Topic: Advances in Machine Learning for Thermal Management and Thermoelectric Conversion Materials Research and Applications

The increasing integration, high frequency and miniaturization of micro-nano electronic and optoelectronic devices have resulted in a sharp rise in the heat flux per unit area. This escalation can significantly elevate device temperatures, seriously affecting reliability and service life. Therefore, effective thermal management and cooling techniques are very important. Thermoelectric materials, which can directly convert electrical and thermal energy into one another, hold significant promise for applications in waste heat recovery and active refrigeration. Therefore, it is of great significance to study the heat transport and thermoelectric conversion properties of materials and devices. In recent years, machine learning methods have emerged as powerful tools for research in this domain.

This Special Issue aims to present and disseminate the most recent advances across a broad spectrum of topics related to the theory, mechanisms, design, modeling, application and control of thermal management and thermoelectric conversion materials and devices by using machine learning methods.

30 Apr 2025