This symposium will broadly cover current and emerging data generation techniques and data driven analysis approaches to characterize phonons, the quantized vibrations of condensed matter systems. Phonons play an increasingly important role in information-processing applications, both directly and indirectly through interactions with other quasiparticles and energy carriers. A key focus of the symposium will remain on thermal properties of materials enabling such applications. Additionally, studies exploring co-optimization of properties of multiple carriers (e.g., electron and phonon) in a variety of materials, such as thermoelectrics, wide-bandgap semiconductors, and photovoltaics, will be of particular interest. The first part of the symposium will focus on emerging theoretical and experimental techniques to calculate/measure phononic properties of complex materials. Symposium contributions should address basic science issues or highlight exploration of unusual phenomena (e.g., glass like phonon transport in crystals and/or low-symmetry materials), and address challenges in understanding the corresponding physical mechanisms. Discussion of theoretical, computational or experimental characterization techniques, challenges in data generation and applicability of emerging materials for technologies are also welcomed. The second part will focus on machine learning (ML) approaches for phononic property prediction, that are of mutual interest of the broader materials informatics communities. ML-enabled design and discovery of new materials are increasingly being facilitated by large amounts of data available through databases, however, the availability of phonon properties data is limited. Discussion of development and application of physics-based ML models that can work with sparse data and provide consistent validation approaches are particularly of interest. Contributions discussing availability of data and methods to improve data sharing practices are also of interest.
Symposium Organizers
Sanghamitra Neogi
University of Colorado Boulder
Ann and H.J. Smead Aerospace Engineering Sciences
USA
Ming Hu
University of South Carolina
Department of Mechanical Engineering
USA
Subramanian Sankaranarayanan
Argonne National Laboratory
Theory and Modeling Group
USA
Junichiro Shiomi
The University of Tokyo
Department of Mechanical Engineering
Japan