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Updated: May 16, 2025

Characterization of Thermal Transport in One-dimensional Solid Materials
Published on: January 26, 2014
Machine learning-assisted study on the thermal transport properties of two-dimensional M3(C6O6)2(M = Fe, Co, Ni)
Meng-Jiao Teng1, Li-Qin Deng2, Pin-Zhen Jia2
1School of Materials Science and Engineering & Hunan Provincial Key Laboratory of Advanced Materials for New Energy Storage and Conversion, Hunan University of Science and Technology, Xiangtan 411201, People's Republic of China.
Abstract:
Two-dimensional metal-organic frameworks (MOF) are widely used in electronic devices and energy storage due to their large surface area, abundant active sites, and tunable sizes. A deeper understanding of the thermal transport properties of two-dimensional MOF materials is essential for these applications. In this work, we systematically studied the thermal transport properties of M3(C6O6)2(M = Fe, Co, Ni) by using a machine learning interatomic potential method combined with the phonon Boltzmann transport equation. The results show that the lattice thermal conductivities of Fe3(C6O6)2, Co3(C6O6)2, and Ni3(C6O6)2at room temperature are 4.0 W mK-1, 5.5 W mK-1, and 5.8 W mK-1, respectively. The differences in thermal conductivity primarily arise from variations in phonon relaxation times, which can be elucidated by examining the three-phonon scattering phase space. Further analysis of bond strengths reveals that the strong bonding between Fe and O impedes phonon propagation through the oxygen atoms, resulting in lower lattice thermal conductivity. Our work provides a fundamental reference for understanding thermal transport in two-dimensional MOF.
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