First-principles prediction of thermal conductivity and radiative properties
is crucial. However, computing phonon scattering, especially for four-phonon
scattering, could be prohibitively expensive, and the thermal conductivity even
for silicon was still under-predicted and not converged in the literature. Here
we propose a method to estimate scattering rates from a small sample of
scattering processes using maximum likelihood estimation. The computational
cost of estimating scattering rates and associated thermal conductivity and
radiative properties is dramatically reduced by over 99%. This allows us to use
an unprecedented q-mesh of 32*32*32 for silicon and achieve a converged thermal
conductivity value that agrees much better with experiments. The accuracy and
efficiency of our approach make it ideal for the high-throughput screening of
materials for thermal and optical applications