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Vertically aligned carbon nanotubes arrays (VACNTs) are a promising candidate for the thermal interface material (TIM) of next-generation electronic devices due to their attractive thermal and mechanical properties. However, the environment required for synthesizing VACNTs is harsh and severely incompatible with standard device packaging processes. VACNTs’ extremely low in-plane thermal conductivity also limits its performance for cooling hot spots. Here, using a transfer-and-encapsulate strategy, a two-step soldering method is developed to cap both ends of the VACNTs with copper microfoils, forming a standalone Cu-VACNTs-Cu sandwich TIM and avoiding the need to directly grow VACNTs on chip die. This new TIM is fully compatible with standard packaging, with excellent flexibility and high thermal conductivities in both in-plane and through-plane directions. The mechanical compliance behavior and mechanism, which are critical for TIM applications, are investigated in depth using in situ nanoindentation. The thermal performance is further verified in an actual light emitting diode (LED) cooling experiment, demonstrating low thermal resistance, good reliability, and achieving a 17 °C temperature reduction compared with state-of-the-art commercial TIMs. This study provides a viable solution to VACNTs’ longstanding problem in device integration and free-end contact resistance, bringing it much closer to application and solving the critical thermal bottleneck in next-generation electronics.

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Publication history
Copyright
Acknowledgements

Publication history

Received: 16 March 2023
Revised: 10 May 2023
Accepted: 24 May 2023
Published: 17 July 2023
Issue date: August 2023

Copyright

© Tsinghua University Press 2023

Acknowledgements

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 52076041), the Natural Science Foundation of Jiangsu Province (No. BK20200371), and the Nanjing Carbon Peak and Carbon Neutrality Science and Technology Innovation Project (No. 202211009). We thank the Big Data Computing Center of Southeast University for providing the facility support on the numerical calculations in this paper.

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