Siavash Khodakarami

Increasing global energy demand is driving the need for efficient heat dissipation techniques, especially for high heat flux applications such as electronics thermal management. Boiling heat transfer has emerged as a promising heat acquisition solution due to its ability to utilize the latent heat of vaporization during liquid-to-vapor phase transformation. However, the thermal performance of conventional plain or finned surfaces can be limited due to low nucleation site density and poor fluid wickability, which are crucial for efficient boiling heat transfer and high critical heat flux (CHF). Unlike their macroscale (> 200 μm length scales) fin counterparts, micro- and nanostructured surfaces, herein termed structured surfaces, have become a promising alternative to overcome these barriers. The selection of appropriate structured surface fabrication techniques is essential to achieve the desired surface topography, cavity size range, and enhanced boiling performance. In this review, we provide a comprehensive analysis of structured surface fabrication strategies for boiling heat transfer enhancement. We broadly classify the methods into two groups: subtractive methods such as etching and laser ablation, and additive methods such as electrochemical deposition, sintering, and coating. The effect of manufacturing process parameters on surface characteristics is discussed in detail for each fabrication technique. We present how these engineered surfaces affect boiling performance and discuss the underlying mechanisms of heat transfer coefficient (HTC) and CHF enhancement in pool and flow boiling. A comparative evaluation of the fabrication methods is provided in terms of their advantages, limitations, and effectiveness in enhancing HTC and CHF. The key challenges associated with translating lab-scale to real-life boiling applications such as scalability, long-term durability and environmental impact of the fabrication methods are critically analyzed. Finally, we propose future directions for further advancement in the field. This review aims to serve as a guideline for structured surface design for high performance and energy efficient thermal systems.

Increasing global energy demand is driving the need for efficient heat dissipation techniques, especially for high heat flux applications such as electronics thermal management. Boiling heat transfer has emerged as a promising heat acquisition solution due to its ability to utilize the latent heat of vaporization during liquid-to-vapor phase transformation. However, the thermal performance of conventional plain or finned surfaces can be limited due to low nucleation site density and poor fluid wickability, which are crucial for efficient boiling heat transfer and high critical heat flux (CHF). Unlike their macroscale (> 200 µm length scales) fin counterparts, micro- and nanostructured surfaces, herein termed structured surfaces, have become a promising alternative to overcome these barriers. The selection of appropriate structured surface fabrication techniques is essential to achieve the desired surface topography, cavity size range, and enhanced boiling performance. In this review, we provide a comprehensive analysis of structured surface fabrication strategies for boiling heat transfer enhancement. We broadly classify the methods into two groups: subtractive methods such as etching and laser ablation, and additive methods such as electrochemical deposition, sintering, and coating. The effect of manufacturing process parameters on surface characteristics is discussed in detail for each fabrication technique. We present how these engineered surfaces affect boiling performance and discuss the underlying mechanisms of heat transfer coefficient (HTC) and CHF enhancement in pool and flow boiling. A comparative evaluation of the fabrication methods is provided in terms of their advantages, limitations, and effectiveness in enhancing HTC and CHF. The key challenges associated with translating lab-scale to real-life boiling applications such as scalability, long-term durability and environmental impact of the fabrication methods are critically analyzed. Finally, we propose future directions for further advancement in the field. This review aims to serve as a guideline for structured surface design for high performance and energy efficient thermal systems.

Flow condensation is a cornerstone of refrigeration systems, heat pumps, and electronics cooling technologies, and its enhancement is critical for improving efficiency and reducing heat exchanger size. Numerous enhancement strategies have been proposed for flow condensation, including micro- and nanostructured surfaces which have been investigated for their potential to promote condensate film redistribution. In this study, the coupled effects of tube diameter, refrigerant properties, and surface structuring on flow condensation performance are systematically investigated. Experiments are conducted in tubes with internal diameters ranging from 1.5 mm to 4.7 mm using two low-GWP refrigerants, R515B and R1233zd(E), on etched aluminum and etched copper surfaces. A counter-flow tube-in-tube facility is employed, with particular attention to the experimental challenges associated with small diameter flow condensation measurements, including flow oscillations, streamwise saturation temperature gradients, and uncertainty control. The results show that heat transfer enhancement is achieved only within a narrow vapor quality range governed by the interaction between condensate film thickness and surface feature size. Averaged over the highest vapor qualities (0.7-1), enhancements of up to 45% are obtained on etched aluminum tubes with a diameter of 2.4 mm, while etched copper tubes exhibit enhancements up to 55% with a diameter of 3.1 mm. Film thickness and flow regime analyses indicate that surface structures become flooded at high vapor qualities (x > 0.8), suppressing capillary-driven film redistribution and eliminating enhancement occurring at lower vapor qualities. These findings establish critical thresholds for effective condensation enhancement in structured tubes.

Knowledge of condensate shedding droplet dynamics provides important information for the characterization of two-phase heat and mass transfer phenomena. Detecting and segmenting the droplets during shedding requires considerable time and effort if performed manually. Here, we developed a self-supervised deep learning model for segmenting shedding droplets from a variety of dropwise and filmwise condensing surfaces. The model eliminates the need for image annotation by humans in the training step and, therefore, reduces labor significantly. The trained model achieved an average accuracy greater than 0.9 on a new unseen test dataset. After extracting the shedding droplet size and speed, we developed a data-driven model for shedding droplet dynamics based on condensation heat flux and surface properties such as wettability and tube diameter. Our results demonstrate that condensate droplet departure size is both heat flux and tube size dependent and follows different trends based on the condensation mode. The results of this work provide an annotation-free methodology for falling droplet segmentation as well as a statistical understanding of droplet dynamics during condensation.

Quantifying the processes involved in liquid-vapor phase-change phenomena, while dauntingly challenging, is central in designing energy conversion and thermal management systems. Recent technological advances in the deep learning and computer vision field offer the potential for quantifying such complex two-phase nucleation processes at unprecedented levels. By leveraging these new technologies, a multiple object tracking framework called “Vision Inspired Online Nuclei Tracker (VISION-iT)” has been proposed to extract large-scale, rich physical data residing within boiling and condensation videos. However, extracting high-quality features which can be integrated with domain knowledge requires detailed discussions that may be field- or case-specific problems. In this regard, we present a demonstration and discussion of the detailed construction, algorithms, and optimization of individual modules to enable adaptation of the framework to custom datasets. The concepts and procedures outlined in this study are transferable and can benefit broader audiences dealing with similar problems.

This review highlights recent developments in improving thermal-hydraulic performance through two phase heat transfer facilitated by microstructured and nanostructured surfaces.