95746 - Materials Modelling and Design

Learning outcomes

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.

Course contents

METHODS

1. Atomic Interactions

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

2. System evolution on the atomistic scale

• Introduction to Molecular Dynamics
• Ab initio Molecular Dynamics

3. Chemical Reactions and Rare Events

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

4. Multiscale simulations

• Kinetic Monte Carlo
  
• Machine learning based molecular dynamics

5. Materials Design

• Introduction to high throughput, first-principles calculations

 

SYSTEMS EXPLORED THROUGH HANDS-ON ACTIVITIES

1. BULKS

• Equilibrium lattice parameter and bulk modulus derived from the Murnaghan equation of state
• Determining the optimal computational parameters for plane-wave, pseudopotentials ab initio calculations.

2. SURFACES

• Miller indexes, surface relaxation and reconstruction, surface energy
• Setting up and optimizing the surface model, ab initio calculation of surface energy

3. MOLECULAR ADSORPTION AND DISSOCIATION

• Molecular physisorption and chemisorption
• Identifying the most stable adsorption configuration and energy for a molecule on a surface
• Ab initio calculation of the reaction energy for molecular dissociation
• Ab initio calculation of the energy barrier for molecular dissociation by means of the nudging elastic band method

4. SOLID INTERFACES

• Constructing and optimizing the model for solid interfaces
• Simulating the dynamics of molecules confined at interfaces

Readings/Bibliography

Books

• 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.

Teaching methods

Front lectures and practical sessions in the computational laboratory

Considering the type of activity and the teaching methods adopted, attendance of this training activity requires the prior participation of all students in Modules 1 and 2 of training on safety in the places of study, [https://elearning-sicurezza.unibo .it/] in e-learning mode.

Assessment methods

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

Teaching tools

Blackboard, Slides, Computer applications

Office hours

See the website of Maria Clelia Righi