Electrospun Proficient Polymer Based Nano Fibers with Ceramic Particles

Cobaltite of magnesium, embedded in polyvinylpyrrolidone (PVP) polymeric fibers forming nanocomposite were synthesized by combining conventional sol-gel method with electrospinning method. Ultrathin diameter polymer fibers containing nanoregime ceramic particles were obtained by varying various process parameters like voltage, concentration, feed rate, distance between nozzle tip and base plate on an indigenously assembled electrospinning unit. Polyvinylpyrrolidone (PVP) and polyvinylalcohol (PVA) polymeric fibers in nanoregime were also synthesized separately and the effect of the process parameters was observed on the fiber thickness and continuity. Characterization was done to verify the synthesis parameter effect on structural morphology of polymer based nanofiber composite. Scanning Electron Microscope (SEM) and Transmission Electron Microscope (TEM) were used as tools for study of structural morphology and its correlation with process parameters.     

Effect of Synthesis and Sintering Conditions on the Thermoelectric Properties of n-Doped Mg2Si

Magnesium silicide (Mg₂Si)-based alloys are promising candidates for thermoelectric (TE) energy conversion in the middle–high temperature range. The detrimental effect of the presence of MgO on the TE properties of Mg₂Si based materials is widely known. For this reason, the conditions used for synthesis and sintering were optimized to limit oxygen contamination. The effect of Bi doping on the TE performance of dense Mg₂Si materials was also investigated. Synthesis was performed by ball milling in an inert atmosphere starting from commercial Mg₂Si powder and Bi powder. The samples were consolidated, by spark plasma sintering, to a density >95%. The morphology, and the composition and crystal structure of samples were characterized by field-emission scanning electronic microscopy and x-ray diffraction, respectively. Moreover, determination of Seebeck coefficients and measurement of electrical and thermal conductivity were performed for all the samples. Mg₂Si with 0.1 mol% Bi doping had a ZT value of 0.81, indicative of the potential of this method for fabrication of n-type bulk material with good TE performance.     

Influence of processing on stability,microstructure and thermoelectric properties of Ca3Co4 − xO9 + δ

Due to high figure of merit, Ca₃Co_4 ? xO_9 + δ (CCO) has potential as p-type material for high-temperature thermoelectrics. Here, the influence of processing including solid state sintering, spark plasma sintering and post-calcination on stability, microstructure and thermoelectric properties is reported. By a new post-calcination approach, single-phase materials were obtained from precursors to final dense ceramics in one step. The highest zT of 0.11 was recorded at 800 °C for CCO with 98 and 72% relative densities. In situ high-temperature X-ray diffraction in air and oxygen revealed a higher stability of CCO in oxygen (～970 °C) than in air (～930 °C), with formation of Ca₃Co₂O₆ which also showed high stability in oxygen, even at 1125 °C. Since achievement of phase pure high density CCO by post-calcination method in air is challenging, the phase stability of CCO in oxygen is important for understanding and further improvement of the method.     

Synthesis and Conductivity of Nano Crystalline Ceria

Nanoparticles of cerium oxide were synthesized by the co-precipitation method. Synthesis conditions were optimized for phase purity, particularly the effect of pH (=14,13,11) of solutions during reaction, was studied. The phase analysis and structural properties of the prepared particles were determined by X-ray diffraction analysis. The average crystallite size decreased with the increase in pH of solution. The temperature-dependent DC conductivity was measured in the temperature range 300 °C to 700 °C and was found to be increasing with the increase in measurement temperature. AC conductivity and dielectric constants were measured in the frequency range of 1 kHz to 3 MHz and also at different temperatures.     

Microstructural and Hardness Studies of Cu-10wt.%Sn Alloy Under Different Aging Conditions

Microstructure of Cu-10wt.%Sn alloy, prepared by powder metallurgy technique and sintered at 900 °C for 120 min in hydrogen atmosphere, was studied by optical microscopy and XRD technique as a function of aging time. Isothermal aging of the alloy specimens was performed at 250 °C for a period of 30, 60, 120, 300, and 1440 min after solution treatment at 500 °C for 60 min. Rockwell hardness of aged specimens was also measured at room temperature as a function of aging time. It was observed that microstructure of the as-sintered specimens consists of the grains of alpha Cu-Sn solid solution. Moreover, solution treatment of the alloy specimens followed by quenching in water increased the hardness of the as-sintered alloy specimens from 35.5 to 59.8 HRF due to the residual stresses generated by fast cooling. Aging at 250 °C for 30, 60, and 120 min was found to cause a decrease in hardness from 59.8 to 45.1 HRF, whereas the specimens aged for 300 and 1440 min show an increase in hardness from 45.1 to 75.7 HRF. The values of porosity calculated from XRD patterns of the alloy specimens referred to show that porosity varies with aging time in a manner opposite to that of hardness, e.g., porosity is maximum for 120 min aging time where hardness is minimum.     

Phase Content Influence on Thermoelectric Properties of Manganese Silicide-Based Materials for Middle-High Temperatures

The higher manganese silicides (HMS), represented by MnSi _x (x = 1.71 to 1.75), are promising p-type leg candidates for thermoelectric energy harvesting systems in the middle-high temperature range. They are very attractive as they could replace lead-based compounds due to their nontoxicity, low-cost starting materials, and high thermal and chemical stability. Dense pellets were obtained through direct reaction between Mn and Si powders during the spark plasma sintering process. The tetragonal HMS and cubic MnSi phase amounts and the functional properties of the material such as the Seebeck coefficient and electrical and thermal conductivity were evaluated as a function of the SPS processing conditions. The morphology, composition, and crystal structure of the samples were characterized by scanning electron microscopy, energy-dispersive x-ray spectroscopy, and x-ray diffraction analyses, respectively. Differential scanning calorimetry and thermogravimetric analysis were performed to evaluate the thermal stability of the final sintered material. A ZT value of 0.34 was obtained at 600°C for the sample sintered at 900°C and 90 MPa with 5 min holding time.     

Multi-agent event recognition by preservation of spatiotemporal relationships between probabilistic models

We present a new method for multi-agent activity analysis and recognition that uses low level motion features and exploits the inherent structure and recurrence of motion present in multi-agent activity scenarios.     

Learning semantic features for action recognition via diffusion maps

Efficient modeling of actions is critical for recognizing human actions. Recently, bag of video words (BoVW) representation, in which features computed around spatiotemporal interest points are quantized into video words based on their appearance similarity, has been widely and successfully explored. The performance of this representation however, is highly sensitive to two main factors: the granularity, and therefore, the size of vocabulary, and the space in which features and words are clustered, i.e., the distance measure between data points at different levels of the hierarchy. The goal of this paper is to propose a representation and learning framework that addresses both these limitations.We present a principled approach to learning a semantic vocabulary from a large amount of video words using Diffusion Maps embedding. As opposed to flat vocabularies used in traditional methods, we propose to exploit the hierarchical nature of feature vocabularies representative of human actions. Spatiotemporal features computed around interest points in videos form the lowest level of representation. Video words are then obtained by clustering those spatiotemporal features. Each video word is then represented by a vector of Pointwise Mutual Information (PMI) between that video word and training video clips, and is treated as a mid-level feature. At the highest level of the hierarchy, our goal is to further cluster the mid-level features, while exploiting semantically meaningful distance measures between them. We conjecture that the mid-level features produced by similar video sources (action classes) must lie on a certain manifold. To capture the relationship between these features, and retain it during clustering, we propose to use diffusion distance as a measure of similarity between them. The underlying idea is to embed the mid-level features into a lower-dimensional space, so as to construct a compact yet discriminative, high level vocabulary. Unlike some of the supervised vocabulary construction approaches and the unsupervised methods such as pLSA and LDA, Diffusion Maps can capture local relationship between the mid-level features on the manifold. We have tested our approach on diverse datasets and have obtained very promising results.     

Application of quantitative Raman spectroscopy for the monitoring of polymorphic transformation in crystallization processes using a good calibration practice procedure

Polymorphism is the property of a substance to have more than one crystalline form. Polymorphic forms of the same chemical compound can have different physical and chemical properties that can strongly affect the manufacturing process. For this reason, determining and monitoring polymorphic transformations have become very important, especially in pharmaceutical industry. Significant work has been developed for the calibration of Raman spectroscopy to monitor the presence and amount of solid polymorphs in suspensions during crystallization, as well as the liquid concentration. Nevertheless, a clear and systematic approach to Raman calibration is missing in the literature. The present work has the aim of developing a methodical strategy for Raman calibration, taking into account the principal factors that can affect the Raman spectra of a specific compound in solution, such as solid type, solute concentration, temperature, crystal size and suspension density. Univariate and multivariate calibration techniques were investigated using pre-processing techniques to optimize the signal. The results are combined in a systematic “good calibration practice” (GCP) procedure, proposed for the first time in this work. The approach has been applied for the quantitative monitoring of the polymorphic transformation of ortho-aminobenzoic acid (OABA).