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Tuning interfacial thermal conductance has been a key task for the thermalmanagement of nanoelectronic devices. Here, it is studied how the interfacialthermal conductance is great influenced by modulating the mass distribution ofthe interlayer of one-dimensional atomic chain. By nonequilibrium Green'sfunction and machine learning algorithm, the maximum/minimum value of thermalconductance and its corresponding mass distribution are calculated.Interestingly, the mass distribution corresponding to the maximum thermalconductance is not a simple function, such as linear and exponentialdistribution predicted in previous works, it is similar to a sinusoidal curvearound linear distribution for larger thickness interlayer. Further, themechanism of the abnormal results is explained by analyzing the phonontransmission spectra and density of states. The work provides deep insight intooptimizing and designing interfacial thermal conductance by modulating massdistribution of interlayer atoms.

Maximization and Minimization of Interfacial Thermal Conductance by Modulating the Mass Distribution of Interlayer