Beijing University of Technology Reports Findings in Machine Learning (Synergist ic activation of peroxymonosulfate by 3D CoNiO2/Co core-shell structure biochar catalyst for sulfamethoxazole degradation)
Beijing University of Technology Reports Findings in Machine Learning (Synergist ic activation of peroxymonosulfate by 3D CoNiO2/Co core-shell structure biochar catalyst for sulfamethoxazole degradation)
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting from Beijing, People’s Republ ic of China, by NewsRx journalists, research stated, “In this study, a 3D CoNiO/ Co core-shell structure biochar catalyst derived from walnut shell was synthesiz ed by hydrothermal and ion etching methods. The prepared BC@CoNi-600 catalyst ex hibited exceptional peroxymonosulfate (PMS) activation.” The news correspondents obtained a quote from the research from the Beijing Univ ersity of Technology, “The system achieved 100 % degradation of su lfamethoxazole (SMX). The reactive oxygen species in the BC@CoNi-600/PMS system included SO, OH, and O. Density functional theory calculations explored the syne rgistic effects between nickel-cobalt bimetallic and carbon matrix during PMS ac tivation. The unique 3D core-shell structure of BC@CoNi-600 features an outer ni ckel-cobalt bimetallic layer with exceptional PMS adsorption capacity, while pro tecting the zero-valence Co of the inner layer from oxidation. Based on the expe rimental-data, machine learning modeling mechanism, and information theory, a no nlinear modeling method was proposed. This study utilizes a machine learning app roach to investigate the degradation of SMX in complex aquatic environments.”
Key words
Beijing/People’s Republic of China/Asi a/Aniline Compounds/Cyborgs/Emerging Technologies/Machine Learning/Organic Chemicals/Sulfamethoxazole/Sulfanilamides/Sulfones/Sulfur Compounds
NETL
NSTL