Dissertation topics suggested by the teacher.
- Machine Learning for Materials: on-the-fly Machine Learning Force Fields (MD), Bayesian optimization (Potential Energy surfaces), Neural Networks, Generative ML algorithms. Development and application to different area of materials science (charge dynamics, hydrogen diffusion, defects in solids, energy materials)
- High-throughput calculations of optical and magnetic properties
- Diagrammatic QuantumMonte Carlo: prediction of unconventional non-collinear spin ordering using first principles methods, many body techniques and Machine Learning
- Correlated and spin-orbit coupled 2D magnets
- Diagrammatic Quantum Monte Carlo : fundamentals, code development,ML-augmented DiagMC
- Electron-phonon interaction: polaron physics, anharmonic effect in using first principles methods and machine learning force field: bulk and surfaces
- Computational Surface Science and computational single atom catalysis
Recent dissertations supervised by the teacher.
First cycle degree programmes dissertations
- Analytical and numerical study of polarons
- Calcoli a primi principi per l'assorbimento di idrogeno su grafene arricchito da adatomi metallici
- Calcoli analitici ed a principi primi di tipiche strutture elettroniche per reticolo triangolare, esagonale e kagome.
- Calcolo a primi principi dell’energia di gap
della perovskite CH3NH3PbI3 per
applicazioni a celle solari
- La superconduttività dalla teoria BCS tradizionale al caso dei cuprati con annessa risoluzione numerica dell’equazione di gap in condizione di interazione anisotropa
- Metodi per la stima ab initio del gap energetico nei materiali
- Modellizzazione di polaroni in DFT: TiO2 Rutilo
- Theoretical models and ab initio calculations of phonons
- Transizioni di fase: da Ising alla ferroelettricità
Second cycle degree programmes dissertations
- Automated Workflows for electronic Structure Calculations using the AiiDA Platform
- Enhancing Diagrammatic Monte Carlo via machine learning
- Predicting the quasiparticle energies and bandgaps of bulk materials with machine learning techniques
PhD programmes thesis
- Excitonic properties of transition metal oxide perovskites and workflow automatization of GW schemes
