The prediction of heat and mass transfer properties of modern nanostructured materials is required to push them from lab to mass production in a broad variety of industries, especially in the energy, aerospace, chemical, and biomedical fields. This course aims at introducing the main ideas associated with the modelling of heat and mass transfer phenomena at the nanoscale, with the final target to develop multi-scale models of components made of nanostructured materials. The recent possibility of coupling machine learning tools with multi-scale materials modelling will be also discussed. In the course, the theoretical aspects related to nanoscale heat and mass transfer will be accompanied by hands-on activities on some common simulation techniques (e.g. Monte Carlo, molecular dynamics). Examples of modelling approaches spanning from nano- to macro-scale will be provided, with focus on nanocolloids, nanocomposites, and nanoporous materials.

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Fundamentals of energy transport by principal energy carriers: electrons, phonons, fluid particles, photons. Theoretical framework: overview of statistical thermodynamics, kinetic theory, lattice dynamics. Heat transfer at the nanoscale: thermal properties of solids and size effects, phonon transport and interface scattering (thermal boundary resistance). Mass transfer at the nanoscale: viscosity and diffusivity of nanoconfined fluids, velocity slip. (5 hours) Research highlights on quantum effects and heat transfer: the quantum reform in metrology; single-particle Schrödinger equation; multiple-particle Schrödinger equation; Density Functional Theory (DFT); phonons and thermal conductivity. (3 hours) Introduction to classical molecular mechanics. Interaction potentials: classical and reactive ones (e.g. based on machine learning algorithms). Computational algorithms and post-processing techniques in atomistic simulations. Examples of Monte Carlo and molecular dynamics simulations: nanocolloids for solar thermal and theragnostic applications; nanocomposites for aerospace and automotive applications; nanoporous materials for thermal energy storage, desalination, and drug delivery; nanostructured solid-liquid interface with tuneable wetting. Machine learning and multi-scale tools for enhanced materials modelling. (4 hours) Hands-on laboratory on molecular dynamics simulations (GROMACS software): geometry and topology creation, energy minimization, setup equilibration, equilibrium/non-equilibrium simulations, post-processing of molecular dynamics trajectories. (8 hours)

Modalità mista

Presentazione orale

P.D.2-2 - Luglio

The lectures will be in July, both online (with recorded lectures and labs) and in presence. The exact calendar will be defined by May 2025 and communicated via email.