首页|Reports from Kunming University Highlight Recent Findings in Machine Learning (P rediction of the Degradation of Organic Pollutants By Metal-activated Peracetic Acid Using Machine Learning)
Reports from Kunming University Highlight Recent Findings in Machine Learning (P rediction of the Degradation of Organic Pollutants By Metal-activated Peracetic Acid Using Machine Learning)
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Investigators discuss new findings in Machine Learning. According to news reporting out of Kunming, People's Republic of China, by NewsRx editors, research stated, "This study utilized machine learn ing (ML) to predict the kinetic constant (k) of pollutant degradation by using m etal-activated peracetic acid (PAA) and evaluated the performance of three diffe rent ML models. The Random Forest (RF) model obtained by parameter optimization had the best prediction performance." Financial support for this research came from Natural Science Foundation of Yunn an Province. Our news journalists obtained a quote from the research from Kunming University, "The study delved into the significance of various characteristics, and three c atalogues (reaction conditions, properties of metal and pollutants) were conside red. The results revealed that the density (rho) and polar surface area (PSA) of pollutants, pH, humic acid (HA), metal ionization energy and atomic radius of m etal (r) exhibited the most pronounced characteristic effects. Among them, rho, PSA and r positively affected k. While HA, pH and ionization energy had negative effects. Based on the results, the metals met ionization energy <710 KJ/mol and r> 0.165 nm (e.g., Ru, Mo, Ti and Tc) we re suggested to be the catalyst to activate PAA. And pH <8 was conducive to the reaction. Furthermore, the metal-activated PAA would be ef ficient to eliminate organic pollutants with the pollutant density > 1.6 g/cm3 and PSA > 180 (e.g., tetracycline, macrocycli c lipids and antibiotics)."
KunmingPeople's Republic of ChinaAsiaAcetic AcidsCyborgsEmerging TechnologiesMachine LearningPeracetic Aci dKunming University
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