Thermoelectric properties of SbNCa3 and BiNCa3 for thermoelectric devices and alternative energy applications

Thermoelectric properties of two antiperovskites SbNCa₃ and BiNCa₃ are calculated using first principles calculations. High values of Seebeck coefficients are observed for these materials. Electrical and thermal conductivities are also calculated. Increase in thermal conductivity and decrease in electrical conductivity are found with increasing temperature. The maximum values of thermal conductivity are 92×10¹⁴  W/m K s and 88×10¹⁴  W/m K s for SbNCa₃ and BiNCa₃ respectively at a temperature of 900 K. The peak values of 5×10²⁰/Ω m s and 5.2×10²⁰/Ω m s are achieved for n-type SbNCa₃ and BiNCa₃ respectively at a temperature of 300 K. Figure of merit is achieved for these materials at room temperature which shows that these materials can be useful for thermoelectric devices and alternative energy sources.     

Effect of Addition of Ni metal catalyst onto the Co and Fe supported catalysts for the formation of carbon nanotubes

Production of novel porous material is a major target in current material science research due to its wide applications. As carbon nanotube (CNTs) is a one dimensional hollow structure it is also one of the promising materials in applications ranging from electronics to hydrogen storage medium. Catalytic chemical vapor deposition (CCVD) is a method whereby CNTs can be produced in large amount. Thus, in this work, we have synthesized CNTs via pyrolysis of acetylene using various supported transition-metal catalysts in a fixed-bed reactor. Scanning electron microscope (SEM) and transmission electron microscope (TEM) were used to investigate the CNTs structure. The structures of nanotubes formed by acetylene pyrolysis were dependent on the catalysts used. It was found that alumina supported Ni/Fe catalyst inhibited the formation of CNTs growth while alumina supported Ni/Co catalyst gave high density of CNTs. However, nanotubes grown over alumina supported Ni/Fe catalyst were less dense due to the deactivation of the catalyst at the early stage of the pyrolysis process.     

Surface modification of henequen (Agave fourcroydes) fibers by ultraviolet curing with 2‐hydroxyethylacrylate and ethylacrylate: Effect of additives on degradable properties

Henequen fibers were grafted with a double impregnating monomer 2‐hydroxyethylacrylate (HEA) and ethylacrylate (EA) to improve the physicomechanical properties. The fibers soaked in different concentration (1–10%) of monomer + MeOH solution along with photoinitiator Irgacure 907 [2%] were cured under ultraviolet (UV) lamp at different UV radiation intensities (2–14 passes). Concentration of monomer at different radiation intensities was optimized with extent of mechanical properties such as polymer loading, tensile strength, and elongation at break. Enhanced tensile strength (268%) and elongation at break (110%) were achieved by the polymer treated fibers than untreated virgin fibers. We observed that, henequen fibers treated by 3% EA showed better physico‐mechanical properties than those treated by 5% HEA. The tensile properties of henequen fibers treated by 3% EA can be enhanced by adding aloxysilane; 3‐(trimethoxysilyl) propylmethacrylate additives with bulk monomer EA (3%). The degradability of the treated and untreated fibers due to accelerated weathering were also studied and it has been found that surface modified henequen fibers produced more resistivity towards different weathering conditions than untreated fibers. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 102: 4000–4006, 2006     

Micellar association in simultaneous presence of organic salts/additives

Viscosity measurements under Newtonian flow conditions had been performed on cetyltrimethylammonium bromide (CTAB) aqueous solutions in the combined presence of sodium salts of aromatic acids (sodium salicylate, NaSal; sodium benzoate, NaBen; sodium anthranilate, NaAn) and organic additives (1-hexanol, C₆OH; n-hexylamine, C₆NH₂) at 30°C. On addition of C₆OH or C₆NH₂, the viscosity of 25 mM CTAB solution remained nearly constant without salt as well as with a lower salt concentration. This is due to low CTAB concentration which is not sufficient to produce structural changes in this concentration range of salts. However, as the salt concentration was increased further, the effect of C₆OH/C₆NH₂ addition was different with different salts: The viscosity first increased; then a decrease was observed with the former while with C₆NH₂ a decrease followed by constancy appeared in plots of relative viscosities (η _r ) vs. organic additive concentrations. At further higher salt concentration, the magnitude of η _r was much higher. The viscosity increase is explained in terms of micellar growth and the decrease in terms of swollen micelle formation (due to interior solubilization of organic additive) or micellar disintegration (due to formation of water + additive pseudophase).     

Lipid Class and Fatty Acid Composition of Psoralia corylifolia Seed

The purified crude lipid of Psoralia corylifolia seeds was subjected to lipid class and fatty acid analysis by thin layer and gas chromatography. The lipid classes identified were triacyl glycerol, free fatty acid, diacyl glycerol, mono acyl glycerol, hydrocarbon-waxester and polar lipid fractions. Most of the fractions were found to contain high level of C_18:1 while C_18:0, C_18:3 and C_20:0 were also found to be present in all the lipid fractions. It has been observed that the diacyl and monoacyl glycerol fractions contain significant amounts of C_14:0 and C_18:0 while the hydrocarbon-waxester fraction was rich in C_22:0. The polar lipids contain high level of C_18:3 and low level of C_18:1 as compared to other lipid fractions. The fatty acid composition of the whole oil was also determined and found to be similar to other fractions. Unidentified long chain fatty acids were also present in significant amounts in all the lipid fractions.     

Photochemical oxidation of fatty acid esters with and without chlorophyll

1. It has been confirmed that the principal products formed in the oxidation of methyl oleate by oxygen under a variety of conditions are predominantlytrans hydroperoxides. However no inversion of the double bond occurs in unoxidized oleate. Hence the conversion ofcis totrans double bonds and peroxide formation occur together in the same molecules.
2. The autoxidation of methyl linoleate at low temperature yields predominantlycis,trans conjugated hydroperoxides. Autoxidation at 25°C., oxidation catalyzed by visible light, or ultraviolet light and copper soap catalyzed oxidation at temperatures appreciably above 0°C., lead to the formation primarily oftrans,trans conjugated hydroperoxides. The inversion of the second double bond in this case appears to be independent of the peroxide-forming reactions.
3. The photochlorophyll oxidation of methyl linoleate leads to the formation of some unconjugated hydroperoxides, some of which containtrans double bonds.
4. Under all of the conditions employed in the present investigation, the oxidation of methyl oleate and linoleate led primarily to the formation of monomeric peroxides which retained most of the unsaturation of the parent compound.

     

The antioxidant activity of amino acids in two vegetable oils

Of 27 amino acids studied, most had some antioxidant activity when added in aqueous solution to either safflower oil or a mixture of sunflower and cottonseed oil (active oxygen and storage methods). Cysteine-HCl, glutamic acid-HCl (in the mixture), and glutamic acid-HCl (in safflower oil) behaved as prooxidants. When added as a solid, most amino acids were ineffective. The protection factors of these amino acids were less than 1.3 in safflower oil with methionine, proline, lysine and cysteine providing the highest activ-ity. In the oil mixture (which had a higher metal content) lysine, arginine, glutamic acid, methionine, and hydroxyproline were anti-oxidant with protection factors of up to 1.85. Chelation of metals by amino acids was presumably responsible for the antioxidant activity. The increase in cysteine concentration up to 1% has more than doubled the protection factor in Bint oil (compared with the 0.01% level), whereas with some other amino acids the increase was either small or slight.     

Growth and formation mechanism of sea urchin-like ZnO nanostructures on Si

Sea urchin-like nanostructures of ZnO consisting of ZnO nanowires with blunt faceted ends were grown on Si (100) substrates by oxidation of metallic Zn at 600 °C. ZnO nanowires having a diameter of 30–60 nm and length of 2–4 Μm were in similar shape with uniform diameter along its entire length with well faceted blunt ends. X-ray diffraction and transmission electron microscope analysis showed that the as-grown nanostructures were highly crystalline with wurtzite hexagonal structure having lattice constants of a=b=3.25 å and c=5.21 å. Room temperature photoluminescence (PL) measurements showed a weak near band-edge emission at 380 nm, but a strong green emission at 500–530 nm. A model for vapor-solid (VS) growth mechanism of ZnO nanowires was presented, in which nucleation of ZnO is crucial for the growth of the nanostructures.     

Painting-91: a large scale database for computational painting categorization

Computer analysis of visual art, especially paintings, is an interesting cross-disciplinary research domain. Most of the research in the analysis of paintings involve medium to small range datasets with own specific settings. Interestingly, significant progress has been made in the field of object and scene recognition lately. A key factor in this success is the introduction and availability of benchmark datasets for evaluation. Surprisingly, such a benchmark setup is still missing in the area of computational painting categorization. In this work, we propose a novel large scale dataset of digital paintings. The dataset consists of paintings from 91 different painters. We further show three applications of our dataset namely: artist categorization, style classification and saliency detection. We investigate how local and global features popular in image classification perform for the tasks of artist and style categorization. For both categorization tasks, our experimental results suggest that combining multiple features significantly improves the final performance. We show that state-of-the-art computer vision methods can correctly classify 50 % of unseen paintings to its painter in a large dataset and correctly attribute its artistic style in over 60 % of the cases. Additionally, we explore the task of saliency detection on paintings and show experimental findings using state-of-the-art saliency estimation algorithms.     

Performance analysis of support vector machines classifiers in breast cancer mammography recognition

Support vector machine (SVM) is a supervised machine learning approach that was recognized as a statistical learning apotheosis for the small-sample database. SVM has shown its excellent learning and generalization ability and has been extensively employed in many areas. This paper presents a performance analysis of six types of SVMs for the diagnosis of the classical Wisconsin breast cancer problem from a statistical point of view. The classification performance of standard SVM (St-SVM) is analyzed and compared with those of the other modified classifiers such as proximal support vector machine (PSVM) classifiers, Lagrangian support vector machines (LSVM), finite Newton method for Lagrangian support vector machine (NSVM), Linear programming support vector machines (LPSVM), and smooth support vector machine (SSVM). The experimental results reveal that these SVM classifiers achieve very fast, simple, and efficient breast cancer diagnosis. The training results indicated that LSVM has the lowest accuracy of 95.6107 %, while St-SVM performed better than other methods for all performance indices (accuracy = 97.71 %) and is closely followed by LPSVM (accuracy = 97.3282). However, in the validation phase, the overall accuracies of LPSVM achieved 97.1429 %, which was superior to LSVM (95.4286 %), SSVM (96.5714 %), PSVM (96 %), NSVM (96.5714 %), and St-SVM (94.86 %). Value of ROC and MCC for LPSVM achieved 0.9938 and 0.9369, respectively, which outperformed other classifiers. The results strongly suggest that LPSVM can aid in the diagnosis of breast cancer.