With the advancement of artificial intelligence (AI) applications, there is a growing demand for sophisticated and powerful chips. The adoption of these processors, along with increased power and bandwidth, highlights the necessity for efficient thermal management solutions. In this context, advanced two-phase thermal management systems have emerged as promising solutions. This study introduces a novel direct-to-chip evaporative cooling (DCEC) device that uses hollow micropillars integrated with a liquid delivery system to enable microscale evaporation of water and dielectric coolants in a fully actively pumped system. The device can operate indifferent evaporative regimes, characterized by a concave meniscus inside the micropillar's hole or a droplet confined at the inner or outer edge of the micropillar, depending on the heating power, thermophysical properties of the coolant, and operating pressure. To characterize the heat transfer performance of the DCEC, we conduct a comprehensive numerical analysis, varying different operating and design parameters for water, R-1336mzz(Z), and OpteonT 2P50. Our numerical results demonstrate device-level heat fluxes of 575 W/cm2, 413 W/cm2, and 365 W/cm2 for water, R-1336mzz(Z), and OpteonT 2P50, respectively. The corresponding heat transfer coefficients are 2.88 x 105 W/m2 K, 2.07 x 105 W/m2 K, and 1.83 x 105 W/m2 K for water, R-1336mzz(Z), and OpteonT 2P50, respectively. We also examine the performance of the device across various operating regimes. The results show that the device achieves 1.33x and 3.1x greater heat flux when a droplet is suspended at the outer edge of the hollow micropillar, compared to the stages with a concave or convex meniscus inside the micropillar's hole. We here conduct a detailed pressure analysis to understand the hydrodynamic characteristics of the device and determine the required inlet pressure for different coolants, operating regimes, and heat loads. These inlet pressure conditions can be integrated into the design of a feedback loop system to mitigate system failures caused by flooding or dryout.

Harnessing phase change materials (PCMs) for thermal management of power electronic devices shows potential to improve their reliability while decreasing the size, weight, power, and cost (SWaP-C) of the system due to the PCM's high latent heat during solid-to-liquid transition. However, despite its high latent heat of fusion, PCMs are limited by their low thermal conductivity and a narrow operational temperature range near their melting point. We here numerically investigate the thermal buffering capability of three distinct compositions of a novel three-component composite PCM consisting of organic microencapsulated paraffin and metallic fields metal with similar melting temperatures and copper cylindrical micropillars. These composites are evaluated under different single pulsewidth heating and cooling conditions and are benchmarked against a pure copper block. The results indicate that the composites generally surpass pure copper in minimizing peak device junction temperatures when the PCM undergoes phase change under single pulse loading, with the best-performing composite consistently achieving a lower junction temperature than the copper block. The best-performing composite can achieve up to 44% reduction in junction temperature swing compared to the copper reference when under a pulse train loading. These findings highlight the potential of the three-component composite system as an effective thermal buffer for electronics subjected to transient heat loads.

In this paper, we propose a set of guidelines to select a solver for the solution of nonlinear programming problems. We conduct a comparative analysis of the convergence performances of commonly used solvers for both unconstrained and constrained nonlinear programming problems. The comparison metrics involve accuracy, convergence rate, and computational time. MATLAB is chosen as the implementation platform due to its widespread adoption in academia and industry. Our study includes solvers which are either freely available or require a license, or are extensively documented in the literature. Moreover, we differentiate solvers if they allow the selection of different optimal search methods. We assess the performance of 24 algorithms on a set of 60 benchmark problems. We also evaluate the capability of each solver to tackle two large-scale UAV optimal path planning scenarios, specifically the 3D minimum time problem for UAV landing and the 3D minimum time problem for UAV formation flying. To enrich our analysis, we discuss the effects of each solver’s inner settings on accuracy, convergence rate, and computational time.

State-of-art power modules use fast-switching, high-voltage wide band gap MOSFETs, leading to die-level hotspots up to 1 kW cm -2 . Microscale evaporative cooling can dissipate large heat fluxes with low pumping power due to large latent heat of vaporization resulting from the phase change. We present a size, weight, and power (SWaP) optimized power electronic system with a novel direct-to-direct bonded copper (DBC) evaporative cooling module with hollow copper micropillars sustaining R-245fa microdroplets. Simulation results show a heat dissipation and heat transfer coefficient of 289 W cm -2 and 24.1 kW m -2 K -1 , respectively, with a required pumping power of 0.96 W, which is 15× lower than commercial cold plate technology. By removing the baseplate and bonding the evaporative module directly to the DBC, we reduce the junction-to-coolant thermal resistance and system weight by 60% and 88% respectively. A 3D manifold distributes the coolant to the evaporator, while ensuring a hermetic seal.

In this paper we propose a set of guidelines to select a solver for the solution of nonlinear programming problems. With this in mind, we present a comparison of the convergence performances of commonly used solvers for both unconstrained and constrained nonlinear programming problems. The comparison involves accuracy, convergence rate, and convergence speed. Because of its popularity among research teams in academia and industry, MATLAB is used as common implementation platform for the solvers. Our study includes solvers which are either freely available, or require a license, or are fully described in literature. In addition, we differentiate solvers if they allow the selection of different optimal search methods. As result, we examine the performances of 23 algorithms to solve 60 benchmark problems. To enrich our analysis, we will describe how, and to what extent, convergence speed and accuracy can be improved by changing the inner settings of each solver.

Evaporation of liquid is important in a diverse range of engineering applications, such as ink-jet printing, pesticide spraying, micro- and nanofabrication, thin-film coatings, biochemical assays, deposition of DNA/RNA microarrays, the manufacture of novel optical and electronic materials, and cooling microelectronics and power electronic devices. In particular, evaporation at the microscale has attracted increasing interest as an effective cooling strategy for overcoming the thermal challenges in high heat flux microelectronics devices. A large number of studies have demonstrated the prospect of evaporative heat transfer methods to tackle die-level hotspots reaching 1 kW/cm(2) on each high-power tier in a 3D microelectronics device. Furthermore, evaporation at the microscale (thin-film evaporation) can achieve higher heat removal than evaporation at macroscale. However, evaporation is a complicated process involving several physical transport phenomena, and their dominance can vary with variations in device dimensions and other system parameters. This article reviews the literature on the factors affecting microscale evaporation, which include the properties and temperature of the solid substrate, vapor transport in the gas domain, microconvection, and engineered surface features. Techniques to enhance evaporative heat transfer are highlighted. Extending the contact line region effectively enhances evaporative heat transfer, and this technique is employed in surface coatings or micro- and nanostructures, wicking structures, and micro- and nanoporous membranes. The evaporation rate can also be enhanced by manipulating the meniscus shape to provide an energy barrier at sharp edges of micro- and nanostructures. This review also summarizes the theoretical models for estimating evaporation rates, then discusses the physical transport processes associated with evaporation and their corresponding thermal resistances. Because non-invasive, high resolution temperature measurement and visualization are critical for implementing evaporative cooling in high heat flux applications, state-of-art techniques are also discussed. Laser-induced fluorescence techniques are judged the most advanced for temperature measurement, and particle image velocimetry (PIV) is the most advanced means of flow field visualization. This review identifies the most promising evaporative cooling techniques for next generation of ultra-high heat flux microelectronics applications. It also compares the performance of these cooling technologies in a regime plot, providing useful information for designing effective cooling solutions. We end by summarizing the current challenges and discussing the outlook for evaporative cooling technologies, then consider future research needs.

Two-phase liquid cooling on nanoengineered surfaces has shown great promise for tackling overheating in high performance microelectronics. At the nanoscale, phase change heat transfer can be affected substantially by the thermal resistance at the solid–liquid interface (also known as the Kapitza resistance). For example, surface modification by nanocoatings has been shown to efficiently enhance boiling heat transfer. However, there have been few studies on the effect of the Kapitza resistance on thin-film evaporative heat transfer. Here, the transport behavior of a liquid argon nanofilm evaporating on silicon (100) surfaces coated with different layers of graphene is analyzed using non-equilibrium molecular dynamics (MD) simulations. The results show that increasing layers of graphene coatings lead to a 136% increase in the Kapitza resistance and a 62% reduction in the evaporation rate. The large increase in Kapitza resistance is attributed to the strong repellence between graphene and argon molecules, manifested by a higher contact angle. These findings demonstrate the dominant role of interfacial thermal transport in the evaporation behavior of thin liquid films, and provide guidelines for selecting new materials when designing nanoengineered surfaces to realize improved evaporative cooling performance.

Over the last several decades, cooling technologies have been developed to address the growing thermal challenges associated with high-powered electronics. However, within the next several years, the heat generated by these devices is predicted to exceed 1 kW/cm(2), and traditional methods, such as air cooling, are limited in their capacities to dissipate such high heat fluxes. In contrast, two-phase cooling methods, such as microdroplet evaporation, are very promising due to the large latent heat of vaporization associated with the phase change process. Previous studies have shown that nonaxisymmetric droplets have different evaporation characteristics than spherical droplets. The solid-liquid and liquid-vapor interfacial areas, volume, contact angle, and thickness of a droplet confined atop a micropillar are the primary parameters that influence evaporative heat transport. These parameters have a strong influence on both the conduction and diffusion resistance during the evaporation process. For example, a droplet with a higher liquid-vapor interfacial area will favorably increase heat transfer. Increased droplet thickness, on the other hand, has a detrimental influence on the evaporation rate. The dimensions of these droplets will vary in response to changes in each of the aforementioned parameters. Lowering the droplet thickness can be achieved by decreasing the liquid volume while maintaining a constant solid-liquid area. However, if the solid-liquid area and volume vary simultaneously, the average droplet thickness may increase, decrease, or remain constant. Furthermore, changes in the shape of the droplet modify the local equilibrium contact angle of the droplet for different azimuthal angles. As a result, the optimal combination of these parameters must be identified to maximize the heat transfer performance of an evaporating microdroplet. These droplet parameters can be manipulated by selecting different micropillar cross sections. In this work, we develop a shape optimization tool using the particle swarm optimization algorithm to maximize evaporation from a droplet confined atop a micropillar. The tool is used to optimize the shape of a nonaxisymmetric droplet. Compared to droplets atop circular and regular equilateral triangular micropillar structures, we find that droplets confined on pseudo-triangular micropillar structures have 23.7% and 5.7% higher heat transfer coefficients, respectively. The results of this work will advance the design of microstructures that support droplets with maximum heat transfer performance.

A newly developed in situ non-intrusive optical (NIO) approach has been developed to survey various types of heliostat optical errors for a concentrating solar power (CSP) tower plant. To measure mirror surface slope error, facet canting error, and heliostat tracking error at a sub-milliradian accuracy, NIO requires several reflection images scanned over each individual heliostat. For a utility-scale plant that typically includes more than 10,000 heliostats, an unmanned aerial system (UAS) is crucial for efficient implementation of the NIO method. In this paper, we develop a flight path generation/optimization algorithm to plan more efficient UAS paths to collect NIO data over a utility-scale heliostat field. The algorithm considers NIO data requirements, all potential constraints, optimization within each subfield, and operational flexibility. Case studies are presented to illustrate the feasibility and robustness of the developed flight path algorithm. The path planning algorithm may also find applications elsewhere, such as drone-driven imaging under extreme conditions.

Seeking maximum evaporative heat transfer, here we report the numerical optimization of an array of non-axisymmetric droplet shapes confined on hollow micropillars. Different shapes of droplets exhibit very different interfacial mass transport features, based on their different perimeter-to-area ratios and meniscus curvatures. Most recently, we have shown that, compared to spherical droplets, microdroplets confined on triangular micropillars can have up to a 71% higher heat transfer coefficient at a substrate temperature of 98 degrees C. Furthermore, to maximize the heat transfer coefficient, we optimized the shape of a triangular micropillar. In this study, building on our previous work, we use particle swarm optimization to identify the arrangement of arrays of micropillars that maximizes non-axisymmetric droplet evaporation. The optimized array of non-axisymmetric droplets, confined on pseudo-triangles, has a 3.5% higher heat transfer coefficient than an unoptimized array of reference non-axisymmetric pseudo-triangles. Compared to circular droplets on an orthogonal arrangement of micropillars, it has a 14.1% higher heat transfer coefficient.

This paper focuses on applications of unmanned aerial vehicles (UAVs) for measuring optical error of heliostats in concentrating solar power (CSP) plants. In CSP, there is a need to measure solar-field optical errors, which is critical for future production improvement as well as for operations and maintenance of a heliostat field. This latter need is particularly challenging because of the large number of heliostats (over 10,000 for a utility-scale power plant) that individually track the sun in the field. To address this issue, a camera-equipped UAV, with an optimized drone flight path developed and uploaded to it, collects images of a precise reflection of the tower on each heliostat to evaluate optical error sources without interrupting plant operation. Generation of the drone path for capturing the reflected images is affected by a number technical and realistic constraints, which include the camera angle used to capture the image, the blocking of the camera view due to surrounding heliostats, the location of the camera in reference to the target heliostat, and the target heliostat position with reference to the tower. The effect of these constraints on calculating the camera position will be discussed in detail in this article. An effective drone-path algorithm is generated to fulfil the need of image collection under various constraints.