OVERVIEW

The course "Simulation methods for materials science" is located in the first year of the specialist degree in materials science, in the second semester, and is particularly suitable for the profile "Materials Scientist: Research Specialist".

The course aims to introduce two simulation methods, the Monte Carlo method and molecular dynamics, profitable for studying the properties of a wide range of materials, from synthetic to biological ones. For both methods, the theoretical physical-statistical bases will be presented first, and then we will move on to a phase of active exercises with direct use of the computer.

AIMS AND CONTENT

LEARNING OUTCOMES

At the end of the course the student will have acquired the basic theoretical knowledge and the ability to apply them necessary for the modeling and simulation of materials and physical phenomena at the nanoscale. In particular, the student will be able to understand, use and adapt codes simulation, based on Monte Carlo methods and molecular dynamics, for the investigation of the structural, thermodynamic and kinetic properties of various synthetic and biological materials, which include polymer systems, metal nanoparticles and lipid membranes.

AIMS AND LEARNING OUTCOMES

At the end of the course, the student will have to know the physical/statistical bases of the computational methods covered in the course (Boltzmann distribution, ergodicity, principles of molecular dynamics in different ensembles).

The student will also be able to apply this knowledge using molecular dynamics and Monte Carlo codes to simulate various types of materials (synthetic and biological).

Both of these objectives fit the "Materials Scientist: Research Specialist" job profile.

TEACHING METHODS

Frontal lessons (for the theoretical introduction of the computational methods covered).

Practical exercises on the computer.

SYLLABUS/CONTENT

The course will be divided into two parts, with the first dedicated to Monte Carlo methods and the second dedicated to molecular dynamics. Both parts will contain a theoretical introduction, necessary for the acquisition of basic physical-statistical knowledge, and a practical section of computer exercises, during which students will apply the acquired knowledge using and, when necessary, modifying different simulation codes.

Part 1: Monte Carlo
- Elements of probability (~ 2 hours).
- Elements of statistical mechanics: the Boltzmann distribution (~ 2 hours).
- Monte Carlo (with importance sampling) and kinetic Monte Carlo (~ 4 hours).
- Computer exercises (~ 8 hours). Possible application examples: magnetization in a two-dimensional ferromagnet, order-disorder transition in a reticular gas, and growth of a crystal in two dimensions.

Part 2: molecular dynamics
- Principles of molecular dynamics (~ 2 hours).
- Molecular dynamics at constant energy (~ 3 hours).
- Molecular dynamics at constant temperature (~ 3 hours).
- Computer exercises (~ 8 hours). Possible examples of application: polymeric systems, metallic nanoparticles (functionalized and not), and lipid membranes.

RECOMMENDED READING/BIBLIOGRAPHY

Understanding Molecular Simulation: From Algorithms to Applications - Daan Frenkel, Berend Smit - ELSEVIER, 2nd Edition

TEACHERS AND EXAM BOARD

Exam Board

DAVIDE BOCHICCHIO (President)

LESSONS

Class schedule

L'orario di tutti gli insegnamenti è consultabile all'indirizzo EasyAcademy.

EXAMS

EXAM DESCRIPTION

Oral exam based on the presentation of a simulation work realized by the student himself.

ASSESSMENT METHODS

The ability to use and adapt the computational methods taught will be evaluated by the presentation of an activity carried out by the student, who will be asked to repeat one of the exercises seen during a class by inserting small changes in the simulated system/material.

After the presentation of the simulation carried out by the student, a question will be asked on the theoretical part to verify its knowledge.