首页|Findings from Delft University of Technology Update Knowledge of Machine Learnin g (Probing Machine Learning Models Based On High Throughput Experimentation Data for the Discovery of Asymmetric Hydrogenation Catalysts)
Findings from Delft University of Technology Update Knowledge of Machine Learnin g (Probing Machine Learning Models Based On High Throughput Experimentation Data for the Discovery of Asymmetric Hydrogenation Catalysts)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Machine Learning is th e subject of a report. According to newsreporting from Delft, Netherlands, by N ewsRx journalists, research stated, “Enantioselective hydrogenationof olefins b y Rh-based chiral catalysts has been extensively studied for more than 50 years. Naively, onewould expect that everything about this transformation is known an d that selecting a catalyst that inducesthe desired reactivity or selectivity i s a trivial task.”
DelftNetherlandsEuropeChemistryC yborgsEmerging TechnologiesMachine LearningDelft University of Technology
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