Abo Bibliothek: Guest

ISSN Online: 2377-424X

ISBN Print: 978-1-56700-474-8

ISBN Online: 978-1-56700-473-1

International Heat Transfer Conference 16
August, 10-15, 2018, Beijing, China

DESIGNING NANOSTRUCTURES FOR HEAT TRANSPORT VIA MATERIALS INFORMATICS

Get access (open in a dialog) DOI: 10.1615/IHTC16.nmt.023928
pages 7323-7330

Abstrakt

As the length scales of materials are reduced to nanoscale, it becomes possible to tune heat carrying phonons transport by manipulating the nanostructures. However, it is rather difficult to identify the detail optimal structure for heat transport due to the various parameters and coupled interference/resonance effects. The key next-generation technology can be materials informatics, which is a new interdisciplinary research to provide efficient tools to accelerate the materials discovery and design. In this work, we present two successful materials informatics approaches in designing nanostructures for heat transport: Bayesian optimization and Monte Carlo tree search. Bayesian optimization is good at dealing cases with limited number of candidates and finding optimal candidate as quickly as possible, while Monte Carlo tree search can handle cases with huge or unlimited number of candidates. We apply both algorithms to design the Si/Ge interfacial alloy structures that minimize/maximize the interfacial thermal conductance across Si-Si and Si-Ge interfaces. The result indicates that using Bayesian optimization the optimal structures can be obtained by calculating only a few percent of the total candidates, considerably saving the computational resources. In comparison to Bayesian optimization, the Monte Carlo tree search algorithm has shown competitive search efficiency and superior scalability for targeting candidates that are approaching the global optimal ones. The present work has shown great advantage of materials informatics in designing nanostructures to control heat transport, which can be extended to other nanostructures and properties.