Transient Pool Research Articles

Experimental study on grid-patterned low thermal conductivity coatings for fast chill-down of flat plate in liquid nitrogen pool

This study investigates a fast chill-down technology utilizing grid-patterned low-thermal-conductivity (low-k) coatings. Experiments were conducted on the transient pool boiling of liquid nitrogen on stainless steel plates under various conditions: bare, partially coated, and fully coated surfaces with coating thicknesses ranging from 50 to 200 μm. Fully coated surfaces exhibited a 52–58 % shorter chill-down time owing to the rapid transition from film to transition boiling. However, these surfaces reduced thermal performance in the nucleate boiling regime owing to the added thermal resistance of the low-k coating. To address this, a partially coated surface with a grid-patterned design was proposed and examined for various pattern sizes of d = 2.5, 5, and 10 mm. The rapid regime transition was most effectively facilitated when the pattern size was comparable to the wavelength determined by the Taylor instability. In the nucleate boiling regime, thermal performance improved as the pattern size approached the capillary length. Consequently, the chill-down time for the partially coated surface with d = 2.5 mm was reduced by 79 %, owing to both the rapid regime transition and improved performance throughout the entire process. Finally, the grid-patterned coatings showed a twofold increase in coating effectiveness (∼4.8) compared to the fully coated surfaces (∼2.4). This study establishes a new design guideline for low-k coatings, optimizing cooling performance across all boiling regimes.

Sediment porewaters serve as a transient organic carbon pool at the land-ocean interface

The organic carbon (OC) cycle at the land-ocean interface is an important component of the global carbon budget, yet the processes that control the transfer, transformation, and burial of OC in these regions remain poorly understood. In this work, we examined sedimentary OC (SOC) in short core sediments, dissolved inorganic carbon (DIC), dissolved organic carbon (DOC), and chromophoric dissolved organic matter (CDOM), as well as other solutes in sediment porewaters of the Changjiang Estuary and adjacent East China Sea (ECS) shelf. The main goal of this work is to investigate the variation of the sources and composition of different forms of carbon in estuarine sediments associated with different sedimentary regimes, to further understand the role of sediment porewater in carbon sequestration at the land-ocean interface. Concentrations of Fe2+ and Mn2+ in porewaters of the muddy sediments are much higher than those in the sandy sediments, and SO42− decreases with depth in the deep sediment layer, indicating the degradation of SOC in mobile muds is mainly driven by suboxic and/or anoxic diagenetic processes (e.g., iron-manganese reduction). The accumulation of DIC in the muddy sediment is higher compared to the sandy sediment, indicating relatively complete SOC remineralization. The DOC in porewaters of the muddy areas is mainly composed of highly degraded and low molecular weight humic-like substances (C1), whereas in the sandy area, porewater DOC is mainly composed of less degraded and high molecular weight protein-like substances (C2 and C3). The average DOC stock (28.5 t/km2) in the upper 30 cm sediment porewaters is significantly higher than that of DIC (12.5 t/km2) in sandy area, but less in muddy areas (17.0 t/km2 of DOC vs. 25.4 t/km2 of DIC). The total DOC stock in sediment porewaters of the sandy area accounted for ∼61 % of DOC stock in water column of the ECS, indicating that the porewater is an important DOC pool in the ECS. However, this DOC pool is rather transient due to its high reactivity and mobility, especially in sandy area. Nevertheless, compared with other marine environments, the carbon stock of DOC (average of 43.8 t/km2) in porewaters of stable sedimentary environments is much higher than that of DIC (average of 21.7 t/km2). This work further supports the notion that sedimentary regime plays an important role in OC cycling at the land-ocean interface and highlights the significance of sediment porewaters as a vast carbon pool in marine ecosystems.

Effect of laser oscillation mode on LWAM deposition morphology and melting pool fluctuation

To investigate the impact of laser beam oscillation on melting pool fluctuation and deposition morphology during laser wire additive manufacturing, we observed transient melting pool fluctuations and measured the 3D deposition morphology. The study revealed that periodic beam oscillation enhances solution stirring, resulting in pronounced fluctuations in the melting pool and reduced roughness of the deposited surface. Furthermore, it was found that different laser oscillation modes resulted in different deposition morphologies. The shape of the melting pool is influenced by energy distribution characteristics, while the movement path of the spot determines this distribution. Moreover, the addition of beam oscillations effectively disperses the energy of the laser heat source, thereby mitigating the protrusion of the molten pool bottom.

Deep learning based reconstruction of transient 3D melt pool geometries in laser powder bed fusion from coaxial melt pool images

Melt pool monitoring can provide guidance for quality control in additive manufacturing. Existing techniques focus on 2D melt pool characteristics. In this work, we explore in situ prediction and control of 3D melt pool geometries within a simulation environment. To reconstruct the transient 3D melt pool geometry with only the 2D coaxial image as an input, we adopt a U-net model trained with a synthetic image dataset generated from simulations. The results show that the root-mean-square error of the pixel-wise predicted melt depth is 1.14μm, demonstrating the potential of the model in enabling precise laser path-wise 3D melt pool control.

Cytokinetic abscission requires actin-dependent microtubule severing

Cell division is completed by the abscission of the intercellular bridge connecting the daughter cells. Abscission requires the polymerization of an ESCRT-III cone close to the midbody to both recruit the microtubule severing enzyme spastin and scission the plasma membrane. Here, we found that the microtubule and the membrane cuts are two separate events that are regulated differently. Using HeLa cells, we uncovered that the F-actin disassembling protein Cofilin-1 controls the disappearance of a transient pool of branched F-actin which is precisely assembled at the tip of the ESCRT-III cone shortly before the microtubule cut. Functionally, Cofilin-1 and Arp2/3-mediated branched F-actin favor abscission by promoting local severing of the microtubules but do not participate later in the membrane scission event. Mechanistically, we propose that branched F-actin functions as a physical barrier that limits ESCRT-III cone elongation and thereby favors stable spastin recruitment. Our work thus reveals that F-actin controls the timely and local disassembly of microtubules required for cytokinetic abscission.

Coordination between circadian neural circuit and intracellular molecular clock ensures rhythmic activation of adult neural stem cells

The circadian clock throughout the day organizes the activity of neural stem cells (NSCs) in the dentate gyrus (DG) of adult hippocampus temporally. However, it is still unclear whether and how circadian signals from the niches contribute to daily rhythmic variation of NSC activation. Here, we show that norepinephrinergic (NEergic) projections from the locus coeruleus (LC), a brain arousal system, innervate into adult DG, where daily rhythmic release of norepinephrine (NE) from the LC NEergic neurons controlled circadian variation of NSC activation through β3-adrenoceptors. Disrupted circadian rhythmicity by acute sleep deprivation leads to transient NSC overactivation and NSC pool exhaustion over time, which is effectively ameliorated by the inhibition of the LC NEergic neuronal activity or β3-adrenoceptors-mediated signaling. Finally, we demonstrate that NE/β3-adrenoceptors-mediated signaling regulates NSC activation through molecular clock BMAL1. Therefore, our study unravels that adult NSCs precisely coordinate circadian neural circuit and intrinsic molecular circadian clock to adapt their cellular behavior across the day.

Effect of Combined Direct Current Electric Field and Pulsed Magnetic Field on the Transient Melt Pool in Laser Additive Manufacturing Process

Effect of Combined Direct Current Electric Field and Pulsed Magnetic Field on the Transient Melt Pool in Laser Additive Manufacturing Process

Development of a comprehensive model for predicting melt pool characteristics with dissimilar materials in selective laser melting processes

Selective laser melting (SLM) is a popular additive manufacturing (AM) technique for the fabrication of precise components. The success of SLM relies on accurate control of the melt pool, where the metal powder melts and solidifies. Fluid flow inside the melt pool is driven by forces like Marangoni force and recoil pressure. SLM process begins with the fabrication of support, which involves the process of joining dissimilar metals. A strong support-base substrate connection ensures the success of subsequent additive manufacturing. In this study a comprehensive model was developed to predict the dimensions and characteristics of the melt pool with a focus on the first layer of the SLM process. An initial numerical simulation was done to obtain transient melt pool temperature and velocity distribution during the SLM process. The results were then coupled with a theoretical analysis development of the proposed model. The effectiveness of the model was validated by experimental results and melt pool characteristics from previous publications. The model shows Root Mean Square Error (RMSE) of 0.53 and 0.49 for height-to-width ratio and normalized area, respectively. The Mean Absolute Percentage Error (MAPE) of normalized area is 15.7% for the majority of the data, which demonstrates a good accuracy of the model. In addition, the transition from conduction mode to keyhole mode can be identified with the model. This model can be used to rapidly and effectively predict the melt pool characteristics for SLM and other similar AM processes with a wide range of processing parameters.

Toward multiscale simulations for solidification microstructure and microsegregation for selective laser melting of nickel-based superalloys

In this study, we carried out multiscale simulations that integrate a macro-scale finite element method simulation for mass and heat transfer of the transient molten pool and a micro-scale quantitative phase-field model for dendritic growth and solute distribution based on selective laser melting (SLM) experiments. Macroscopic simulations reveal an approximately inverse coupling of solidification velocity Vs and thermal gradient G near the solid–liquid interface at the tail end of the molten pool. It was found that the maximum flow velocity of the Inconel 718 alloy melt in the molten pool exceeds 2×10−2 m/s and the maximum negative pressure reaches −5.28×10−4 Pa. Through quantitative phase-field simulations, the map about G/Vs for each solidification morphology was obtained, and it was found that solidification velocity dependent solute partition coefficients k(Vs) can strongly influence the estimated stability regions. The power law relationship of the primary dendritic arm spacing (PDAS) λ1 versus solidification velocity λ1∝Vsα agrees with the previous experimental results for lower G, and the exponent α decreases with increasing G. The PDAS λ1 versus cooling rate R following λ1∝R−0.512 is consistent with previous investigations. We found that λ1 is a nonlinear function with G−0.5Vs−0.25, i.e., λ1∝(G−0.5Vs−0.25)α, with α ranging from 0.887 to 2.466 for various G. Comparison of the predicted λ1 with Trivedi's model reveals that λ1 is still nonlinear with G−0.25Vs−0.25.

Memtrade: Marketplace for Disaggregated Memory Clouds

We present Memtrade, the first practical marketplace for disaggregated memory clouds. Clouds introduce a set of unique challenges for resource disaggregation across different tenants, including resource harvesting, isolation, and matching. Memtrade allows producer virtual machines (VMs) to lease both their unallocated memory and allocated-but-idle application memory to remote consumer VMs for a limited period of time. Memtrade does not require any modifications to host-level system software or support from the cloud provider. It harvests producer memory using an application-aware control loop to form a distributed transient remote memory pool with minimal performance impact; it employs a broker to match producers with consumers while satisfying performance constraints; and it exposes the matched memory to consumers through different abstractions. As a proof of concept, we propose two such memory access interfaces for Memtrade consumers -- a transient KV cache for specified applications and a swap interface that is application-transparent. Our evaluation using real-world cluster traces shows that Memtrade provides significant performance benefit for consumers (improving average read latency up to 2.8X) while preserving confidentiality and integrity, with little impact on producer applications (degrading performance by less than 2.1%).

Numerical determination of the required insulation thickness for steel protection against accidental cryogenic exposure

Cryogenic spill protection by insulation is widely used as one of the most effective risk-mitigation measures to protect steel structures against accidental cryogenic spills. This study proposed, for the first time, a numerical method for predicting the insulation thickness. The method is a combination of an optimization technique and the solution to the heat conduction problem. The major difficulty lies in the boundary condition at the boiling surface, which has not been clearly stated in the literature. To accurately determine the boundary condition, the effect of the insulation thickness on the transient pool boiling heat transfer of a cryogenic liquid on an insulated steel flat plate was first studied. It was determined that the boiling resistance generally decreased with increasing insulation thickness, which suggested that the liquid and boiling surfaces could be assumed to have perfect thermal contact. Subsequently, the assumption of perfect thermal contact was proven to be a valid boundary condition for sufficiently thick insulation layers. The developed method was verified and used to draw the correlations of the insulation thickness with the period of resistance and metal thickness. The findings of this study are expected to aid in the design of steel structure’s cryogenic spill protection systems.

Effect of Combined Dc Electric Field and Pulsed Magnetic Field on the Transient Melt Pool in Laser Additive Manufacturing Process

Effect of Combined Dc Electric Field and Pulsed Magnetic Field on the Transient Melt Pool in Laser Additive Manufacturing Process

A Deep-Learning-Based Surrogate Model for Thermal Signature Prediction in Laser Metal Deposition

Laser metal deposition (LMD) is an additive manufacturing method for metal parts by using focused thermal energy to fuse materials as they are deposited. During LMD, transient thermal signatures such as the in-situ thermal images of melt pool, contain rich information about process performance. Early prediction of such transient thermal signatures provides opportunities for process monitoring and defect prevention. While physics-based models of LMD have been conventionally used for thermal signature prediction, they have limitations and are computationally expensive for real-time prediction. A scalable, efficient data-science-based model is therefore needed. This paper develops a deep-learning-based surrogate model, called LMD-cGAN, to predict and emulate the transient thermal signatures in LMD. The model generates images for the thermal dynamics of melt pool conditionally on the deposition layer. It enables early prediction of future-layer thermal signatures for an in-process part based on its early-layer thermal signatures. To respect the physics in LMD, a physics-guided image selection (PGIS) mechanism is integrated with LMD-cGAN to calibrate the predictions against physical benchmarks of transient melt pool for the process. The effectiveness and efficiency of the proposed method are demonstrated in a case study on the LMD of Ti-4Al-6V thin-walled structures. Note to Practitioners—With online sensing, many LMD applications have real-time process data that convey valuable information about the process status and part quality. The proposed method leverages these data for thermal signature prediction. LMD-cGAN is a deep-learning-based surrogate model that learns the population profile of real thermal signatures and generates thermal signatures from there. The proposed PGIS mechanism in LMD-cGAN ensures the physical validity of these predictions by benchmarking them against physical insights about the process. LMD-cGAN can be applied to predict thermal signatures in future layers based on early-layer thermal signatures of an in-process part (an implicit assumption here is that the in-process part to be predicted for is the same type). LMD-cGAN can also be applied to emulate thermal signatures in specific layers. To generate thermal signatures for generic, non-defect parts, the training data should be selected with caution – the part where the data were collected should have no obvious defects, so the thermal signatures generated by LMD-cGAN show the regular thermal dynamics. Compared with pure physical models, the proposed method incorporates process uncertainties captured from the early-layer data, hence “on-the-fly” emulation of the melt pool, while characterizing the inherent relationship between the LMD process and thermal signatures.

A fast inversion approach for the identification of highly transient surface heat flux based on the generative adversarial network

The efficient identification of surface heat flux during highly transient pool boiling process is an essential task for engineering production and manufacture, which can be mathematically defined as nonlinear inverse heat transfer problems (IHTP) of Neumann boundary conditions. Conventional regularization-based inversion approaches for these types of problems are computationally expensive since packs of nonlinear partial differential equations (PDE) constrained optimization problems in complex computational domains need to be solved. In this paper, an operator-learning method is proposed for the efficient solution of complex three-dimensional (3D) transient nonlinear IHTP. FluxNet, a generated adversarial network composed of a discrete wavelet transform (DWT) layer, a “generator” and a “discriminator”, is constructed to significantly improve the computational efficiency, reaching sub-second for the first time. The DWT layer is capable of extracting detailed information of the temperature distribution while the “generator” approximates the inverse operator of the governing PDE system with its convolution kernels. A minimax optimization strategy is adopted through adversarial training between the “generator” and the “discriminator” to encourage deeper understanding of data distribution. Compared with other types of deep learning methods, the proposed method shows its superiority when dealing with highly transient experimental data and micro-nano porous structured geometry. Based on the developed sub-second light-weight numerical solver with operator learning, the development of advanced real-time soft sensor techniques for a class of 3D transient IHTP in practical engineering applications is possible.

Role of sea salt deposition on the advances in pool boiling heat transfer in nuclear reactors

The study of pool boiling performance of seawater and its advancements in the field of nuclear power safety is given significant importance in the Arabian Gulf (AG) region. The literature covers very limited data regarding the heat transfer capabilities of seawater collected from the AG region. This work investigates the transient pool boiling characteristics of natural seawater using cylindrical zirconium rods. Five successive quenching experiments were performed using distilled water and natural seawater coolants at saturated temperature and atmospheric pressure. Natural seawater was collected from the Doha Power Station, located along the AG coast of Kuwait. The chemical composition, pH, total dissolved solids (TDS), and electrical conductivity (EC) of the collected seawater were examined. By plotting the quenching and boiling curves, the cooling performance was evaluated based on minimum film boiling temperature ( T m i n ) and critical heat flux (CHF). The results revealed a remarkable boiling heat transfer enhancement, with T m i n and CHF increasing up to 25% and 93.6% in the fifth experiment, respectively. Subsequently, the surface morphology of the rods before and after quenching in each liquid coolant was characterized in detail. The surface characterization results justified the augmentation in heat transfer caused by quenching in seawater coolant. The boiling visualization images were presented at different time frames to visually support the enhancement mechanism. Surface wettability results were illustrated to understand the influence of surface porosity on the spreadability of liquid droplets. A novel hypothesis on the mechanism of sea salt deposition and its impact on destabilizing the vapor layer in the film boiling regime was proposed. The findings of this study are anticipated to be beneficial in improving the safety margins for in-vessel retention of the fuel rods in nuclear power plants. • Investigation of transient pool boiling in saturated distilled water and natural seawater coolants. • Enhanced heat transfer using seawater due to sea salt deposition. • Tmin and CHF enhancement with 25% and 93.6%, respectively. • Detailed surface characterization to detect the sea salt deposition on the heated rod. • Proposed hypothesis for sea salt deposition.

Mechanism Study of the Effect of Selective Laser Melting Energy Density on the Microstructure and Properties of Formed Renewable Porous Bone Scaffolds

To investigate the effect of selective laser melting (SLM) energy densities on the performance of porous 316L stainless steel bone scaffolds, the porous bone scaffolds with a face-centered cubic (FCC) structure were prepared using SLM technology, and a comprehensive study combining finite element analysis (FEA) and experiments was conducted on the SLM-formed 316L porous bone scaffolds. The mechanism of how various energy densities affect bone scaffolds were identified, and the effects of different energy densities on the primary dendrite spacing, grain orientation, residual stress, and transient melt pool variation in the scaffolds were discussed and summarized. It was found that the change in the energy densities had a more serious effect on the primary dendrite spacing, with the primary dendrite spacing increasing from 320 to 501 nm when the energy densities were increased from 41.7 to 111.1 J/mm3. In addition, analysis of the residual stress in the formed scaffolds showed that when an energy density of 41.7 J/mm3 was chosen for construction, the internal residual stress in the scaffolds reached a minimum value of 195.78 MPa, a reduction of approximately 36.6% compared to that of 111.1 J/mm3 for the porous scaffold. For the other properties of the scaffolds, the choice of low energy densities for the construction of FCC-structured porous bone scaffolds allowed for a maximum 10% reduction in the controlled deformation and a maximum 17% increase in the compressive properties. At the same time, it was found that the analysis results of the SLM-forming process by the FEA method were consistent with the experimental results. The main innovation of this paper is the proposal of the best construction parameters for porous bone scaffolds with an FCC structure formed by SLM and verification of the rationality of the best parameters through macro and micro experimental analysis, which guides the construction of porous bone scaffolds with an FCC structure formed by additive manufacturing. In addition, this study used finite element simulation to analyze the SLM process. This provides early prediction, optimization, and improvement for SLM-forming FCC porous bone scaffolds. The most important thing is that FEA can be used to more rapidly and economically analyze SLM. In the future, FEA can be used to provide a reference for porous bone scaffolds with different structures, different construction energy densities, different materials, and additive manufacturing in other industries.

Analytical modeling of temperature distribution in laser powder bed fusion with different scan strategies

This study proposes an analytical model to predict the transient temperature distribution and melt pool size in laser powder bed fusion (LPBF) process with different scan strategies. The scan strategies are divided into discontinuous scan path and continuous scan path. The moving Gaussian surface heat source solution and the instantaneous Gaussian surface heat source transient solution are applied for these two different scan strategies. The residual temperature linear superposition is adopted to consider the multi-track effect on the temperature distribution. The virtual negative power heat source method is utilized to consider the heat diffusion for the tracks that has been scanned of the build part. The image heat source method is used to consider the zero-flux boundary condition at the lateral surface of the build part. The proposed model is validated by the experimental data of the melt pool in single-track LPBF process. The analytical models of these two different scan strategies are verified by the comparison of the melt pool size. Based on the validated analytical model, it is extended for the multiple scan strategies combination processes. The temperature and melt pool predicted by the analytical model show good consistency with the FEM results. The analytical model method is much more efficient than FEM, which is about 120 times faster than FEM for the calculation of round-corner part. Due to the satisfied efficiency and accuracy in the prediction of melt pool size and the thermal history, the proposed analytical model has great potential application in optimization of the scan path planning and avoidance of the undesired residual temperature accumulation in the part.

Optimum coating thickness for the fastest chilldown of Teflon-coated stainless steel flat plate in liquid nitrogen pool

In this study, a novel model was developed to accurately determine the optimum thickness of a low-thermal-conductivity coating layer applied on a stainless steel flat plate resulting in the fastest chilldown of the plate in a cryogenic liquid pool. A low-thermal-conductivity layer coated on a metal surface is known to significantly reduce the cryogenic chilldown time of the metal by facilitating the early transition from film to nucleate boiling. However, there is still a lack of models to estimate the optimum coating thickness. An attempt has been made to address this issue. To do so, the authors first investigated the transient pool boiling of liquid nitrogen on Teflon-coated stainless-steel plates with various coating thicknesses ranging from 0 to 300 μm. Both the pool mass and plate temperature over time were measured and used to determine the heat flux into the liquid pool. A coating layer that results in a lower thermal resistance during film boiling would lead to a higher thermal resistance in nucleate boiling. As the thickness of the coating layer increases, the thermal resistance in film boiling decreases and the transition from film to nucleate boiling occurs earlier. The early transition of the boiling regimes was successfully explained by the assumption of intermittent liquid-solid contact during the film-boiling regime. The coating thickness in the range of 100–150 μm was observed to be the optimum thickness that resulted in both the smallest thermal resistance and earliest transition of boiling regimes. Subsequently, a new model to estimate the optimum coating thickness was derived based on experimental observations and the assumption of intermittent liquid-solid contact. The findings of this study are expected to be beneficial in enhancing the chilldown efficiency of cryogenic systems.

Temperature variation and mass transport simulations of invar alloy during continuous-wave laser melting deposition

Continuous-wave laser melting deposition (LMD) offers several advantages, such as higher cooling rate, finer microstructures and improved mechanical properties over traditional processing technology. The fluid flow in the molten pool affects the solute distribution and the microstructure morphology when invar alloy mould is repaired with laser melting deposition. However, the effects of laser on the molten pool motion, thermal field and microstructure of invar alloy are not distinct. In this work, a three-dimensional model utilizing the volume of fluid method was developed to simulate the transient molten pool motion, heat transfer and fluid flow for the laser melting deposition process. The interaction among powder, laser and molten pool in LMD process was comprehensively considered in the model. The laser melting deposition with Nano-WC powder particles as a dispersoid was investigated. The simulated molten pool geometry was compared with experimental results. Moreover, temperature variation, fluid flow and their influence on the microstructure were analyzed. It is concluded that a significant Marangoni flow is observed with the highest velocity in the middle of the molten pool but lower in the surface and bottom of the molten pool. The lower velocity of fluid flow results in an element accumulation in the bottom of the molten pool. This study provides a referenced value for revealing the flow mechanism of molten pool in the LMD process of invar alloy.

Rapid cooling performance of zirconium rods quenched in natural seawater

The viability of using natural seawater as an effective working coolant to ensure safe and efficient cooling mechanism is a significant study in the Arabian Gulf region. This study investigates transient pool boiling characteristics of natural seawater collected from different locations in the Arabian Gulf coast of Kuwait, compared to the baseline case of distilled water. Seawater samples are collected from prime locations (Shuwaikh, Al Zour, and Doha ports), which are highly capable of accommodating upcoming power plants and nuclear reactors. Extremely heated vertical zirconium rods are quenched in saturated pools at atmospheric pressure. A detailed study of the seawater samples is carried out through semi-quantitative calculation (SQX) results to evaluate the elemental composition, and water quality comparisons are made based on pH, total dissolved solids, and conductivity. The cooling performance is monitored by plotting the quenching and cooling rate curves, and evaluated based on the minimum film boiling temperature (Tmin) and maximum cooling rate. The results demonstrate an excellent improvement in Tmin and maximum cooling rate by employing natural seawater collected from Al Zour, which is located in the southern part of Kuwait. A minimum of 10% increase in Tmin is depicted by Al Zour seawater. The enhancement is attributed to the salt deposition activity caused by sudden evaporation of seawater on the surface. The salt deposits destabilize the vapor film to promote early vapor film breakage and act as an additional nucleation site to initiate early nucleate boiling, leading to an efficient cooling performance. Seawater collected from Shuwaikh port demonstrates a negative influence on the effective change in Tmin. A detailed examination is carried out on the surface of zirconium samples with the help of wavelength dispersive x-ray fluorescence analysis and SQX analysis, to identify and evaluate the prime elements responsible for the enhanced cooling performance. This study proves that even though the seawater is collected along the same coast, its characteristics differ when utilizing it in cooling systems.