首页|Data on Machine Learning Reported by B. Moses Abraham and Colleagues [Machine Learning-Enabled Nanoscale Phase Prediction in Engineered Poly(Vinyliden e Fluoride)]
Data on Machine Learning Reported by B. Moses Abraham and Colleagues [Machine Learning-Enabled Nanoscale Phase Prediction in Engineered Poly(Vinyliden e Fluoride)]
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is the subject of a report. According to news reporting from Barcelona, Spain, by New sRx journalists, research stated, “Engineered poly(vinylidene fluoride) (PVDF) with its diverse crystalline phases plays a crucial role in determining the perfo rmance of devices in piezo-, pyro-, ferro- and tribo-electric applications, indi cating the importance of distinct phasedetection in defining the structure-prop erty relation. However, traditional characterization techniques struggle to effe ctively distinguish these phases, thereby failing to offer complete information. ” Financial supporters for this research include Mission on Nano Science and Technology, University Grants Commission - South Eastern Regional Office.
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