首页|Northwest University Reports Findings in Machine Learning (Comparing the Catalytic Effect of Metals for Energetic Materials: Machine Learning Prediction of Adsorption Energies on Metals)
Northwest University Reports Findings in Machine Learning (Comparing the Catalytic Effect of Metals for Energetic Materials: Machine Learning Prediction of Adsorption Energies on Metals)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Machine Learning is the subject of a report. According to news reportingfrom Xi’an, People’s Republic of China, by NewsRx journalists, research stated, “Energetic materials(Ems) and metals are the important components of solid propellants, and a strong catalysis of metals onEms could further enhance the combustion performance of solid propellants. Accordingly, the study onthe adsorption of Ems such as octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX), hexahydro-1,3,5- trinitro-1,3,5-triazine (RDX), and ammonium dinitramide (AND) on metals (Ti, Zr, Fe, Ni, Cu, and Al)was carried out by density functional theory (DFT) to reveal the catalytic effect of metals.”
Xi’anPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine Learning