
Course unit
COMPUTATIONAL METHODS IN MATERIAL SCIENCE
SCP7081717, A.A. 2019/20
Information concerning the students who enrolled in A.Y. 2019/20
ECTS: details
Type 
ScientificDisciplinary Sector 
Credits allocated 
Educational activities in elective or integrative disciplines 
FIS/03 
Material Physics 
6.0 
Course unit organization
Period 
Second semester 
Year 
1st Year 
Teaching method 
frontal 
Type of hours 
Credits 
Teaching hours 
Hours of Individual study 
Shifts 
Lecture 
6.0 
48 
102.0 
No turn 
Examination board
Examination board not defined
Prerequisites:

Elementary notions of quantum physics and solid state physics.
Fundamentals of thermodynamics: principles, thermodynamic potentials.
No prior knowledge of computer programming is required. 
Target skills and knowledge:

The aim of this course is to provide the student with a basic understanding of the computational methods used in materials sciences, their capabilities and limitations. This should enable the student:
 to understand how computational methods can be used to rationalize and predict the behavior of materials and the relationship between macroscopic properties and microscopic structure of matter;
 to recognize the numerical techniques suitable for different time and spatial scales;
 to be aware of the underlying assumptions and approximations of different computational techniques.
It is expected that after completion of this course a student will be able to critically evaluate capability and limitations of computational methods in material science and to evaluate the quality of molecular simulation studies reported in the literature.
Furthermore, he/she will reach a deeper understanding of the microscopic origin of physical behavior of matter. Finally he/she will acquire a basic knowledge of common sotware packages. 
Examination methods:

Oral examination in which the students will discuss written reports, on the results of three numerical simulations (Monte Carlo, Molecular Dynamics and DFT calculations). 
Assessment criteria:

Understanding of the basic concepts of methods for the numerical simulation of properties of condensed matter. Capability to analyze and present the results of computer simulations. 
Course unit contents:

Basic concepts of thermodynamics and classical statistical mechanics.
Classical Molecular Dynamics simulations; numerical integration of Newton equations.
Monte Carlo method; Metropolis algorithm.
Simulations in various statistical ensembles.
Common features of simulations methods: initial and boundary conditions; calculation of interparticle interactions.
Calculation of thermodynamic and transport properties.
Intermolecular interactions: forcefields; atomistic and coarse grained models.
Variational methods for the solution of the Schrodinger equation.
Hartree and HartreeFock theory.
Elements of Density Functional Theory (DFT).
'First principles' simulations.
The different computational methods will be discussed in relation their application to topics of interest for material science (crystals, surfaces, soft matter, nanostructured materials).
In the computer exercises, students will carry out simple simulations, using opensource software packages of current use in materials science, and will learn how to interpret and present the results of simulations. 
Planned learning activities and teaching methods:

This course is taught by prof. Francesco Ancilotto and prof. Alberta Ferrarini.
The course is comprised of lectures and computer exercises. 
Additional notes about suggested reading:

Handouts and slides provided by the teacher. The teaching material will be made available on the teachers website. Furter material (general articles, papers on specific topics, user guide of software packages,...) will be shared in dropbox. 
Textbooks (and optional supplementary readings) 

M. P. Allen, D. .J. Tildesley, Computer simulation of liquids  2nd Edition. Oxford: Oxford University Press, 2017.

D. Frenkel, B. Smit, Understanding Molecular Simulations, 2nd edition. San Diego: Academic Press, 2002.

R. LeSar, Introduction to Computational Materials Science. Cambridge: Cambridge University Press, 2013.

Innovative teaching methods: Teaching and learning strategies
 Lecturing
 Laboratory
 Interactive lecturing
 Working in group
 Questioning
 Loading of files and pages (web pages, Moodle, ...)
Innovative teaching methods: Software or applications used
Sustainable Development Goals (SDGs)

