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Publishing Language: Chinese | Open Access

Research Progress on Liquid Cooling Technologies for High-Power and Large-Area AI Chips

Qifan Zou1,3Hong Liu2Hailiang Luo2Ronggui Yang1,2,3( )
School of Energy and Power Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China
China Mobile Group Design Institute Co., Ltd., Beijing, 100080, China
Department of Energy Resources Engineering, School of Mechanics and Engineering Science, Peking University, Beijing, 100871, China
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Abstract

With advances in artificial intelligence (AI), massive computing demands have driven the development of AI chips. In particular, the recently proposed chiplet technology provides an advanced chip packaging and integration solution that offers high computing performance at a high yield rate and low cost, thus delivering solid hardware support for AI development. Chiplet-based chips are characterized by large area and high heat power, and their 3D chip stacking design leads to cooling challenges such as non-uniform heat flux distribution, long heat conduction paths for multilayer chips, and relatively thick thermal interface materials. These thermal issues are key bottlenecks limiting chip performance, making efficient chiplet thermal management a critical challenge in AI development. The progress in advanced liquid cooling technologies, including single- and two-phase liquid cooling solutions, is reviewed. Based on the cooling architecture, liquid cooling solutions can be categorized as cold-plate, near-junction-region, and immersion liquid cooling. In addition, the heat dissipation challenges and cooling strategies in 2.5D and 3D chiplets are summarized, providing a reference for the application and development of liquid cooling technologies for high-power, large-area AI chips.

CLC number: TK124; TN305.94 Document code: A Article ID: 0253-4339(2026)01-0020-17

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Journal of Refrigeration
Pages 20-36

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Cite this article:
Zou Q, Liu H, Luo H, et al. Research Progress on Liquid Cooling Technologies for High-Power and Large-Area AI Chips. Journal of Refrigeration, 2026, 47(1): 20-36. https://doi.org/10.12465/issn.0253-4339.20251011001

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Received: 11 October 2025
Revised: 04 November 2025
Accepted: 04 November 2025
Published: 16 February 2026
© 2026 The Editorial Office of Journal of Refrigeration

This is an open access article under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0, http://creativecommons.org/licenses/by/4.0/).