  Metal-organic frameworks (MOFs) are a family of materials that have high
porosity and structural tunability and hold great potential in various
applications, many of which requiring a proper understanding of the thermal
transport properties. Molecular dynamics (MD) simulations play an important
role in characterizing the thermal transport properties of various materials.
However, due to the complexity of the structures, it is difficult to construct
accurate empirical interatomic potentials for reliable MD simulations of MOFs.
To this end, we develop a set of accurate yet highly efficient machine-learned
potentials for three typical MOFs, including MOF-5, HKUST-1, and ZIF-8, using
the neuroevolution potential approach as implemented in the GPUMD package, and
perform extensive MD simulations to study thermal transport in the three MOFs.
Although the lattice thermal conductivity (LTC) values of the three MOFs are
all predicted to be smaller than 1 $\rm{W/(m\ K)}$ at room temperature, the
phonon mean free paths (MFPs) are found to reach the sub-micrometer scale in
the low-frequency region. As a consequence, the apparent LTC only converges to
the diffusive limit for micrometer single crystals, which means that the LTC is
heavily reduced in nanocrystalline MOFs. The sub-micrometer phonon MFPs are
also found to be correlated with a moderate temperature dependence of LTC
between those in typical crystalline and amorphous materials. Both the large
phonon MFPs and the moderate temperature dependence of LTC fundamentally change
our understanding of thermal transport in MOFs.
