI, etc.).

4. QSPR methods: overview and evaluation of their applicability.

5.-6. Basic molecular and material properties: dipole moment, refractive index, refraction, parachor, gyration radius, melting point, normal boiling point, critical parameters, vapor pressure, heat capacity in liquid phase. Calculation or estimation of these properties and an overview of methods used for their determination. Comparison of selected estimation methods. An overview of databases containing experimental data for these properties.

7. Equations of state, estimation of viral coefficients, density of liquids. Comparison of selected estimation methods. Phase equilibrium modeling using equations of state. An overview of databases containing experimental data for these properties.

8. Transport properties: Newtonian and non-Newtonian fluids, estimation methods for prediction of viscosity and thermal conductivity of gases, liquids and mixtures at different pressures, viscosity of suspensions, estimation of diffusion coefficients, demonstration of experimental determination of these properties, importance of rheology and transport properties for material research and petroleum industry.

9. Phase equilibria in multicomponent systems: estimation methods for activity coefficients in non-electrolyte mixtures. PhD students will learn to apply widely used UNIFAC method.

10. Estimation methods and models for prediction of physicochemical properties of nanomaterials.

11. Project assignment - estimation of physicochemical properties for selected systems and preparation of a report in a form of presentation.

12. Presentation of projects, discussion of results, evaluation.

Last update: Fulem Michal (21.05.2019)
Learning resources -

http://webbook.nist.gov/chemistry/

http://cccbdb.nist.gov/

Last update: Pátková Vlasta (16.11.2018)
Entry requirements -

Physical chemistry (bachelor courses)

Last update: Pátková Vlasta (16.11.2018)
 
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