首页|New Findings from Wayne State University in Machine Learning Provides New Insights (Unraveling the Effect of Single Atom Catalysts On the Charging Behavior of Nonaqueous Mg-co2 Batteries: a Combined Density Functional Theory and …)
New Findings from Wayne State University in Machine Learning Provides New Insights (Unraveling the Effect of Single Atom Catalysts On the Charging Behavior of Nonaqueous Mg-co2 Batteries: a Combined Density Functional Theory and …)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Fresh data on Machine Learning are presented in a new report. According to newsoriginating from Detroit, Michigan, by NewsRx correspondents, research stated, “This study integratesdensity functional theory (DFT) and machine learning (ML) methodologies to investigate the chargingperformance and catalyst design principles of porphyrin-supported single atom catalysts (SACs) based on3d and 4d transition metals (TMs) in the context of nonaqueous Mg-CO2 batteries. Specifically, we utilizeDFT calculations to elucidate the adsorption energies of the primary discharge product, MgCO3, on SACssupported on NxSy (where x = 4, 3, 2 and y = 0, 1, 2, respectively) moieties of porphyrin.”
DetroitMichiganUnited StatesNorth and Central AmericaBiological FactorsBiological PigmentsCyborgsEmerging TechnologiesMachine LearningPorphyrinsWayne State University
NETL
NSTL
