Minimizing thermal conductivity of crystalline material with optimal nanostructure

Minimizing thermal conductivity of crystalline material with optimal nanostructure
The optimum nanostructure designed with MI (aperiodic superlattice structure) was actually fabricated, and the optimal performance was verified by assessing its thermal conductivity. Figure: the Actual Structure is the electron microscope image of the fabricated sample. In addition, by further analyzing the phonon transport in the optimal structure, the mechanism that reduces thermal conductivity was clarified. Credit: The University of Tokyo

Professor Junichiro Shiomi et al. from the University of Tokyo aimed to reduce the thermal conductivity of semiconductor materials by reducing the internal nanostructure. The researchers successfully minimized thermal conductivity by designing, fabricating and evaluating the optimal nanostructure-multilayer materials through materials informatics (MI), which combines machine learning and molecular simulation. In 2017, this research group developed a method to design an optimal structure that minimizes or maximizes thermal conductivity via MI based on computational science. However, it had not been experimentally demonstrated, and preparation of nano-scale structures and realization of an optimal structure based on property measurements were desired.

Thus, the research group utilized a film deposition method able to regulate, at a , a superlattice structure wherein two materials were alternately layered at several nanometers thick, and a measurement method that could assess thermal conductivity of a film at nano-scale, and realized the optimal aperiodic superlattice structure that minimizes thermal conductivity. With the optimal structure, wave interference of the lattice vibration (phonon) that conducts heat was maximized, and thermal conductivity was strongly regulated.

In the present study, using the semiconductor lattice structure as the model, the research group verified the utility of the MI method in design, fabrication, assessment, and mechanism toward regulation of thermal conductivity. In the future, application of the MI method to various material systems is anticipated. It was also shown that optimization of the aperiodic structure can regulate thermal conductivity by fully controlling the wave property of a phonon at near room temperature. This is expected to contribute to developments in phonon engineering for instance in thermoelectric conversion devices, optical sensors, and gas sensors, where low is needed while maintaining electric conductivity and mechanical properties.

Explore further

Researchers use machine learning to aid oil production

More information: Run Hu et al. Machine-Learning-Optimized Aperiodic Superlattice Minimizes Coherent Phonon Heat Conduction, Physical Review X (2020). DOI: 10.1103/PhysRevX.10.021050
Journal information: Physical Review X

Provided by Japan Science and Technology Agency (JST)
Citation: Minimizing thermal conductivity of crystalline material with optimal nanostructure (2020, June 12) retrieved 19 January 2021 from
This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only.

Feedback to editors

User comments