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Daytime radiative cooling devices consisting of various materials are used to transmit and radiate heat energy from a target body outward through the atmosphere and into cold outer space, without using external energy and in the presence of sunlight. In this study, a daytime radiative cooling thin film structure is designed to achieve high emission...
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Radiative cooling is a passive cooling technology without any energy consumption, compared to conventional cooling technologies that require power sources and dump waste heat into the surroundings. For decades, many radiative cooling studies have been introduced but its applications are mostly restricted to nighttime use only. Recently, the emergence of photonic technologies to achieves daytime radiative cooling overcome the performance limitations. For example, broadband and selective emissions in mid-IR and high reflectance in the solar spectral range have already been demonstrated. This review article discusses the fundamentals of thermodynamic heat transfer that motivates radiative cooling. Several photonic structures such as multilayer, periodical, random; derived from nature, and associated design procedures were thoroughly discussed. Photonic integration with new functionality significantly enhances the efficiency of radiative cooling technologies such as colored, transparent, and switchable radiative cooling applications has been developed. The commercial applications such as reducing cooling loads in vehicles, increasing the power generation of solar cells, generating electricity, saving water, and personal thermal regulation are also summarized. Lastly, perspectives on radiative cooling and emerging issues with potential solution strategies are discussed.
In this work, a tool for estimating the contact angle from the molecular dynamics simulations is developed and presented. The tool (Achilles) can detect water droplet on hydrophobic and hydrophilic surfaces. The tool can reconstruct the droplets broken across the periodic boundaries. Further a neighbor density based accurate filter is used to find the droplet liquid vapor interface and a circle is fitted using it after removing the dense layers of water next to solid surface. This fitted circle is solved for contact angle and results are outputted in the form of graphical images and text. The entire content of the internal computations of the tool is broken down into 4 phases and users can monitor the outcomes at every phase through output images. The tool is tested using sample molecular dynamics results of water droplet on hydrophobic and hydrophilic surfaces. We believe this tool can be a good addition to the molecular dynamics simulation community who work on the interfacial physics, droplet evaporation, super hydrophobic surfaces, and wettability etc.
This investigation explores a novel path-planning and optimization strategy for multiple cooperative robotic agents, applied in a fully observable and dynamically changing obstacle field. Current dynamic path planning strategies employ static algorithms operating over incremental time-steps. We propose a cooperative multi-agent (CMA) based algorithm, based on natural flocking of animals, using vector operations. It is preferred over more common graph search algorithms like A* as it can be easily applied for dynamic environments. CMA algorithm executes obstacle avoidance using static potential fields around obstacles, that scale based on relative motion. Optimization strategies including interpolation and Bezier curves are applied to the algorithm. To validate effectiveness, CMA algorithm is compared with A* using static obstacles due to lack of equivalent algorithms for dynamic environments. CMA performed comparably to A* with difference ranging from -0.2% to 1.3%. CMA algorithm is applied experimentally to achieve comparable performance, with an error range of -0.5% to 5.2%. These errors are attributed to the limitations of the Kinect V1 sensor used for obstacle detection. The algorithm was finally implemented in a 3D simulated space, indicating that it is possible to apply with drones. This algorithm shows promise for application in warehouse and inventory automation, especially when the workspace is observable.
