首页|New Findings from University of Hull in the Area of Machine Learning Reported (O perando Study of the Dynamic Evolution of Multiple Fe-rich Intermetallics of an Al Recycled Alloy In Solidification By Synchrotron X-ray and Machine Learning)
New Findings from University of Hull in the Area of Machine Learning Reported (O perando Study of the Dynamic Evolution of Multiple Fe-rich Intermetallics of an Al Recycled Alloy In Solidification By Synchrotron X-ray and Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Data detailed on Machine Learning have been prese nted. According to news reporting out of Kingston upon Hull, United Kingdom, by NewsRx editors, research stated, “Using synchrotron X-ray diffraction, tomograph y and machine-learning enabled phase segmentation strategy, we have studied unde r operando conditions the nucleation, co-growth and dynamic interplays among the dendritic and multiple intermetallic phases of a typical recycled Al alloy (Al5 Cu1.5Fe1Si, wt.%) in solidification with and without ultrasound. Th e research has revealed and elucidated the underlying mechanisms that drive the formation of the very complex and convoluted Fe-rich phases with rhombic dodecah edron and 3D skeleton networks (the so-called Chinese-script type morphology).” Funders for this research include Engineering & Physical Sciences Research Council (EPSRC), National Natural Science Foundation of China (NSFC), Y unnan International Cooperation Base in Cloud Computation for Non-ferrous Metal Processing, University of Hull, China Scholarship Council.
Kingston upon HullUnited KingdomEuro peCyborgsEmerging TechnologiesMachine LearningPhysicsSynchrotronsUni versity of Hull
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