Prof. Sanghamitra Neogi is an Assistant Professor in the Ann and H.J. Smead Department of Aerospace Engineering Sciences at the University of Colorado Boulder since Fall 2015. Prior to joining UC Boulder, she received her Ph.D. in theoretical condensed matter physics from the Pennsylvania State University in 2011 and was a postdoctoral research associate at the Max Planck Institute for Polymer Research, Mainz, Germany.
Her research is in the field of theoretical and computational solid-state materials physics, with a focus on nanoscale heat transport, nanophononics, electronic transport and electron-phonon coupling, thermal and electronic properties of semiconductor heterostructures and data driven methods for electronic and thermal property prediction and probing spin-phonon interaction in solid state quantum systems.
Phonons, quantum mechanics, nanoscale, tuning phonons
Controlling local thermal properties of nanostructures: Perspective from atomistic modeling and data driven techniques
Quantized vibrations in condensed phases, phonons, obey the laws of quantum mechanics in the same way as electrons and photons, that are commonly exploited as energy and/or information carriers. Efforts to control phonons, especially at micro- and nanoscale, have been stimulated by the ever-increasing roles that phonons assume via self-interaction and interacting with other quasiparticles such as electrons and photons. However, a broad range of phonon frequencies needs to be engineered, in contrast with electronic applications, where only energies close to the Fermi level are relevant. The difficulty of working with a broad spectrum of excitations naturally poses major challenges in achieving control over nanoscale phonon transport. Engineered nanoscale features offer remarkable possibilities to manipulate phonons in nanostructures. My research program at the University of Colorado Boulder is focused on the central theme—to develop fundamental insights on tuning phonons and their interactions with other quantum particles via engineering of nanostructured materials—to enable nanoelectronics, thermoelectric and quantum technology applications.
Atomistic modelling techniques for phonon transport property prediction have progressed rapidly in recent years, however, it remains a challenge to model phononic/thermal properties of nanostructures reflecting fabrication dependent variability. Machine-learning-based-material-informatics (MI) approaches are increasingly used to accelerate design and discovery of new materials with targeted properties, however, few studies exploited MI to learn the atomic scale dynamics or physics of carrier transport in nanostructures. There is great benefit to exploit MI approaches to harness information from atomistic models and predict thermal properties of nanostructures. Such approaches will inform the design of nanostructured materials with targeted thermal environments for energy efficient chips as well as a broad range of existing and future technologies. In this seminar, I will present an overview of the research activities in my group, with particular emphasis on our study of phonon transport properties of nanostructured materials and development of machine learning models for thermal property predictions.