首页|Findings from University of Miskolc in Nanoparticles Reported (Ma- chine Learning-assisted Characterization of Electroless Deposited Ni-p Particles On Nano/micro Sic Particles)
Findings from University of Miskolc in Nanoparticles Reported (Ma- chine Learning-assisted Characterization of Electroless Deposited Ni-p Particles On Nano/micro Sic Particles)
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NETL
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Elsevier
2024 FEB 22 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – A new study on Nanotechnology - Nanoparticles is now available. According to news reporting from Miskolc, Hungary, by NewsRx journalists, research stated, "In this experiment, Ni-P nanoparticles were deposited (ED) on SiC micro- and nanoparticles with different parameters. Our goal was to suc- cessfully prepare metal deposits and develop an effective method for comparing and evaluating the various procedures." Funders for this research include New National Excellence Program of the Ministry for Innovation, National Research, Development and Innovation Fund, Ministry of Innovation and Technology from the National Research, Development and Innovation Fund, National Research, Development & Innovation Office (NRDIO) - Hungary, Ministry of Innovation and Technology of Hungary from the National Research, Development and Innovation Fund, European Union (EU). The news correspondents obtained a quote from the research from the University of Miskolc, "During the experimental work, a three-step electroless Ni-P coating process was applied with different concentrations. The coated SiC particles were examined by scanning electron microscopy (SEM). The mass-specific surface area (SSA) of the coated SiC was measured by the Brunauer-Emmett-Teller (BET) method, while the volumetric-specific surface area (VSSA) was also calculated. The adhesion between the metal and the ceramic particle was analyzed by X-ray photoelectron spectroscopy (XPS)."
MiskolcHungaryEuropeCyborgsEmerging TechnologiesMachine LearningNanoparticlesNanotechnologyUniversity of Miskolc
NETL
NSTL
Elsevier
