Efficient Calculation of the Lattice Thermal Conductivity by Atomistic Simulations with Ab Initio Accuracy

High-order force constant expansions can provide accurate representations of the potential energy surface relevant to vibrational motion. They can be efficiently parametrized using quantum mechanical calculations and subsequently sampled at a fraction of the cost of the underlying reference calculations. Here, force constant expansions are combined via the hiphive package with GPU-accelerated molecular dynamics simulations via the GPUMD package to obtain an accurate, transferable, and efficient approach for sampling the dynamical properties of materials. The performance of this methodology is demonstrated by applying it both to materials with very low thermal conductivity (Ba₈Ga₁₆Ge₃₀, SnSe) and a material with a relatively high lattice thermal conductivity (monolayer-MoS₂). These cases cover both situations with weak (monolayer-MoS₂, SnSe) and strong (Ba₈Ga₁₆Ge₃₀) pho renormalization. The simulations also enable to access complementary information such as the spectral thermal conductivity, which allows to discriminate the contribution by different phonon modes while accounting for scattering to all orders. The software packages described here are made available to the scientific community as free and open-source software in order to encourage the more widespread use of these techniques as well as their evolution through continuous and collaborative development.

Brorsson Joakim, Hashemi Arsalan, Fan Zheyong, Fransson Erik, Eriksson Fredrik, Ala-Nissila Tapio, Krasheninnikov Arkady V., Komsa Hannu-Pekka, Erhart Paul

A1 Journal article – refereed

Brorsson, J., Hashemi, A., Fan, Z., Fransson, E., Eriksson, F., Ala-Nissila, T., Krasheninnikov, A.V., Komsa, H.-P. and Erhart, P. (2022), Efficient Calculation of the Lattice Thermal Conductivity by Atomistic Simulations with Ab Initio Accuracy. Adv. Theory Simul., 5: 2100217. https://doi.org/10.1002/adts.202100217

https://doi.org/10.1002/adts.202100217 http://urn.fi/urn:nbn:fi-fe2022030922691