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Two-phase thermal management offers cooling performance enhancement by an order of magnitude higher than single-phase flow due to the latent heat associated with phase change. Among the modes of phase-change, boiling can effectively remove massive amounts of heat flux from the surface by employing structured or 3D microporous coatings to significantly enlarge the interfacial surface area for improved heat transfer rate as well as increase the number of potential sites for bubble nucleation and departure. The bubble dynamics during pool boiling are often considered to be essential in predicting heat transfer performance, causing it to be a field of significant interest. While prior investigations seek to modulate the bubble dynamics through either active (e.g., surfactants, electricity) or passive means (e.g., surface wettability, microstructures), the utilization of an ordered microporous architecture to instigate desirable liquid and vapor flow field has been limited. Here, we investigate the bubble dynamics using various spatial patterns of inverse opal channels to induce preferential heat and mass flow site in highly-interconnected microporous media. A fully-coated inverse opal surface demonstrates the intrinsic boiling effects of a uniform microporous coating, which exhibits 156% enhancement in heat transfer coefficient in comparison to the polished silicon surface. The boiling heat transfer performances of spatially-variant inverse opal channels significantly differ based on the pitch spacings between the microporous channels, which dictate the bubble coalescent behaviors and bubble departure characteristics. The elucidated boiling heat transfer performances will provide engineering guidance toward designing optimal two-phase thermal management devices.
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Computer vision-assisted investigation of boiling heat transfer on segmented nanowires with vertical wettability
The boiling efficacy is intrinsically tethered to trade-offs between the desire for bubble nucleation and necessity of vapor removal. The solution to these competing demands requires the separation of bubble activity and liquid delivery, often achieved through surface engineering. In this study, we independently engineer bubble nucleation and departure mechanisms through the design of heterogeneous and segmented nanowires with dual wettability with the aim of pushing the limit of structure-enhanced boiling heat transfer performances. The demonstration of separating liquid and vapor pathways outperforms state-of-the-art hierarchical nanowires, in particular, at low heat flux regimes while maintaining equal performances at high heat fluxes. A deep-learning based computer vision framework realized the autonomous curation and extraction of hidden big data along with digitalized bubbles. The combined efforts of materials design, deep learning techniques, and data-driven approach shed light on the mechanistic relationship between vapor/liquid pathways, bubble statistics, and phase change performance.
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- Award ID(s):
- 2045322
- PAR ID:
- 10415305
- Date Published:
- Journal Name:
- Nanoscale
- Volume:
- 14
- Issue:
- 36
- ISSN:
- 2040-3364
- Page Range / eLocation ID:
- 13078 to 13089
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1039/D2NR02447K
