PET-SWNT nanocomposites through ultrasound assisted dissolution-evaporation

Poly(ethylene terephthalate) (PET) based nanocomposites have been prepared with single walled carbon nanotubes (SWNTs) through an ultrasound assisted dissolution-evaporation method. Differential scanning calorimetry studies showed that SWNTs nucleate crystallization in PET at weight fractions as low as 0.3%, as the nanocomposite melt crystallized during cooling at temperature 24 °C higher than neat PET of identical molecular weight. Isothermal crystallization studies also revealed that SWNTs significantly accelerate the crystallization process. Mechanical properties of the PETSWNT nanocomposites improved as compared to neat PET indicating the effective reinforcement provided by nanotubes in the polymer matrix. Electrical conductivity measurements on the nanocomposite films showed that SWNTs at concentrations exceeding 1 wt% in the PET matrix result in electrical percolation. Comparison of crystallization, conductivity and transmission electron microscopy studies revealed that ultrasound assisted dissolution-evaporation method enables more effective dispersion of SWNTs in the PET matrix as compared to the melt compounding method

Liquid phase benzoylation of arenes over iron promoted sulphated zirconia

The present work undertakes the preparation and physico-chemical characterisation of iron promoted sulphated zirconia (SZ) with different amounts of iron loading and their application to Friedel-Crafts benzoylation of benzene, toluene and xylene under different experimental conditions, XRD and laser Raman techniques reveal the stabilisation of the tetragonal phase of zirconia and the existence of iron in highly dispersed form as Fe203 on the catalyst surface. The surface acidic properties were determined by ammonia temperature programmed desorption (TPD) and perylene adsorption, The results were supported by the TGA studies after adsorption of pyridine and 2,6-dimethylpyridine (2,6-DMP), Strong Lewis acid sites on the surface, which are evident from TPD and perylene adsorption studies. explain the high catalytic activity of the systems towards benzoylation. The experimental results provide evidence for the truly heterogeneous nature of the reaction. The studies also establish the resistance to deactivation in the metal incorporated sulphated systems.

Automatic Detection and Classification of Glioma Tumors using Statistical Features

The characterization and grading of glioma tumors, via image derived features, for diagnosis, prognosis, and treatment response has been an active research area in medical image computing. This paper presents a novel method for automatic detection and classification of glioma from conventional T2 weighted MR images. Automatic detection of the tumor was established using newly developed method called Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA).Statistical Features were extracted from the detected tumor texture using first order statistics and gray level co-occurrence matrix (GLCM) based second order statistical methods. Statistical significance of the features was determined by t-test and its corresponding p-value. A decision system was developed for the grade detection of glioma using these selected features and its p-value. The detection performance of the decision system was validated using the receiver operating characteristic (ROC) curve. The diagnosis and grading of glioma using this non-invasive method can contribute promising results in medical image computing