Maria Clelia Righi

Thesis projects are embedded within the research activities of our group [http://www.tribchem.it], which develops and applies advanced computational tools to model materials behaviour and design improved materials for technological applications. The main computational approaches employed in our research are:

1. Molecular dynamics simulations based on machine learning interatomic potentials.
Using our in-house software [https://tribchem.it/?page_id=3628]SCS [http://https://tribchem.it/?page_id=3628], we train accurate machine learning interatomic potentials for large-scale molecular dynamics simulations of realistic systems, such as sliding interfaces, catalytic hydrogen production, and earthquake nucleation.

2. High-throughput screening of surfaces and interfaces.
Using our in-house software packages TribChem [https://tribchem.it/?page_id=1663] and XSorb [https://tribchem.it/?page_id=3106], we screen the properties of hundreds of interfaces and build databases of properties such as adsorption and adhesion energies, shear and cleavage strengths, and electronic properties.

3. Fundamental understanding of materials under extreme conditions.
Using first-principles methods, we investigate mechanochemical processes and other phenomena occurring under high mechanical stresses or at high temperatures to gain a fundamental understanding of the materials behaviour in extreme conditions.

Our group welcomes students with different backgrounds and aspirations. Thesis projects can, in fact, be oriented towards:

• Scientific software development, for students interested in computational methods and code development.
• In silico experiments, involving the application of state-of-the-art simulation techniques to investigate technologically relevant materials and interfaces.
• Developing new fundamental understanding of complex phenomena in materials under extreeme conditions.
• Industrial collaborative projects, carried out in partnership with multinational companies that have long-standing collaborations with our group, where students address real-world technological challenges using advanced computational materials science.