PCA and LDA Based Neural Networks for Human Face Recognition

Abstract

The equilibrium behavior of ellipsoidal Janus nanoparticles at water-oil interfaces was investigated using dissipative particle dynamics simulations. It was found that the orientation of the nanoparticles with respect to the interface depends on nanoparticle aspect ratio, on the amount of polar vs nonpolar surface groups, and on the interactions between the nanoparticles surface groups and aqueous and nonaqueous solvents. The changes in nanoparticle orientation are not always monotonic, probably because of a competition between different driving forces. For nanoparticles of high aspect ratio, steric effects seem to cause an isotropic-to-nematic phase transition as the surface coverage increases. It was observed that at a sufficiently high surface coverage the nanoparticles are most effective at reducing the interfacial tension when they lay with their longer axis parallel to the interface. The simulation results presented could be useful for the design of Pickering emulsions.