Thermo-hydrodynamic characteristics of hybrid nanofluids for chip-level liquid cooling in data centers: a review of numerical investigations
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| Title: | Thermo-hydrodynamic characteristics of hybrid nanofluids for chip-level liquid cooling in data centers: a review of numerical investigations |
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| Authors: | Li, Yifan, Zhu, Congzhe, Lyu, Zhihan, Yang, Bin, Olofsson, Thomas, 1968 |
| Source: | Energy Engineering. 122(9):3525-3553 |
| Subject Terms: | chip-level liquid cooling, Data centers, energy transport characteristic, hybrid nanofluid, hydrodynamic performance, numerical investigation |
| Description: | The growth of computing power in data centers (DCs) leads to an increase in energy consumption and noise pollution of air cooling systems. Chip-level cooling with high-efficiency coolant is one of the promising methods to address the cooling challenge for high-power devices in DCs. Hybrid nanofluid (HNF) has the advantages of high thermal conductivity and good rheological properties. This study summarizes the numerical investigations of HNFs in mini/micro heat sinks, including the numerical methods, hydrothermal characteristics, and enhanced heat transfer technologies. The innovations of this paper include: (1) the characteristics, applicable conditions, and scenarios of each theoretical method and numerical method are clarified; (2) the molecular dynamics (MD) simulation can reveal the synergy effect, micro motion, and agglomeration morphology of different nanoparticles. Machine learning (ML) presents a feasible method for parameter prediction, which provides the opportunity for the intelligent regulation of the thermal performance of HNFs; (3) the HNFs flow boiling and the synergy of passive and active technologies may further improve the overall efficiency of liquid cooling systems in DCs. This review provides valuable insights and references for exploring the multi-phase flow and heat transport mechanisms of HNFs, and promoting the practical application of HNFs in chip-level liquid cooling in DCs. |
| File Description: | electronic |
| Access URL: | https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-244098 https://doi.org/10.32604/ee.2025.067902 |
| Database: | SwePub |
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Nájsť tento článok vo Web of Science | Abstract: | The growth of computing power in data centers (DCs) leads to an increase in energy consumption and noise pollution of air cooling systems. Chip-level cooling with high-efficiency coolant is one of the promising methods to address the cooling challenge for high-power devices in DCs. Hybrid nanofluid (HNF) has the advantages of high thermal conductivity and good rheological properties. This study summarizes the numerical investigations of HNFs in mini/micro heat sinks, including the numerical methods, hydrothermal characteristics, and enhanced heat transfer technologies. The innovations of this paper include: (1) the characteristics, applicable conditions, and scenarios of each theoretical method and numerical method are clarified; (2) the molecular dynamics (MD) simulation can reveal the synergy effect, micro motion, and agglomeration morphology of different nanoparticles. Machine learning (ML) presents a feasible method for parameter prediction, which provides the opportunity for the intelligent regulation of the thermal performance of HNFs; (3) the HNFs flow boiling and the synergy of passive and active technologies may further improve the overall efficiency of liquid cooling systems in DCs. This review provides valuable insights and references for exploring the multi-phase flow and heat transport mechanisms of HNFs, and promoting the practical application of HNFs in chip-level liquid cooling in DCs. |
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| ISSN: | 01998595 15460118 |
| DOI: | 10.32604/ee.2025.067902 |