An electron paramagnetic resonance study of Pr0.6Ca0.4MnO3 across the charge-ordering transition

We report the first electron paramagnetic resonance studies of single crystals and powders of Pr0.6Ca0.4MnO3 in the 300-4.2 K range, covering the charge-ordering transition (Tco) at ~240 K and antiferromagnetic transition (TN) at ~170 K. The asymmetry parameter for the Dysonian single-crystal spectra shows an anomalous increase at Tco. Below Tco the g-value increases continuously, suggesting a gradual strengthening of the orbital ordering. The linewidth undergoes a sudden increase at Tco and continues to increase down to TN. The intensity increases as the temperature is decreased until Tco is reached, due to the renormalization of the magnetic susceptibility arising from the build-up of ferromagnetic correlations.

Effects of electron correlations in conjugated organic molecules and solids

The discrepancies between the non-interacting models and experimental results for conjugated systems is highlighted in this brief review. The interacting model hamiltonians correctly give the forbidden singlet state below the optical gap in polyenes and also explain both the nonvanishing optical gap in polyacetylenes and the vanishing optical gap in symmetric cyanine dyes. The negative spin densities in polyene radicals is also understood in terms of a correlated picture. The role of electron-electron interactions in other strongly correlated systems, such as polydiacetylene and mixed and segregated stack charge transfer solids, are also briefly discussed.

Nonlinear I-V characteristics of nanocrystalline SnO2

Current versus voltage characteristics (I-V) of nanocrystalline SnO2 materials have been investigated in air at room temperature. The samples were prepared by the inert gas condensation technique (IGCT) as well as by chemical methods. X-ray diffraction studies showed a tetragonal rutile structure for all the samples. Microstructural studies were performed with transmission electron microscopy. All the samples exhibited nonlinear I-V characteristics of the current-controlled negative resistance (CCNR) type. The results show that the threshold field (break down) voltage is higher for the samples prepared by the IGCT method than for those prepared by the chemical method due to the formation of a tin oxide layer over the crystalline tin. It is also found that the threshold field increases with the decrease in grain size.

Gas turbine diagnostics using a soft computing approach

A fuzzy system is developed using a linearized performance model of the gas turbine engine for performing gas turbine fault isolation from noisy measurements. By using a priori information about measurement uncertainties and through design variable linking, the design of the fuzzy system is posed as an optimization problem with low number of design variables which can be solved using the genetic algorithm in considerably low amount of computer time. The faults modeled are module faults in five modules: fan, low pressure compressor, high pressure compressor, high pressure turbine and low pressure turbine. The measurements used are deviations in exhaust gas temperature, low rotor speed, high rotor speed and fuel flow from a base line 'good engine'. The genetic fuzzy system (GFS) allows rapid development of the rule base if the fault signatures and measurement uncertainties change which happens for different engines and airlines. In addition, the genetic fuzzy system reduces the human effort needed in the trial and error process used to design the fuzzy system and makes the development of such a system easier and faster. A radial basis function neural network (RBFNN) is also used to preprocess the measurements before fault isolation. The RBFNN shows significant noise reduction and when combined with the GFS leads to a diagnostic system that is highly robust to the presence of noise in data. Showing the advantage of using a soft computing approach for gas turbine diagnostics.

A simple classical approach for the melting temperature of inert-gas nanoparticles

Like the metal and semiconductor nanoparticles, the melting temperature of free inert-gas nanoparticles decreases with decreasing size. The variation is linear with the inverse of the particle size for large nanoparticles and deviates from the linearity for small nanoparticles. The decrease in the melting temperature is slower for free nanoparticles with non-wetting surfaces, while the decrease is faster for nanoparticles with wetting surfaces. Though the depression of the melting temperature has been reported for inert-gas nanoparticles in porous glasses, superheating has also been observed when the nanoparticles are embedded in some matrices. By using a simple classical approach, the influence of size, geometry and the matrix on the melting temperature of nanoparticles is understood quantitatively and shown to be applicable for other materials. It is also shown that the classical approach can be applied to understand the size-dependent freezing temperature of nanoparticles.

Infrared Spectra of Dimethylquinolines in the Gas Phase: Experiment and Theory

Infrared spectra of atmospherically important dimethylquinolines (DMQs), namely 2,4-DMQ, 2,6-DMQ, 2,7-DMQ, and 2,8-DMQ in the gas phase at 80 degrees C were recorded using a long variable path-length cell. DFT calculations were carried out to assign the bands in the experimentally observed spectra at the B3LYP/6-31G* level of theory. The spectral assignments particularly for the C-H stretching modes could not be made unambiguously using calculated anharmonic or scaled harmonic frequencies. To resolve this problem, a scaled force field method of assignment was used. Assignment of fundamental modes was confirmed by potential energy distributions (PEDs) of the normal modes derived by the scaled force fields using a modified version of the UMAT program in the QCPE package. We demonstrate that for large molecules such as the DMQs, the scaling of the force field is more effective in arriving at the correct assignment of the fundamentals for a quantitative vibrational analysis. An error analysis of the mean deviation of the calculated harmonic, anharmonic, and force field fitted frequencies from the observed frequency provides strong evidence for the correctness of the assignment.

Contactless conductivity of nanoparticles from electron magnetic resonance lineshape analysis

A contactless method to determine the electrical conductivity of nanoparticles is presented. It is based on the lineshape analysis of electron magnetic resonance signals which are `Dysonian' for conducting samples of sizes larger than the skin depth. The method is validated bymeasurements on a bulk sample of La0.67Sr0.33MnO3 where it gives values close to those obtained from direct measurement of conductivity and is then used to determine the conductivity of nanoparticles of La0.67Sr0.33MnO3 dispersed in polyvinyl alcohol as a function of temperature. (C) 2010 Elsevier Ltd. All rights reserved.