Advances in fabricating nanostructured devices and thermal conductivity measurements have revealed that Fourier's law fails at the nanoscales. In fact, when the characteristic length of a material becomes comparable with the mean-free-path (MFP) of phonons a significant fraction of heat becomes ballistic. Nondiffusive models based on the Boltzmann transport equation (BTE) have shown remarkable agreement with experiments on simple geometries. However, the inherent difficulties in handling both momentum and real space across several length scales have limited the development of solvers of heat transport in complex geometries. In the first part of the talk, I will describe our recent efforts toward the development of heat transport models that are both reliable and computational efficient. Special emphasis will be given to complex-shaped 2D materials, where the BTE with the full scattering operator is needed. As an example, thermal conductivity calculations of porous graphene will be reported. The last part of the talk will focus on optimization of low-thermal conductivity nanostructured materials via machine learning.
Dr. Giuseppe Romano is a research scientist at the Massachusetts Institute of Technology, where he leads the Inverse Design of Materials and Devices group. In 2018 he was a visiting scientist at the Jet Propulsion Lab, investigating the next generation of the radioisotope thermoelectric generator. He is broadly interested in data-driven materials discovery for energy conversion. His current focus is nanoscale heat transport and AI-driven optimization of nanomaterials for thermoelectrics and photovoltaics. Dr. Romano joined MIT in 2010 as a postdoctoral associate after receiving his PHD from the University of Rome Tor Vergata.