  Tuning interfacial thermal conductance has been a key task for the thermal
management of nanoelectronic devices. Here, it is studied how the interfacial
thermal conductance is great influenced by modulating the mass distribution of
the interlayer of one-dimensional atomic chain. By nonequilibrium Green's
function and machine learning algorithm, the maximum/minimum value of thermal
conductance and its corresponding mass distribution are calculated.
Interestingly, the mass distribution corresponding to the maximum thermal
conductance is not a simple function, such as linear and exponential
distribution predicted in previous works, it is similar to a sinusoidal curve
around linear distribution for larger thickness interlayer. Further, the
mechanism of the abnormal results is explained by analyzing the phonon
transmission spectra and density of states. The work provides deep insight into
optimizing and designing interfacial thermal conductance by modulating mass
distribution of interlayer atoms.
