Critical transition of thermal rectification on complex networks

Abstract

Thermal rectification is a mechanism that controls the direction of heat conduction, allowing it to flow freely in one direction and hindering it in the opposite direction. In this study, we propose a heat conduction model on a complex network where the node masses are non-uniformly distributed according to mi∼kiα. Our findings show that the existence of a critical point, α=1, determines the working mode of thermal rectification. For α>1, the working mode of thermal rectification is positive, whereas for α<1, the working mode is negative. Additionally, we discovered that this critical transition is a general phenomenon and does not vary with changes in network size, average degree, or degree distribution. By conducting theoretical analyses based on phonon spectra, we also identified the physical mechanism of the critical transition. These results provide a new approach to implement and enrich thermal diodes, opening up new possibilities for more efficient thermal management.

Prediction of Thermal Conductance of Complex Networks with Deep Learning

“…[18][19][20][21][22] To better understand heat transfer in networks, nodes can be considered as junctions, while the edges signify the connection between these junctions. [23] The key distinction between complex networks and 1D/2D lattices lies in the distribution of node degrees: lattices have uniformly distributed degrees for each node, whereas random networks exhibit varying degrees among different nodes. [24][25][26][27][28] Additionally, several other factors influence heat transport in complex networks, including clustering coefficients, average shortest distances, assortativity coefficient, and masses of nodes.…”