Structural tuning of Montmorillonite clays by pillaring: Designing of shape selective solid acid catalysts and PANI - Montmorillonite nanocomposites

Green chemistry boots eco-friendly,natural clays as catalysts in the chemical as well as in the pharmaceutical industry.Industry demands thermal stability,mechanical strength etc for the catalyst and there the modification methods becomes important.Pillaring tunes clays as efficient catalytic templates for shape selective organic synthesis.Here pillared clays are used as promising alternatives for the environmentally hazardous homogeneous catalysts in some industrially important Friedel-Crafts alkylation reactions of arenes with lower alchohols and higher olefins.The layer structure is enhanced upon pillaring and allows the nanocomposite formation with polyaniline to develop today’s nanoscale diameter devices.Present work gives an entry of pillared clays to the world of conducting composite nanofibers.

Enhanced shape anisotropy and magneto-optical birefringence by high energy ball milling in NixFe1−xFe2O4 ferrofluids

Ferrofluids belonging to the series NixFe1 xFe2O4 were synthesised by two different procedures—one by standard co-precipitation techniques, the other by co-precipitation for synthesis of particles and dispersion aided by high-energy ball milling with a view to understand the effect of strain and size anisotropy on the magneto-optical properties of ferrofluids. The birefringence measurements were carried out using a standard ellipsometer. The birefringence signal obtained for chemically synthesised samples was satisfactorily fitted to the standard second Langevin function. The ball-milled ferrofluids showed a deviation and their birefringence was enhanced by an order. This large enhancement in the birefringence value cannot be attributed to the increase in grain size of the samples, considering that the grain sizes of sample synthesised by both modes are comparable; instead, it can be attributed to the lattice strain-induced shape anisotropy(oblation) arising from the high-energy ball-milling process. Thus magnetic-optical (MO) signals can be tuned by ball-milling process, which can find potential applications.

Vibrational behaviour of bcc Cu-based shape memory alloys close to the martensitic transition

Experimental data from ultrasonic and inelastic neutron scattering measurements are analyzed for different families of Cu-based shape-memory alloys. It is shown that the transition occurs at a value, independent of composition and alloy family, of the ratio between the elastic constants associated with the two shears necessary to accomplish the lattice distortion from the bcc to the close-packed structure. The zone boundary frequency of the TA2[110] branch evaluated at the transition point (TM), weakly depends, for each family, on composition. A linear relationship between this frequency and the inverse of the elastic constant C', both quantities evaluated at TM, has been found, in agreement with the prediction of a Landau model proposed for martensitic transformations.

On the stability of the bcc phase in Cu-Al-Mn shape memory alloys

Measurements of the entropy change at the martensitic transition of two composition-related sets of Cu-Al-Mn shape-memory alloys are reported. It is found that most of the entropy change has a vibrational origin, and depends only on the particular close-packed structure of the low-temperature phase. Using data from the literature for other Cu-based alloys, this result is shown to be general. In addition, it is shown that the martensitic structure changes from 18R to 2H when the ratio of conduction electrons per atom reaches the same value as the eutectoid point in the equilibrium phase diagram. This finding indicates that the structure of the metastable low-temperature phase is reminiscent of the equilibrium structure.

Elastic constants of Ni-Mn-Ga magnetic shape memory alloys

We have measured the adiabatic second order elastic constants of two Ni-Mn-Ga magnetic shape memory crystals with different martensitic transition temperatures, using ultrasonic methods. The temperature dependence of the elastic constants has been followed across the ferromagnetic transition and down to the martensitic transition temperature. Within experimental errors no noticeable change in any of the elastic constants has been observed at the Curie point. The temperature dependence of the shear elastic constant C' has been found to be very different for the two alloys. Such a different behavior is in agreement with recent theoretical predictions for systems undergoing multi-stage structural transitions.

Cooling and heating by adiabatic magnetization in Ni50Mn34In16 magnetic shape-memory alloy

We report on measurements of the adiabatic temperature change in the inverse magnetocaloric Ni50Mn34In16 alloy. It is shown that this alloy heats up with the application of a magnetic field around the Curie point due to the conventional magnetocaloric effect. In contrast, the inverse magnetocaloric effect associated with the martensitic transition results in the unusual decrease of temperature by adiabatic magnetization. We also provide magnetization and specific heat data which enable to compare the measured temperature changes to the values indirectly computed from thermodynamic relationships. Good agreement is obtained for the conventional effect at the second-order paramagnetic-ferromagnetic phase transition. However, at the first-order structural transition the measured values at high fields are lower than the computed ones. Irreversible thermodynamics arguments are given to show that such a discrepancy is due to the irreversibility of the first-order martensitic transition.

Automatic Image Annotation Using SURF Descriptors

In recent years there is an apparent shift in research from content based image retrieval (CBIR) to automatic image annotation in order to bridge the gap between low level features and high level semantics of images. Automatic Image Annotation (AIA) techniques facilitate extraction of high level semantic concepts from images by machine learning techniques. Many AIA techniques use feature analysis as the first step to identify the objects in the image. However, the high dimensional image features make the performance of the system worse. This paper describes and evaluates an automatic image annotation framework which uses SURF descriptors to select right number of features and right features for annotation. The proposed framework uses a hybrid approach in which k-means clustering is used in the training phase and fuzzy K-NN classification in the annotation phase. The performance of the system is evaluated using standard metrics.

The Effect of SIFT Features as Content Descriptors in the Context of Automatic Writer Identification in Malayalam Language

The span of writer identification extends to broad domes like digital rights administration, forensic expert decisionmaking systems, and document analysis systems and so on. As the success rate of a writer identification scheme is highly dependent on the features extracted from the documents, the phase of feature extraction and therefore selection is highly significant for writer identification schemes. In this paper, the writer identification in Malayalam language is sought for by utilizing feature extraction technique such as Scale Invariant Features Transform (SIFT).The schemes are tested on a test bed of 280 writers and performance evaluated