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thermal management, data mining, machine learning




日本熱物性学会, 日本熱物性学会


  • 2018年日本熱物性学会賞 (奨励賞) (2018)

Advancing interfacial thermal resistance prediction for thermal management in heterogeneous materials


Interfacial thermal resistance, Thermal management, Predictive modeling, Heterogeneous materials, Machine learning


This research aims to address the challenges associated with interfacial thermal resistance (ITR) and develop predictive models for efficient thermal management in various applications. The background that led to this study is the increasing need for accurate prediction and control of ITR in interfaces between dissimilar materials. In many practical scenarios, such as microelectronics and energy conversion systems, precise understanding and management of ITR are essential for optimal thermal behavior. To fulfill these needs, this study focuses on advancing our understanding of ITR mechanisms and developing predictive models for different material systems.


● This research combines machine learning and comprehensive descriptors to understand and predict ITR.
● Advanced Predictive Models: The study achieves a remarkable 96% accuracy with highly accurate predictive models for ITR, surpassing previous limitations.
● Exploration of Asymmetric ITR: The research uncovers the novel phenomenon of asymmetric ITR, revealing the interplay between interfacial electron-phonon couplings and temperature differences.
● Tunability of Thermal Conductance through interfacial chemical modifications.
● Efficient thermal management solutions in Thermal Insulators and Microelectronics



Our research focuses on advancing ITR prediction and control in heterogeneous materials for optimal thermal management. Through innovative machine learning techniques and comprehensive descriptors, we have achieved 96% accuracy in predicting ITR. We can develop ultra-low thermal conductivity thermal insulators and materials with tunable thermal and electrical conductance. This research meets the growing demand for efficient thermal management in industries like electronics, automotive, and energy. Going forward, we aim to collaborate with industry partners to apply our findings and develop cutting-edge thermal management technologies, enhanced insulating materials, and optimized microelectronic devices. This research opens up new possibilities for improved thermal management in diverse industries.


● Achievements: Significant advancements have been made in predicting and controlling ITR in heterogeneous materials, achieving a high accuracy rate of 96%.
● Potential Applications: The research holds promise for practical applications in fields such as microelectronics, energy systems, and thermal management.
● Future Goals: The focus will be on advancing thermal management technologies, optimizing thermal insulating materials, and enhancing microelectronic device performance.