Anno Accademico 2022/2023

  • Docente: Maria Clelia Righi
  • Crediti formativi: 6
  • SSD: FIS/03
  • Lingua di insegnamento: Inglese
  • Modalità didattica: Convenzionale - Lezioni in presenza
  • Campus: Bologna
  • Corso: Laurea Magistrale in Physics (cod. 9245)

Conoscenze e abilità da conseguire

At the end of the course the students will learn advanced modeling and simulation techniques to predict materials behavior over different scales. They will understand how the fundamental physics necessary to describe materials in terms of electrons and atoms enters in numerical simulations and how it relates to the macroscopic function of materials. The electronic structure will be treated by quantum mechanical calculations, atomistic processes by molecular dynamics, mesoscale evolution by kinetic Monte Carlo and machine learning.Through hands-on sessions the students will become able to design and perform computer experiments using (and linking) the computational methods that are more suitable for the problem at hand. They will be challenged in integrating in silico experiments to real experiments for solving problems that are fundamental in nature and yet have great technological impact. Applied case studies include: Chemical reactions at surfaces and interfaces; Tribological (adhesion and friction), Mechanical and Electronic properties of solids and 2D materials.


I. Methods for modeling:

1. Atomic Interactions

  • Density Functional Theory in a nutshell
  • Semi-empirical and Empirical Potentials
  • Machine-learning based Force Fields

2. Chemical Reactions and Rare Events

  • Transition State Theory
  • Methods for finding the Minimum Energy Path on Potential Energy Surfaces

3. System evolution on the atomistic scale

  • Introduction to Molecular Dynamics
  • Ab initio Molecular Dynamics

4. Multiscale phenomena

  • Quantum mechanics/molecular mechanics (QM/MM)
  • Kinetic Monte Carlo
  • Machine learning based molecular dynamics

5. Materials Design

  • High throughput, first-principles calculations


II. Applications

  1. Mechanical properties of solids
  2. Surfaces and Interfaces
  3. Cathalysis for H production and CO2 capture
  4. Materials growh
  5. Tribology (friction and adhesion) and Mechanochemistry
  6. Energy Harvesting



  • R. M. Dreizler and E. K. U. Gross Density functional theory: an approach to the quantum many-body problem
  • D. S. Sholl and J. A. Steckel Density Functional Theory: A Practical Introduction
  • D. Frankel and B. Smit Understanding Molecular Simulations
  • E. B. Tadmor and R. E. Miller Modeling Materials

Reviews and research articles are also part of the course reference readings. The full bibliography will be provided within the lecture notes.


Metodi didattici

Front lectures and practical sessions in the computational laboratory.

In considerazione della tipologia di attività e dei metodi didattici adottati, la frequenza di questa attività formativa richiede la preventiva partecipazione di tutti gli studenti ai Moduli 1 e 2 di formazione sulla sicurezza nei luoghi di studio, [https://elearning-sicurezza.unibo.it/] in modalità e-learning.

Modalità di verifica e valutazione dell'apprendimento

The exam will be constituted of both a practical part focused on the execution of a computational research project and a colloquium.

Strumenti a supporto della didattica

Blackboard, Slides, Computer applications

Orario di ricevimento

Consulta il sito web di Maria Clelia Righi