Course detail

Materials Modelling

FSI-9MOMAcad. year: 2022/2023

Computational modelling of materials is an indispensable tool to understand the relationship between microstructure and physical properties of materials. Atomic models based on empirical and semiempirical potentials represent essential and frequently used tools for computer simulations of nanostructures such as nanotubes, epitaxial films or graphene, studies of radiation damage and the motion of dislocations under stress. Spin-based models investigated using the Monte Carlo method and continuum mesoscopic models are standard approaches to study the ordering of solid solutions, phase transitions in multiferroics and their changes caused by crystal lattice defects. Macroscopic studies employing the Finite Element Method, which are often enriched by the results of atomistic and mesoscopic studies, represent an essential tool for the prediction of macroscopic behavior of real-world structures. This course provides a broad overview of the basic theoretical methods used in computational modelling of materials from the level of interacting atoms to the continuum macroscopic description, including postprocessing and visualizations of results.

Language of instruction

Czech

Mode of study

Not applicable.

Guarantor

doc. Ing. Roman Gröger, Ph.D. et Ph.D.

Department

Institute of Materials Science and Engineering (ÚMVI)

Learning outcomes of the course unit

Within this course, the students will acquire knowledge of a broad range of computational methods used to study the relationships between microstructure and physical properties of materials. It will provide basic theoretical and practical skills for the studies of nanostructures, interacting many-body systems and for simulations of mesoscopic and macroscopic systems based on their continuum descriptions.

Prerequisites

Knowledge of mathematics at the level of the 2nd year of FME (differentiations of the functions of many variables, basic probability theory, numerical methods), and basic knowledge of programming.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

The objective of the lectures is to introduce fundamental theoretical descriptions of individual methods, their analyses, and in some cases also analytical solutions. The main focus of the exercises is on understanding the implementation of each method and their use to solve model problems and students‘ individual assignments.

Assesment methods and criteria linked to learning outcomes

At the end of the semester, each student will be assigned a problem that will be tightly linked to some of the methods explained in the lectures and more deeply studied in the exercises. The output of each such assignment will be the formulation (or modification of already existing) simulation code, its application to study the given problem and writing a report that summarizes these developments and the principal results. The exam will then consist of an oral defense of this report.

Course curriculum

Not applicable.

Work placements

Not applicable.

Aims

This course will provide a broad overview of the most frequently used methods for computational simulations of materials from the atomic level, via a range of mesoscopic descriptions to the continuum simulations of macroscopic bodies. In the series of exercises, the students will get acquianted with computer implementations of the individual algorithms, which will make it possible to understand the inputs into, methods used and results obtained from standard commercial and open-source packages for computer simulations of materials.

Specification of controlled education, way of implementation and compensation for absences

The attendance at exercises is mandatory and each absence must be propertly justified. The absence will be accepted upon the student submitting a written report from the missed exercise which proves that the student understood the method explained.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

D. Frenkel, B. Smith: Understanding molecular simulation. Academic Press (2002).
J. P. Sethna: Statistical mechanics: Entropy, order parameters, and complexity. Oxford University Press
M. P. Allen, D. J. Tildesley: Computer simulation of liquids. Clarendon Press (1987).

Recommended reading

Not applicable.

Classification of course in study plans

  • Programme D-MAT-K Doctoral 1 year of study, winter semester, recommended course
  • Programme D-MAT-P Doctoral 1 year of study, winter semester, recommended course

Type of course unit

 

Lecture

20 hod., optionally

Teacher / Lecturer

doc. Ing. Roman Gröger, Ph.D. et Ph.D.

Syllabus

The objective of the lectures is to introduce fundamental theoretical descriptions of individual methods, their analyses, and in some cases also analytical solutions.
Topics of the lectures:
1. Modelling of relationships between microstructure and physical properties, history and presence.
2. Equilibrium statistical mechanics, spin models and their mean field solutions.
3. Phase space, phase trajectory, ergodic theorem, entropy.
4. Numerical methods for the minimizations of functions of N variables.
5. Crystallography and symmetry in the real and reciprocal spaces.
6. Molecular statics, atomic-level forces, energies and stresses in many-body systems.
7. Molecular dynamics, stability of numerically integrated equations of motions, thermostats, barostats.
8. More advanced interaction potentials and their physical origins.
9. Mesoscopic phase field models.
10. Phase field crystal model.
11. Methods for finding the minimum energy paths of systems.
12. Finite Element Method, shape functions and elasticity.
13. Modern trends in computational studies of materials.