How to design a nanostructure with prescribed transport properties? While several topology optimization methods have been developed for macroscale scenarios, they can’t be readily applied to nanoscale devices. When the feature size of the material becomes comparable with the particles’ mean-free path, flux becomes nondiffusive, and a momentum-resolved model is needed. On the other side, standard material interpolation methods, such as SIMP, are mainly applied to averaged quantities, such as the local thermal conductivity. In this talk, I will discuss the “Transmission Interpolation Method” (TIM), a novel approach we recently developed to overcome this limitation. Instead of parametrizing the material distribution in terms of locally resolved variables, TIM acts on the interfacial flux, linking the material density with fictitious particle transmission. The talk will show the application of TIM to two examples: Tuning the effective thermal conductivity tensor of a nanostructure and maximizing phonon size effects. I will conclude the talk with final remarks and future developments.
Giuseppe Romano is a research scientist at the Massachusetts Institute of Technology. His research integrates multiscale modeling, machine-learning, and high-performance computing to accelerate the discovery of energy materials. Recent focus includes the inverse design of devices for photovoltaic and thermoelectric applications. He is the PI/co-PI of projects funded by the MIT-IBM Watson AI Lab and NASA. He is the developer of OpenBTE, an open-source software for simulating nanoscale thermal transport in arbitrary geometries, and coordinated the development of ∂PV, a differentiable solar cell simulator. In 2019, he was a Distinguished Visiting Scientist at the University of Colorado, Boulder, and in the Fall of 2018, he was a visiting scientist at the NASA Jet Propulsion Lab. He joined MIT in 2010 after receiving his Ph.D. in Electrical Engineering from the University of Rome Tor Vergata.