The AM-4 Family of Layered Titanosilicates: Single-Crystal-to-Single-Crystal Transformation, Synthesis and Ionic Conductivity.

Flexible crystal() structures, which exhibit() single-crystal()-to-single-crystal() (SCSC) transformations(), are attracting attention() in many applied aspects: magnetic() switches, catalysis, ferroelectrics and sorption. Acid treatment() for titanosilicate material() AM-4 and natural() compounds with the same structures led to SCSC transformation() by loss() Na+, Li+ and Zn2+ cations with large structural() changes (20% of the unit()-cell() volume()). The conservation() of crystallinity through complex() transformation() is possible due() to the formation() of a strong hydrogen bonding() system(). The mechanism() of transformation() has been characterized using single-crystal() X-ray() diffraction analysis(), powder() diffraction, Rietvield refinement, Raman spectroscopy and electron microscopy. The low migration() energy() of cations in the considered materials() is confirmed using bond()-valence and density() functional() theory() calculations, and the ion conductivity of the AM-4 family's materials() has been experimentally verified.

Investigation of East Asian clouds with polarization light detection and ranging.

In this paper we present results of investigation of the main optical properties of East Asian clouds with a ground-based polarization lidar placed in Daejeon, Republic of Korea. Asian dust is located in elevated layers of the atmosphere in spring, travels long distances, and causes significant damage to ecology. We present backscattering matrices of clouds obtained from polarimetric remote measurements which comprise information on the scattering and absorption properties of cloud particles, their morphology, and spatial orientation. Theory of our applied lidar polarization experiment is presented in terms of the instrumental vectors of a transmitter and a receiver. Methods of solving linear and nonlinear systems of equations comprising echo signals are considered. Some numerical and measurement results are presented to illustrate the efficiency and versatility of the method of estimating the cloud parameters.

Raman and fluorescent scattering matrix of spherical microparticles.

In this paper, we have investigated the main properties of the Raman and fluorescent matrix of scattering by microspheres using the matrix scattering formalism. The coherent and incoherent inelastic scattering of incident light by a microsphere is described by the Stokes parameters. We demonstrate the main symmetry properties of the coherent and incoherent Raman and fluorescent scattering matrices. Numerical results are presented to illustrate the Raman scattering efficiency, cross-phase coefficient, and some other parameters of scattering by microspheres.

Investigating particle orientation in cirrus clouds by measuring backscattering phase matrices with lidar.

The relation between the orientation of particles in ice-crystal clouds and backscattering phase matrices (BSPMs) is considered. Parameters characterizing the predominant orientation of particles in the azimuthal direction and in the horizontal position are presented. The parameters are expressed through BSPM elements. A technique for measuring BSPM elements with lidar is described. Examples of some measurements are presented along with a statistical generalization of the results from more than 400 BSPM measurements. It is found that the orientation of coarse particles with large diameters in an azimuthal direction and in a horizontal position is more probable than in a random direction. However, the orientation of large particles is often masked by small particles that are not subject to the effect of orienting factors. Thus the mean parameters characterizing the state of orientation of particles in clouds as a whole correspond to weak orientation. It is supposed that the orientation of particles in the azimuthal direction is caused by wind-velocity pulsations.

Optimal method of linear regression in laser remote sensing.

Remote lidar sensing in the photon-counting mode is now the commonly accepted method for studying atmospheric processes in the lower and free atmosphere. However, when processing signals obtained from lidar measurements, investigators necessarily face the problem of achieving accuracy in reconstructing the atmospheric parameters despite the presence of inhomogeneous noise in the measured signals. We propose an optimal method of linear regression (OMLR) of signals. The accuracy of the the method for the reconstructed signal is estimated. An example of application of the OMLR to the reconstruction of the temperature profile from the data obtained with a Raman lidar at the Siberian Lidar Station of the Institute of Atmospheric Optics (Tomsk, Russia) is given. The proposed method is distinguished by simplicity of interpretation of the criteria used, based on careful adherence to statistical principles. This method is shown to be an efficient auxiliary tool for the processing of measured data.