Abstract
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 out of Shaanxi, People's Repu blic of China, by NewsRx editors, research stated, "Oxygen reduction reaction (O RR) and oxygen evolution reaction (OER) are essential for the development of exc ellent bifunctional electrocatalysts, which are key functions in clean energy pr oduction. The emphasis of this study lies in the rapid design and investigation of 153 MN-graphene (Gra)/ MXene (MNO) electrocatalysts for ORR/OER catalytic act ivity using machine learning (ML) and density functional theory (DFT)." Our news journalists obtained a quote from the research from the Shaanxi Univers ity of Technology, "The DFT results indicated that CoN-Gra/TiNO had both good OR R (0.37 V) and OER (0.30 V) overpotentials, while TiN-Gra/MNO and MN-Gra/CrNO ha d high overpotentials. Our research further indicated orbital spin polarization and d-band centers far from the Fermi energy level, affecting the adsorption ene rgy of oxygen-containing intermediates and thus reducing the catalytic activity. The ML results showed that the gradient boosting regression (GBR) model success fully predicted the overpotentials of the monofunctional catalysts RhN-Gra/TiNO (ORR, 0.39 V) and RuN-Gra/WNO (OER, 0.45 V) as well as the overpotentials of the bifunctional catalyst RuN-Gra/WNO (ORR, 0.39 V; OER, 0.45 V)."
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