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Reducing interfacial thermal resistance by interlayer.

Dengke Ma1, Yuheng Xing2, Lifa Zhang1

  • 1Phonon Engineering Research Center of Jiangsu Province, Center for Quantum Transport and Thermal Energy Science, Institute of Physics Frontiers and Interdisciplinary Sciences, School of Physics and Technology, Nanjing Normal University, Nanjing 210023, People's Republic of China.

Journal of Physics. Condensed Matter : an Institute of Physics Journal
|December 21, 2022
PubMed
Summary
This summary is machine-generated.

Introducing interlayers effectively reduces interfacial thermal resistance (ITR) in electronics and batteries. This review explores bonding and bridging effects, graded interlayers, and machine learning for optimizing heat dissipation strategies.

Keywords:
graded materialsinterfacial bondinginterfacial thermal resistanceinterlayervibrational mismatch

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Area of Science:

  • Materials Science
  • Thermal Engineering
  • Nanotechnology

Background:

  • Effective heat dissipation is critical for the performance and longevity of modern electronics and energy storage systems.
  • Interfacial thermal resistance (ITR) significantly impedes heat transfer, necessitating advanced thermal management solutions.
  • Introducing interlayers is a prevalent industrial strategy to mitigate ITR.

Purpose of the Study:

  • To elucidate the mechanisms by which interlayers reduce interfacial thermal resistance (ITR).
  • To review current research on utilizing bonding and bridging effects for thermal management.
  • To discuss novel approaches like graded interlayers and machine learning for interlayer optimization.

Main Methods:

  • Review of theoretical principles behind bonding and bridging effects in interlayers.
  • Analysis of simulative and experimental studies on interlayer applications.
  • Examination of recent advancements in graded interlayers and machine learning for optimization.

Main Results:

  • Interlayers decrease ITR through bonding and bridging mechanisms, enhancing thermal transport.
  • Graded interlayers offer tunable properties for improved thermal management.
  • Machine learning algorithms show promise in optimizing interlayer design and performance.

Conclusions:

  • Interlayer engineering is a key strategy for reducing ITR and improving heat dissipation.
  • Further research into graded interlayers and AI-driven optimization can unlock new possibilities.
  • Addressing current challenges will pave the way for next-generation thermal management solutions.