clusters – TechConnect Briefs

Clusters of Iron Oxide Nanoparticles for Efficient Magnetic Resonance Imaging

Lai P.S., Lai S.M., Lai P.S., Lai S.M., National Chung Hsing University, TW

Recently, self-assembling clusters of metal nanoparticles have been extensively investigated in various fields. To prepare these clusters, various ionic surfactants, have been employed as stabilizers or emulsifiers to form water-dispersed spherical clusters. However, these ionic [...]

Vitamin E-assisted Superparamagnetic Iron Oxide Clusters Formation for Magnetic Resonance Imaging

Lai J-R, Lai P.S., Yen H-C, Hsu C.Y., Lai J-R, Lai P.S., National Chung Hsing University, TW

Magnetic Resonance Imaging (MRI) has been regard as a noninvasive powerful imaging tool that yields excellent soft-tissue contrast, has a high spatial resolution, and possesses tomographic capabilities. Among the contrast agents used for MRI, superparamagnetic [...]

Molecular approach for the synthesis of supported nanoparticles on active carbon using noble metal clusters

Willocq C., Vidick D., Hermans S., Delcorte A., Bertrand P., Dubois V., Devillers M., Université catholique de Louvain, BE

A molecular approach was envisaged for the preparation of nanoparticles supported on carbon. The support was first treated in order to build suitable anchors for organometallic compounds on the surface. Palladium clusters of various nuclearities [...]

Keywords: clusters

Clusters of Iron Oxide Nanoparticles for Efficient Magnetic Resonance Imaging

Vitamin E-assisted Superparamagnetic Iron Oxide Clusters Formation for Magnetic Resonance Imaging

Molecular approach for the synthesis of supported nanoparticles on active carbon using noble metal clusters

Scattering properties of dense clusters of nanoparticles

Gas Sensor Arrays by Supersonic Cluster Beam Deposition

Gas Sensor Arrays by Supersonic Cluster Beam Deposition

Self-Assembled Cluster Nanostructures and Nanodevices

Kinetic and Numerical Approaches to Nucleation and Growth During a First Order Phase Transition

Applications of the Structural Comparison Algorithm for Simulated Annealing Optimizations and Stochastic Simulations