Argomenti di tesi proposti dal docente.
- 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
- Quantum Magnetism: 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
Ultime tesi seguite dal docente
Tesi di Laurea
- An Ab Initio Study of Magnetic Exchange Interactions and Spin Waves in bcc Iron
- Calcolo numerico del bandgap del silicio e dell'arseniuro di gallio
- Diagrammatic Monte Carlo for the Holstein Hamiltonian in the Atomic Limit
- First principles calculations of electronic properties of the altermagnet MnTe
- Path-Integral Molecular Dynamics using machine learned potentials for hydrogen diffusion
- Predizione del bandgap nei solidi tramite XGBoost
- Studio ab initio delle proprietà strutturali, elettroniche e magnetiche di LaMnO₃
- Studio computazionale delle proprietà fononiche dei solidi: dalla Density Functional Theory ai machine-learning force fields
- Studio fondamentale della fisica dei solidi: teoria del reticolo e
vibrazioni reticolari
Tesi di Laurea Magistrale
- Diagrammatic Monte Carlo for the Froehlich polaron in materials with anisotropic non-degenerate band extrema
non-degenerate band extrema
- Electronic Structure and Many-Body Effects in the Breathing Kagome Ferromagnet Nb3I8
- First Principles study of molecular
adsorption on SrTiO3 surfaces
- Intrinsic Electron Trapping in Amorphous SiO2: A First Principles Study of Small Polaron Formation and Precursor Site Identification
- Predicting the Raman Spectrum of KTaO3 Using Machine Learning Force Fields
