首页|New Machine Learning Findings Reported from School of Electrical Engineering (A Machine Learning Based Electronic Property Predictor of Cu 2 Sns 3 Thin Film Syn thesized By Ultrasonic Spray Pyrolysis)
New Machine Learning Findings Reported from School of Electrical Engineering (A Machine Learning Based Electronic Property Predictor of Cu 2 Sns 3 Thin Film Syn thesized By Ultrasonic Spray Pyrolysis)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ma chine Learning. According to news reporting originating in Chennai, India, by NewsRx journalists, research stated, “Copper tin sulphide (CTS) is an important material used as an absorber layer for low cost solar cells. Variation of the elem ental constituents of CTS and the substrate temperature cause a significant alte ration in its electronic property, which may cause unpredictable change in the device efficiency.”
ChennaiIndiaAsiaCyborgsEmerging TechnologiesMachine LearningSchool of Electrical Engineering
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