Investigation of ternary zirconia ceramics

Transformation toughening ceramics (TTCs) are engineering materials which combine ceramic properties such as hardness, corrosion resistance and low thermal conductivity with good toughness and mechanical strength. At elevated temperatures their use is limited due to destabilisation of the transformation toughening microstructure (partially stabilised zirconia or PSZ) or creep and hydrothermal degradation (tetragonal zirconia polycrystals or TZPs). Despite these limitations, the use of TTCs, particularly zirconia based, has become widespread. To date, most commercial TTCs are based on combinations of zirconia and one stabilising oxide. This work investigates a zirconia ceramic containing two stabilisers, namely yttria and titania in roughly equal proportions.

Paclitaxel resistance and multicellular spheroid formation are induced by kallikrein-related peptidase 4 in serous ovarian cancer cells in an ascites mimicking microenvironment

High tumor kallikrein-related-peptidase 4 (KLK4) levels are associated with a poor outcome for women with serous epithelial ovarian cancer (EOC), for which peritoneal dissemination and chemoresistance are key events. To determine the role of KLK4 in these events, we examined KLK4-transfected SKOV-3 and endogenous KLK4 expressing OVCA432 cells in 3-dimensional (3D) suspension culture to mimic the ascites microenvironment. KLK4-SKOV-3 cells formed multicellular aggregates (MCAs) as seen in ascites, as did SKOV-3 cells treated with active KLK4. MCA formation was reduced by treatment with a KLK4 blocking antibody or the selective active site KLK4 sunflower trypsin inhibitor (SFTI-FCQR). KLK4-MCAs formed larger cancer cell foci in mesothelial cell monolayers than those formed by vector and native SKOV-3 cells, suggesting KLK4-MCAs are highly invasive in the peritoneal microenvironment. A high level of KLK4 is expressed by ascitic EOC cells compared to matched primary tumor cells, further supporting its role in the ascitic microenvironment. Interestingly, KLK4 transfected SKOV-3 cells expressed high levels of the KLK4 substrate, urokinase plasminogen activator (uPA), particularly in 3D-suspension, and high levels of both KLK4 and uPA were observed in patient cells taken from ascites. Importantly, the KLK4-MCAs were paclitaxel resistant which was reversed by SFTI-FCQR and to a lesser degree by the general serine protease inhibitor, Aprotinin, suggesting that in addition to uPA, other as yet unidentified substrates of KLK4 must be involved. Nonetheless, these data suggest that KLK4 inhibition, in conjunction with paclitaxel, may improve the outcome for women with serous epithelial ovarian cancer and high KLK4 levels in their tumors.

Thermal analysis and application of organoclays for water purification

In recent years, organoclays have become widely used in many industrial applications, and particularly they have been applied as adsorbents for water purification (de Paiva et al., 2008; Zhou et al., 2008; Park et al., 2011). When the organoclays are enhanced by intercalation of cationic surfactant molecules, the surface properties are altered from hydrophilic to highly hydrophobic. These changes facilitate their industrial applications which are strongly dependent on the structural properties of organoclays (Koh and Dixon, 2001; Zeng et al., 2004; Cui et al., 2007). Thus a better understanding of the configuration and structural change in the organoclays by thermogravimetric analysis (TG) is essential. It has been proven that the TG is very useful for the study of complex minerals, modified minerals, and nanomaterials (Laachachi et al., 2005; Palmer et al., 2011; Park et al., in press, 2011). Therefore, the current investigation involves the thermal stability of a montmorillonite intercalated with two types of cationic surfactants: dodecyltrimethylammonium bromide (DDTMA) and didodecyldimethylammonium bromide (DDDMA) using TG. The modification of montmorillonite results in an increase in the interlayer or basal spacing and enhances the environmental and industrial application of the obtained organoclay.

Thermal performance of composite panels under fire conditions using numerical studies : plasterboards, rockwool, glass fibre and cellulose insulations

In recent times, light gauge steel frame (LSF) wall systems are increasingly used in the building industry. They are usually made of cold-formed and thin-walled steel studs that are fire-protected by two layers of plasterboard on both sides. A composite LSF wall panel system was developed recently, where an insulation layer was used externally between the two plasterboards to improve the fire performance of LSF wall panels. In this research, finite element thermal models of the new composite panels were developed using a finite element program, SAFIR, to simulate their thermal performance under both standard and Eurocode design fire curves. Suitable apparent thermal properties of both the gypsum plasterboard and insulation materials were proposed and used in the numerical models. The developed models were then validated by comparing their results with available standard fire test results of composite panels. This paper presents the details of the finite element models of composite panels, the thermal analysis results in the form of time-temperature profiles under standard and Eurocode design fire curves and their comparisons with fire test results. Effects of using rockwool, glass fibre and cellulose fibre insulations with varying thickness and density were also investigated, and the results are presented in this paper. The results show that the use of composite panels in LSF wall systems will improve their fire rating, and that Eurocode design fires are likely to cause severe damage to LSF walls than standard fires.

Inflammation, hepatic enzymes and resistance training in individuals with metabolic risk factors

AIMS: Increases in inflammatory markers, hepatic enzymes and physical inactivity are associated with the development of the metabolic syndrome (MetS). We examined whether inflammatory markers and hepatic enzymes are correlated with traditional risk factors for MetS and studied the effects of resistance training (RT) on these emerging risk factors in individuals with a high number of metabolic risk factors (HiMF, 2.9 +/- 0.8) and those with a low number of metabolic risk factors (LoMF, 0.5 +/- 0.5). METHODS: Twenty-eight men and 27 women aged 50.8 +/- 6.5 years (mean +/- sd) participated in the study. Participants were randomized to four groups, HiMF training (HiMFT), HiMF control (HiMFC), LoMF training (LoMFT) and LoMF control (LoMFC). Before and after 10 weeks of RT [3 days/week, seven exercises, three sets with intensity gradually increased from 40-50% of one repetition maximum (1RM) to 75-85% of 1RM], blood samples were obtained for the measurement of pro-inflammatory cytokines, C-reactive protein (CRP), gamma-glutamyltransferase (GGT) and alanine aminotransferase (ALT). RESULTS: At baseline, HiMF had higher interleukin-6 (33.9%), CRP (57.1%), GGT (45.2%) and ALT (40.6%) levels, compared with LoMF (all P < 0.05). CRP, GGT and ALT correlated with the number of risk factors (r = 0.48, 0.51 and 0.57, respectively, all P < 0.01) and with other anthropometric and clinical measures (r range from 0.26 to 0.60, P < 0.05). RT did not significantly alter inflammatory markers or hepatic enzymes (all P > 0.05). CONCLUSIONS: HiMF was associated with increased inflammatory markers and hepatic enzyme concentrations. RT did not reduce inflammatory markers and hepatic enzymes in individuals with HiMF.

Visualization of thermal characteristics around the absorber tube of a standard parabolic trough thermal collector by 3D simulation

Three dimensional conjugate heat transfer simulation of a standard parabolic trough thermal collector receiver is performed numerically in order to visualize and analyze the surface thermal characteristics. The computational model is developed in Ansys Fluent environment based on some simplified assumptions. Three test conditions are selected from the existing literature to verify the numerical model directly, and reasonably good agreement between the model and the test results confirms the reliability of the simulation. Solar radiation flux profile around the tube is also approximated from the literature. An in house macro is written to read the input solar flux as a heat flux wall boundary condition for the tube wall. The numerical results show that there is an abrupt variation in the resultant heat flux along the circumference of the receiver. Consequently, the temperature varies throughout the tube surface. The lower half of the horizontal receiver enjoys the maximum solar flux, and therefore, experiences the maximum temperature rise compared to the upper part with almost leveled temperature. Reasonable attributions and suggestions are made on this particular type of conjugate thermal system. The knowledge that gained so far from this study will be used to further the analysis and to design an efficient concentrator photovoltaic collector in near future.

Three dimensional simulation of a parabolic trough concentrator thermal collector

Parabolic Trough Concentrators (PTC) are the most proven solar collectors for solar thermal power plants, and are suitable for concentrating photovoltaic (CPV) applications. PV cells are sensitive to spatial uniformity of incident light and the cell operating temperature. This requires the design of CPV-PTCs to be optimised both optically and thermally. Optical modelling can be performed using Monte Carlo Ray Tracing (MCRT), with conjugate heat transfer (CHT) modelling using the computational fluid dynamics (CFD) to analyse the overall designs. This paper develops and evaluates a CHT simulation for a concentrating solar thermal PTC collector. It uses the ray tracing work by Cheng et al. (2010) and thermal performance data for LS-2 parabolic trough used in the SEGS III-VII plants from Dudley et al. (1994). This is a preliminary step to developing models to compare heat transfer performances of faceted absorbers for concentrating photovoltaic (CPV) applications. Reasonable agreement between the simulation results and the experimental data confirms the reliability of the numerical model. The model explores different physical issues as well as computational issues for this particular kind of system modeling. The physical issues include the resultant non-uniformity of the boundary heat flux profile and the temperature profile around the tube, and uneven heating of the HTF. The numerical issues include, most importantly, the design of the computational domain/s, and the solution techniques of the turbulence quantities and the near-wall physics. This simulation confirmed that optical simulation and the computational CHT simulation of the collector can be accomplished independently.

Multi-scale numerical simulations of thermal expansion properties of CNT-reinforced nanocomposites

In this work, the thermal expansion properties of carbon nanotube (CNT)-reinforced nanocomposites with CNT content ranging from 1 to 15 wt% were evaluated using a multi-scale numerical approach, in which the effects of two parameters, i.e., temperature and CNT content, were investigated extensively. For all CNT contents, the obtained results clearly revealed that within a wide low-temperature range (30°C ~ 62°C), thermal contraction is observed, while thermal expansion occurs in a high-temperature range (62°C ~ 120°C). It was found that at any specified CNT content, the thermal expansion properties vary with temperature - as temperature increases, the thermal expansion rate increases linearly. However, at a specified temperature, the absolute value of the thermal expansion rate decreases nonlinearly as the CNT content increases. Moreover, the results provided by the present multi-scale numerical model were in good agreement with those obtained from the corresponding theoretical analyses and experimental measurements in this work, which indicates that this multi-scale numerical approach provides a powerful tool to evaluate the thermal expansion properties of any type of CNT/polymer nanocomposites and therefore promotes the understanding on the thermal behaviors of CNT/polymer nanocomposites for their applications in temperature sensors, nanoelectronics devices, etc.

The difference of thermal stability between Fe-substituted palygorskite and Al-rich palygorskite

Sedimentary palygorskite (SP) and hydrothermal palygorskite (HP) were characterized by XRF, TG/DSC, andXRD. The total iron and dissociative iron in palygorskite were detected using spectrophotometry. The results showed that about 3.57 wt% of Fe2O3 was detected in SP in contrast with 0.4 wt% in HP. SP was a Fe-substituted palygorskite, and HP was an Al-rich palygorskite. The occurrence of Fe substitution in SP resulted in two mass loss steps of coordinated water and resulted in a larger d spacing. The SP showed greater thermal stability than the HP. It was proposed the change of (200) diffraction peak and (240) diffraction peak reflect changes of tetrahedral and octahedral structures in palygorskite.

Studies on self-assembly hydrothermal fabrication and thermal stability of Chromium oxyhydroxide nanomaterials synthesised from Chromium oxide colloids

Chromium oxyhydroxide nanomaterials with narrow size-distribution were synthesised through a simple hydrothermal method. Experimental conditions, such as reaction duration and pH values of the precipitation process and hydrothermal treatment played important roles in determining the nature of the final product chromium oxyhydroxide nanomaterials. The effect of these synthesis parameters were studied with the assistance of X-ray diffraction, scanning electron microscopy, X-ray photoelectron spectroscopy and thermogravimetric analyses. This research has developed a controllable synthesis of Chromium oxyhydroxide nanomaterials from Chromium oxide colloids.

Application of TG-FTIR to study SO2 evolved during the thermal decomposition of coal-derived pyrite

The thermal decomposition of the coal-derived pyrite was studied using thermogravimetry combining with Fourier-transform infrared spectroscopy (TG-FTIR) techniques to gain knowledge on the SO2 gas evolution process and formation mechanism during the thermal decomposition of the coal-derived pyrite. The results showed that the thermal decomposition of the coal-derived pyrite which started at about 400 ◦C was complete at 600 ◦C; the gas evolved can be established by combining the DTG peak, the Gram–Schmidt curve and in situ FTIR spectroscopic evolved gas analysis. It can be observed from the spectra that the pyrolysis products for the sample mainly vary in quantity, but not in species. It was proposed that the oxidation of the coal-derived pyrite started at about 400 ◦C and that pyrrhotite and hematite were formed as primary products. The SO2 released by the thermal decomposition of the coal-derived pyrite mainly occurred in the first pyrolysis stage between 410 and 470 ◦C with the maximum rate at 444 ◦C. Furthermore, the SO2 gas evolution and formation mechanism during the thermal decomposition of the coal-derived pyrite has been proposed.

Preparation and thermal energy storage properties of paraffin/calcined diatomite composites as form-stable phase change materials

A composite paraffin-based phase change material (PCM) was prepared by blending composite paraffin and calcined diatomite through the fusion adsorption method. In this study, raw diatomite was purified by thermal treatment in order to improve the adsorption capacity of diatomite, which acted as a carrier material to prepare shape-stabilized PCMs. Two forms of paraffin (paraffin waxes and liquid paraffin) with different melting points were blended together by the fusion method, and the optimum mixed proportion with a suitable phase-transition temperature was obtained through differential scanning calorimetry (DSC) analysis. Then the prepared composite paraffin was adsorbed in calcined diatomite. The prepared paraffin/calcined diatomite composites were characterized by the scanning electron microscope (SEM) and Fourier transformation infrared (FT-IR) analysis techniques. Thermal energy storage properties of the composite PCMs were determined by DSC method. DSC results showed that there was an optimum adsorption ratio between composite paraffin and calcined diatomite and the phase-transition temperature and the latent heat of the composite PCMs were 33.04 ◦C and 89.54 J/g, respectively. Thermal cycling test of composite PCMs showed that the prepared material is thermally reliable and chemically stable. The obtained paraffin/calcined diatomite composites have proper latent heat and melting temperatures, and show practical significance and good potential application value.

Genetic variability and antimicrobial resistance of Ureaplasma parvum in response to maternal erythromycin treatment : a study in pregnant sheep

Background: Ureaplasmas are the most frequently isolated microorganisms from the amniotic fluid (AF) of pregnant women and can cause chronic infections that are difficult to eradicate with standard macrolide treatment. We tested the effects of erythromycin treatment on phenotypic and genotypic markers of ureaplasmal antimicrobial resistance in sheep. Method: At 50 days of gestation (d, term=145d) 12 pregnant ewes received intra-amniotic injections of U. parvum serovar 3 (erythromycin-sensitive, 2x104 colony-forming-units). At 100d ewes received: erythromycin treatment (500 mg, q3h for 4 days, IM, n=6) or no treatment (n=6). Fetuses were delivered surgically (125d) and AF and chorioamnion were collected for: culture, minimum inhibitory concentration (MIC) and minimum biofilm inhibitory concentration (MBIC) testing; 23S rRNA sequencing; and detection of macrolide-lincosamide-streptogramin resistance (MLSr) genes. Results: MICs of erythromycin, azithromycin and roxithromycin against AF isolates were low (range = 0.06 mg/L to 1.0 mg/L); however, chorioamnion isolates demonstrated increased resistance to roxithromycin (0.13 – 5.33 mg/L). 62.5% of chorioamnion ureaplasmas formed biofilms in vitro and mutations (125 nucleotides, 29.6%) were found in the 23S rRNA gene (domain V) of chorioamnion (but not AF) ureaplasmas. MLSr genes (ermB, msrC and msrD) were detected in 100% of chorioamnion isolates and only msrD was detected in AF isolates (40%). Conclusions: 23S rRNA mutations and MLSr genes occurred independently of erythromycin treatment, suggesting that the anatomical site of infection and microenvironment may exert selective pressures on ureaplasmas that cause genetic changes and alter antimicrobial sensitivity profiles. These results have serious implications for treatment of in utero infections.

Breast cancer detection from thermal images using bispectral invariant features

Highly sensitive infrared (IR) cameras provide high-resolution diagnostic images of the temperature and vascular changes of breasts. These images can be processed to emphasize hot spots that exhibit early and subtle changes owing to pathology. The resulting images show clusters that appear random in shape and spatial distribution but carry class dependent information in shape and texture. Automated pattern recognition techniques are challenged because of changes in location, size and orientation of these clusters. Higher order spectral invariant features provide robustness to such transformations and are suited for texture and shape dependent information extraction from noisy images. In this work, the effectiveness of bispectral invariant features in diagnostic classification of breast thermal images into malignant, benign and normal classes is evaluated and a phase-only variant of these features is proposed. High resolution IR images of breasts, captured with measuring accuracy of ±0.4% (full scale) and temperature resolution of 0.1 °C black body, depicting malignant, benign and normal pathologies are used in this study. Breast images are registered using their lower boundaries, automatically extracted using landmark points whose locations are learned during training. Boundaries are extracted using Canny edge detection and elimination of inner edges. Breast images are then segmented using fuzzy c-means clustering and the hottest regions are selected for feature extraction. Bispectral invariant features are extracted from Radon projections of these images. An Adaboost classifier is used to select and fuse the best features during training and then classify unseen test images into malignant, benign and normal classes. A data set comprising 9 malignant, 12 benign and 11 normal cases is used for evaluation of performance. Malignant cases are detected with 95% accuracy. A variant of the features using the normalized bispectrum, which discards all magnitude information, is shown to perform better for classification between benign and normal cases, with 83% accuracy compared to 66% for the original.