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 require 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 values of the three MOFs
are all predicted to be smaller than 1 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
thermal conductivity only converges to the diffusive limit for micrometer
single crystals, which means that the thermal conductivity is heavily
reduced in nanocrystalline MOFs. The sub-micrometer phonon MFPs are
also found to be correlated with a moderate temperature dependence
of thermal conductivity between those in typical crystalline and amorphous
materials. Both the large phonon MFPs and the moderate temperature
dependence of thermal conductivity fundamentally change our understanding
of thermal transport in MOFs.