Computational Materials Science Kierunek studiów: Biofizyka
Kod programu: W4-S2BFA21.2021

Nazwa modułu: Computational Materials Science
Kod modułu: W4-2BF-MB-21-34
Kod programu: W4-S2BFA21.2021
Semestr: semestr zimowy 2021/2022
Język wykładowy: angielski
Forma zaliczenia: egzamin
Punkty ECTS: 6
Opis:
Intermolecular Forces: Hydrogen bonding, Electrostatic interactions, London forces. Molecular clusters, Supramolecular assemblies. Thermodynamics: Variational formulation. Free energy of a reaction, Equilibrium constants. Statistical Mechanics: Gibbs ensemble, Mechanical system, Generalized coordinates, Lagrangian formalism. Hamiltonian formalism, Hamilton's equation, Phase space. Properties of Hamiltonian systems, Conservation laws, Canonical transformation, Poisson brackets, Liouville's operator, Equation of motion of dynamical variables. Liouville's equation and theorem, Probability density, Microcanonical ensemble, Canonical ensemble. Molecular dynamics: Definition, Foundations of molecular simulations, Limits and approximations. Overview of the basic ingredients (Energy potential, Force fields, Numerical integrators). Energy potential, Force fields, Numerical integrators. Force field terms (bonding, bending, torsion, non-covalent interactions). Molecular Dynamics: Coordinate and Velocity initialization, Integrators. Numerical integrators (velocity Verlet, Leapfrog), Statistical mechanical ensemble, Thermal and pressure coupling. Enhanced Sampling Methods. Simulation of the Kv ion channel. Simulation of a lipid bilayer. Fundamentals of enhanced sampling techniques. Implicit solvent and continuum electrostatic modeling. From collisional theory to stochastic dynamical systems. Stochastic differential equations and Statistical Mechanics. Structural properties: distribution function, radial distribution functions. Monte Carlo methods: Numerical Integration, Importance sampling. Free Energy methods. Free Energy Methods: Thermodynamic Integration, Free energy perturbation, Umbrella Sampling Free Energy Methods: Metadynamics, Jarzinski method, Adiabatic free energy. The course aims to provide an overview of the theories and methodologies currently used in various fields of computational molecular sciences, ranging from biomedical sciences to material sciences. A special focus will be devoted to those models and algorithms related to molecular simulation techniques, including enhanced sampling and free energy methods. Such models will be illustrated along with relevant examples taken from recent literature and concerning different molecular modeling applications.
Wymagania wstępne:
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Literatura podstawowa:
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Efekt modułowy Kody efektów kierunkowych do których odnosi się efekt modułowy [stopień realizacji: skala 1-5]
the student can comprehend molecular modeling techniques currently used in the field of life and material sciences [MB_34_1]
 KBF_W02 [4/5]
The student develops competencies on some of the most common computational methodologies used in molecular sciences [MB_34_2]
 KBF_W03 [4/5] KBF_W08 [4/5]
the student develop computational skills through tutorials and exercises [MB_34_3]
 KBF_K04 [4/5]
Typ Opis Kody efektów modułowych do których odnosi się sposób weryfikacji
egzamin [MB_34_w_1]
Oral Exam. In addition to questions related to the basic knowledge of the course, students will be asked to present a scientific problem of their interest suitable to be treated with molecular modeling methodologies.
 MB_34_1 MB_34_2 MB_34_3
Rodzaj prowadzonych zajęć Praca własna studenta Sposoby weryfikacji
Typ Opis (z uwzględnieniem metod dydaktycznych) Liczba godzin Opis Liczba godzin
wykład [MB_34_fs_1]
detailed discussion by the lecturer of the issues listed in the table "module description" using the table and/or multimedia presentations
 48
supplementary reading, working with the textbook
 102 egzamin [MB_34_w_1]
Załączniki
Opis modułu (PDF)
Informacje o sylabusach mogą ulec zmianie w trakcie trwania studiów.
Sylabusy (USOSweb)
Semestr Moduł Język wykładowy
(brak danych)