NANOSIZED HETEROSTRUCTURES EFFECTIVE THERMAL CONDUCTIVITY COEFFICIENT MODELING USING MACHINE LEARNING
Karine Karlenovna Abgaryan, Computer Science and Control", Ilya Kolbin · 2020
In this work we construct neural network models of the effective thermal conductivity coefficient for heterogeneous nanostructures using GaAs / AlAs superlattices as an example; training sets are obtained from the modal suppression method