首页|Reports Outline Machine Learning Research from CSIR - Central Mechanical Enginee ring Research Institute [Smartphone enabled machine learning approach assisted copper (Ⅱ) quantification and opto-electrochemical explosive recognition by …]
Reports Outline Machine Learning Research from CSIR - Central Mechanical Enginee ring Research Institute [Smartphone enabled machine learning approach assisted copper (Ⅱ) quantification and opto-electrochemical explosive recognition by …]
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 - New study results on artificial intell igence have been published. According to newsoriginating from Durgapur, India, by NewsRx correspondents, research stated, “An Aldazine-based optoelectrochemical sensor, BMH (1-(quinolin-4-ylmethylene)hydrazono)methyl)naphthalen-2-ol) has b eenintroduced herein for selective detection of aqueous copper (Cu2+) and 2, 4, 6-Trinitrophenol (TNP) atan ultra-low level detection limit (0.09 ppm for Cu2+ and 0.019 ppm for TNP).”
CSIR - Central Mechanical Engineering Re search InstituteDurgapurIndiaAsiaChemicalsCyborgsElectrochemicalsE merging TechnologiesMachine Learning
NETL
NSTL
