首页|ITMO University Details Findings in Photocatalytics (Optimization of G-c3n4 Synt hesis Parameters Based On Machine Learning To Predict the Efficiency of Photocat alytic Hydrogen Production)
ITMO University Details Findings in Photocatalytics (Optimization of G-c3n4 Synt hesis Parameters Based On Machine Learning To Predict the Efficiency of Photocat alytic Hydrogen Production)
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 ; Investigators publish new report on Nanotechnolog y - Photocatalytics. According to news reportingout of St. Petersburg, Russia, by NewsRx editors, research stated, “This study demonstrated a machinelearning approach to predict the photocatalytic properties of graphitic carbon nitride (g -C3N4) 3 N 4 )depending on its synthesis parameters to enhance photocatalytic h ydrogen production. In connection withthe task, a database was experimentally f ormed to prepare g-C3N4 3 N 4 samples by heat treatment ofnitrogen-containing p recursors in air at a temperature of 450-600 degrees C with varying time and heating rates of the synthesis.”
St. PetersburgRussiaCyborgsElement sEmerging TechnologiesGasesHydrogenInorganic ChemicalsMachine LearningNanotechnologyPhotocatalystPhotocatalyticsITMO University
NETL
NSTL
