Course detail
Materials Modelling II
FSI-WMQAcad. year: 2018/2019
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. An important part of the course is to gain practical experience with these approaches through a series of exercises (implementation, solution and analysis of each model problem), and through individual problem assignments.
Language of instruction
Number of ECTS credits
Mode of study
Learning outcomes of the course unit
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Co-requisites
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
Course curriculum
Work placements
Aims
Specification of controlled education, way of implementation and compensation for absences
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Prerequisites and corequisites
Basic literature
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
Classification of course in study plans
Type of course unit
Lecture
Teacher / Lecturer
Syllabus
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.
Computer-assisted exercise
Teacher / Lecturer
Syllabus
2. Monte Carlo studies of the 1D-3D Ising models and calculations of their phase diagrams.
3. Calculation of the density of states of the 2D Ising model using the Wang-Landau method.
4. Implementation of numerical methods for the minimizations of functions of N variables.
5. Construction of an arbitrary Bravais lattice and introduction to visualizations.
6. Ground state of crystalline argon in 2D a 3D using the Lennard-Jones potential.
7. Crystallization of inert gas in the Lennard-Jones potential.
8. Calculation of the energies of point defects and surfaces in an fcc material.
9. Study of twinning in ferroelastic materials.
10. Evolution of microstructure in the phase field crystal model.
11. Obtaining the transition pathway of a model system using the Nudged Elastic Band method.
12. Distribution of stresses and strains in a deformed elastic body using the Finite Element Method.
13. Discussions on the assigned problems.