01 / Funded projects
Phonon transport in metamaterials: thermal management, thermoelectrics, etc.
NSF Thermal Transport Processes program (07/2021-06/2026).
NSF CAREER Award
Both thermoelectric and thermal barrier materials must have low thermal conductivity, while a high thermal conductivity is desired for many thermal management applications. The increase in the thermoelectric figure of merit ZT based on nanostructuring has reached a plateau, largely because of the strongly coupled electrical conductivity, Seebeck coefficient, and the thermal conductivity of materials. Metamaterials provides a promising route to decouple electron transport and phonon transport. Notably, it provides strong phonon scatterings and possibly induce strong phonon localization. Our group work extensively on designing novel structures using molecular dynamics, lattice dynamics, and Boltzmann equations aided by first-principles methods, and, machine learning (of course!). We aim to develop nanostructured (meta)materials with strong localization of phonons but preserving low scattering of electrons, which will eventually lead to advanced thermoelectric materials with high ZT that could replace traditional power generators and coolers.
Related publications & highlights
News
Publications to date (more updated publication list at our Publications page)
[5] Tengfei Ma, Cheng-Te Lin, and Yan Wang*, "The Dimensionality Effect on Phonon Localization in Graphene/Hexagonal Boron Nitride Superlattices," 2020 2D Mater. 7 035029.
- Highlights: How does the 3rd dimension affect coherent phonon transport and localization? Is the lower thermal conductivity of aperiodic superlattice than its periodic counterpart caused by localization or scattering? How does each phonon mode behave in an aperiodic superlattice? We have provided some preliminary answers in this paper (and there are many more to explore in the future).
[4] Pranay Chakraborty, Yida Liu, Tengfei Ma, Xixi Guo, Lei Cao, Run Hu*, and Yan Wang*, "Quenching Thermal Transport in Aperiodic Superlattices: a Molecular Dynamics and Machine Learning Study," ACS Appl. Mater. Interfaces 2020, 12, 7, 8795-8804.
- Thanks to the recent advancements in machine learning, we were able to use this technique to study the aperiodic superlattice structure, which has a tremendously large design space. Highlights: We demonstrated the effectiveness of the neural network method for predicting the thermal conductivity of aperiodic superlattices. We also proposed a few effective parameters to quantify the randomness of the configuration.
[3] Pranay Chakraborty, Lei Cao, and Yan Wang*, "Ultralow lattice thermal conductivity of the random multilayer structure with lattice imperfection," Sci. Rep. 7 (1), 8134 (2017).
- Highlights: Randomizing the layer thicknesses in superlattices can localize (a fancier word used nowadays, "quench") the coherent phonons, how to deal with the remaining incoherent phonons? We proposed to use point defects to scatter rather shorter-wavelength incoherent phonons and reduced the thermal conductivity even further.
[2] Yan Wang, Chongjie Gu, and Xiulin Ruan, "Optimization of the random multilayer structure to break the random-alloy limit of thermal conductivity," Appl. Phys. Lett., 106, 073104, 2015.
- Highlights: We systematically investigated and proposed physics-informed strategies to optimize aperiodic superlattices, also called random multilayers, toward lower lattice thermal conductivity.
[1] Yan Wang, Haoxiang Huang, and Xiulin Ruan, "Decomposition of coherent and incoherent phonon conduction in superlattices and random multilayers," Phys. Rev. B 90, 165406, 2014.
- Highlights: We found greatly reduced thermal conductivity in aperiodic superlattices than their periodic counterparts; we established a rigorous two-phonon model to quantify the contribute of coherent phonons, which can be localized in aperiodic superlattices, and incoherent phonons, which are scattered at the interfaces, to the overall thermal transport.