Characterization of spherical particles using high-order neural networks and scanning flow cytometry

We retrieve the radius R, real n and imaginary k parts of the refractive index of homogeneous spherical particles using angular distribution of the light-scattering intensity. To solve the inverse light-scattering problem we use a high-order neural-network technique. The effect of network parameters on optimization is examined. The technique is evaluated for noise-corrupted input data at 0.6 μm<R<10.6 μm, 1.02<n<1.38, and 0<k<0.03. The errors of retrieval for nonabsorbing particles do not exceed 0.05 μm for radius and 0.015 for refractive index. The experimental verification is fulfilled by experimental data retrieved by means of a scanning flow cytometer. The light-scattering profiles of polystyrene beads and spherized red blood cells are processed with the high-order neural networks and a non-linear regression at Mie theory. The parameters retrieved by the high-order neural networks correlate well with the parameters retrieved by the least-square method.     

Simulation of electron bunch generation by an ultrashort-pulse high-intensity laser-driven wakefield

Electron acceleration due to a wakefield excited by a ultrashort-pulse intense laser propagating through a finite-length underdense plasma layer is studied by two-dimensional particle-in-cell simulation. The electron energy distribution is analyzed for moderate to high intensity. For the electron density, where the pulse length is almost half of the plasma wavelength, dramatic changes of the density structure occur with cavity and bunch formation with an increase in the laser intensity, also leading to the appearance of a fast electron component well confined in phase space. The analytical form of the fast electron energy spectrum is also presented.     

Polymerization of butadiene on nanoparticles’ surfaces and formation of metal/polymer nanocomposites

In this paper, we demonstrate that laser vaporization of metals in the presence of a small concentration of butadiene vapor leads to the polymerization of butadiene and incorporation of the metal nanoparticles within the polymer matrix. The metal nanocomposites are characterized by electron microscopy, X-ray diffraction and EDX. The results from high pressure mass spectrometry indicate that multiple additions of butadiene molecules on the metal cations Fe⁺, Ni⁺ and Pt⁺, generated by laser vaporization, take place at room temperature thus providing an efficient means of initiating further polymerization reactions. The Pt⁺ reactions show extensive fragmentations and elimination steps generating hydrocarbon ions. The laser vaporization/polymerization method provides the ability to encapsulate several different metals or metal oxides which undoubtedly will play a significant role in tuning the various properties of the polymer composites.