Lycurgus Cup: inverse problem using photographs for characterization of matter

Photographs of the Lycurgus Cup with a source light inside and outside exhibit purple and green colors, respectively (dichroism). A model relying on the scattering of light to colors in the photographs is proposed and used within an inverse problem algorithm, to deduce radius and composition of metallic particles, and the refractive index of the surrounding glass medium. The inverse problem algorithm is based on a hybridization of particle swarm optimization and of the simulated annealing methods. The results are compared to experimental measurements on a small sample of glass. The linear laws that are deduced from sets of possible parameters producing the same color in the photographs help simplify the understanding of phenomena. The proportion of silver to gold in nanoparticles is found to be in agreement, but a large proportion of copper is also found. The retrieved refractive index of the surrounding glass is close to 2.

Numerical retrieval of thin aluminium layer properties from SPR experimental data

The inverse problem for Surface Plasmon Resonance measurements [1] on a thin layer of aluminium in the Kretschmann configuration, is solved with a Particle Swarm Optimization method. The optical indexes as well as the geometrical parameters are found for the best fit of the experimental reflection coefficient in s and p polarization, for four samples, under three theoretical hypothesis on materials: the metal layer is pure, melted with its oxyde, or coated with oxyde. The influence of the thickness of the metal layer on its optical properties is then investigated.

Quantitative comparison of optimized nanorods, nanoshells and hollow nanospheres for photothermal therapy

The purpose of this study is to get more efficient gold nanoparticles, for necrosis of cancer cells, in photothermal therapy. Therefore a numerical maximization of the absorption efficiency of a set of nanoparticles (nanorod, nanoshell and hollow nanosphere) is proposed, assuming that all the absorbed light is converted to heat. Two therapeutic cases (shallow and deep cancer) are considered. The numerical tools used in this study are the full Mie theory, the discrete dipole approximation and the particle swarm optimization. The optimization leads to an improved efficiency of the nanoparticles compared with previous studies. For the shallow cancer therapy, the hollow nanosphere seems to be more efficient than the other nanoparticles, whereas the hollow nanosphere and nanorod, offer comparable absorption efficiencies, for deep cancer therapy. Finally, a study of tolerance for the size parameters to guarantee an absorption efficiency threshold is included.