首页|Studies from Purdue University in the Area of Machine Learning Reported (Machine Learning-based Design Optimization of Aperiodic Multilayer Coatings for Enhance d Solar Reflection)
Studies from Purdue University in the Area of Machine Learning Reported (Machine Learning-based Design Optimization of Aperiodic Multilayer Coatings for Enhance d Solar Reflection)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing have been published. According to news reporting originating from West Lafay ette, Indiana, by NewsRx correspondents, research stated, “Multilayered coatings are promising and successful for applications in semiconductors, optical mirror s, and energy harvesting technologies. Amongst these, optical mirrors are essent ial for passive radiative cooling.” Financial support for this research came from National Science Foundation (NSF). Our news editors obtained a quote from the research from Purdue University, “Bui lding upon the multilayer radiative cooling systems observed in snails and drawi ng from previous research, this study showcases the efficacy of machine learning algorithms in optimizing and gaining insights into multilayer structures. Due t o the constraint of low sky window emissivity in biologically found calcite shel ls, focusing on solar reflectance becomes crucial to maximize the biological phe nomenon found in snails. The manual search of the periodic multilayer design spa ce for calcite with air gaps points to the maximum solar reflectance of -89% at 170 nm layer thickness for 20 mu m coating. To unlock the full potential of t hese multilayers, we then employ machine learning -based evolutionary optimizati on method - a genetic algorithm. The optimized aperiodic coating shows a signifi cant enhancement of solar reflectance to -99.8% for a 20 mu m coat ing. Interestingly, the same average layer thickness of 170 nm provides maximum solar reflectance in 20 mu m periodic and aperiodic calcite multilayer. Investig ation of the spectral reflectance shows that layer thickness is crucial in tunin g the solar reflectance. For small coatings, wavelengths with higher solar inten sity are prioritized. Increasing the coating thickness allows inclusion of thick er layers to reflect longer wavelengths, leading to increasing trend of average calcite layer thickness. Further work exploring radiative cooling materials show s that calcite and barium sulfate reflect sunlight significantly better than sil icon dioxide due to their refractive index contrast.”
West LafayetteIndianaUnited StatesNorth and Central AmericaCyborgsEmerging TechnologiesMachine LearningPur due University
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