Rietveld refinement study of nanocrystalline copper doped zirconia

Structural studies of Cu-doped zirconia samples with varying Cu content have been carried out. Copper-zirconia samples containing 2-20 mol% Cu were prepared by the co-precipitation technique using tetramethylammonium hydroxide as the precipitating agent and calcined at 773 K in air. The powder XRD data following Rietveld refinement revealed stabilization of zirconia in both tetragonal and cubic phases for all the samples with some monoclinic impurity phase. A decrease in the unit cell parameters of the cubic and tetragonal phase indicates incorporation of copper in the zirconia lattice of both the phases. An increase in the copper concentration (up to 20 mol%) stabilizes zirconia into the cubic phase at the expense of the tetragonal phase, with a decrease in the crystallite size (6-8 nm). Rietveld refinement of the high temperature XRD data reveals that both cubic and tetragonal phases exist up to 723 K with the cubic phase dominating (80% at 723 K). At temperature higher than 723 K, cubic phase gets transformed into the tetragonal phase, which further transforms into the monoclinic phase at 1173 K. At 1173 K, copper comes out of the cubic zirconia lattice forming a separate copper oxide phase and only the tetragonal and monoclinic polymorphs of zirconia exist.     

Using directed hypergraphs to verify rule-based expert systems

Rule-based representation techniques have become popular for storage and manipulation of domain knowledge in expert systems. It is important that systems using such a representation are verified for accuracy before implementation. In recent years, graphical techniques have been found to provide a good framework for the detection of errors that may appear in a rule base. The authors present a graphical representation scheme that: 1) captures complex dependencies across clauses in a rule base in a compact yet intuitively clear manner and 2) is easily automated to detect structural errors in a rigorous fashion. Their technique uses a directed hypergraph to accurately detect the different types of structural errors that appear in a rule base. The technique allows rules to be represented in a manner that clearly identifies complex dependencies across compound clauses. Subsequently, the verification procedure can detect errors in an accurate fashion by using simple operations on the adjacency matrix of the directed hypergraph. The technique is shown to have a computational complexity that is comparable to that of other graphical techniques. The graphical representation coupled with the associated matrix operations illustrate how directed hypergraphs are a very appropriate representation technique for the verification task     

Bioinspired flame retardant polymers of tyrosol

The enzyme catalyzed polymerization of flame retardant (FR) polymers from the renewable resource 2‐(4‐hydroxyphenyl) ethanol (HPE), commonly known as tyrosol, is presented. The synthesis is environmentally friendly and requires only monomer, peroxidase catalyst, dilute hydrogen peroxide, and deionized water. Phenolic polymers are produced in short, one pot, high yield reactions that require minimal purification. Fourier transform infrared spectroscopy and ¹H‐NMR analysis suggest the polymers are coupled through the 1, 2, 4, and 5 positions of the phenol ring and through the phenoxy substituent. Thermogravimetric analysis and pyrolysis combustion flow calorimeter show HPE homopolymers exhibit very low heat release rate and total heat release, while copolymerization with phenol increases already high char yields. Gel permeation chromatography reveals the molecular weight of the polymer increases with ethanol cosolvent concentration. The alcohol cosolvent also increases the proportion of oxyphenylene linkages to the detriment of FR properties. Preliminary quantitative structure–activity relationship toxicity modeling predicts the polymers are negative for developmental toxicity and Ames mutagenicity. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134, 45394.     

Iron minerals and their influence on the optical properties of two Indian kaolins

Kaolin is mostly associated with minor quantities of ancillary minerals containing transition elements such as iron and titanium. These ions impart color to the white kaolin which adversely affects its application in paper and paint industries. Hence their removal is of prime importance in the optimum utilization of kaolin. The coloring effect as well as the mode of removal of these impurities depends on the “species” of the ion and/or the type of mineral. The present paper deals with the investigation on two Indian kaolins of different geological origin, one from Gujarat state at the western part of India and the other from Kerala State at the southern most part. Detailed physical, chemical and mineralogical characterization of the samples was carried out. The product clays after beneficiation by size classification, high gradient magnetic separation and chemical leaching were found to be of acceptable grade for paper industry with respect to optical properties and particle size. The impurity minerals were concentrated by different methods so that their identification was easier. Attempts were made to study the Fe species by correlating the XRD, chemical assay, DCB treatment and EPR spectral information of the clay samples before and after beneficiation. Iron stained anatase was found to be the major impurity in the Gujarat clay whereas iron was present as oxide/hydroxide in the Kerala sample. The beneficiated products from the Kerala clay were found to have better optical properties.     

Differences in the Method by Which Plasma Is Separated from Whole Blood Influences Amphotericin B Plasma Recovery and Distribution Following Amphotericin B Lipid Complex Incubation Within Whole Blood

A previous investigation suggested that the use of plasma as the biological fluid for measurement of amphotericin B (AmpB) concentrations greatly underestimates the concentrations of AmpB in the total blood circulation following amphotericin B lipid complex (ABLC) administration to humans. The purpose of this study was to determine if differences in the method used to obtain plasma from whole blood influences the percentage of AmpB recovered in plasma following ABLC incubation in whole blood. ABLC (5 μg AmpB/ml; peak blood concentration observed in rabbits following intravenous bolus of ABLC at a dose of 1 mg/kg) was incubated in whole blood for 5 min at 25°C. These conditions were used to mimic the sample retrieval conditions used when blood is obtained from animals and human patients. Following incubation, plasma was obtained from whole blood using five different methods: (A) Whole blood was centrifuged for 5 min at 23°C, and the plasma was separated; (B) whole blood was stored at 4°C for 18 h, and the plasma was separated by gravity; (C) whole blood was stored at 23°C for 18 h, and the plasma was separated by gravity; (D) whole blood was stored at 37°C for 18 h in a water bath, and the plasma was separated by gravity; and (E) whole blood was stored at 30°C for 18 h in a water bath, and the plasma was separated by gravity. All samples were protected from light throughout the duration of the experiment. AmpB concentration in each plasma sample was determined by high-performance liquid chromatography (HPLC) using an external calibration curve. The whole blood : plasma Amp B concentration ratio and the percentage of AmpB partitioned into plasma following incubation of ABLC in whole blood for each plasma separation procedure was as follows: (A) 6.5 : 1 blood : plasma AmpB concentration ratio, 15.4% ± 1.6% AmpB in plasma; (B) 2.98 : 1 blood : plasma AmpB concentration ratio, 33.6% ± 7.7% AmpB in plasma; (C) 1.5 : 1 blood : plasma AmpB concentration ratio, 67.6% ± 10.3% AmpB in plasma; (D) 1.5 : 1 blood : plasma concentration ratio, 68.1% ± 1.1% AmpB in plasma; and (E) 1.2 : 1 blood : plasma AmpB concentration ratio; 83.4% ± 5.5% AmpB in plasma. These findings suggest that when measurement of AmpB in plasma is required following ABLC administration, incubation of whole blood at 30°C for 18 h appears to be the most effective method.     

Assessing environmental impacts of aviation on connected cities using environmental vulnerability studies and fluid dynamics: an Indian case study

As the annual air passenger traffic in India is increasing steeply (13.52 million in 2012 compared to 11.02 million in 2010), an environmental impact assessment on important cities connected by air is becoming increasingly indispensable. This study proposes an innovative screening method that uses a modified Environmental Vulnerability Index (EVI). This modified EVI calculator includes aviation-related parameters and can be used to assess the environmental vulnerabilities of political states and cities, in addition to countries as is being already done. This study also suggests the need to include aspects of human comfort in the screening process through the use of state-of-the-art computational fluid dynamical software and large eddy simulations which can be used to estimate forces experienced by aircraft of different sizes during in-flight turbulence for various weather conditions. A comparative analysis is presented on how changing the size of the aircraft operating in a particular route between the cities of Chennai and Bengaluru has better implications on both passenger comfort and the environment. It is observed that if commercial airlines incorporated fewer medium-sized aircraft, there would be a significant reduction in the environmental vulnerability of the two connected cities.     

Modeling and Optimization of Microwave Osmotic Dehydration of Apple Cylinders Under Continuous-Flow Spray Mode Processing Conditions

The objective of this study was to model and optimize the mass transfer behavior during microwave osmotic dehydration of apple cylinders under continuous-flow spray mode processing conditions. Data needed for the model development and optimization were obtained using a central composite rotatable experimental design involving sucrose concentration (33.3–66.8°B), temperature (33.3–66.8 °C), flow rate (2,120–3,480 ml/min), and contact times (5–55 min); and the response variables were moisture loss, solids gain, and weight loss. Mass transfer kinetics was evaluated based on the empirical Azuara model and the conventional diffusion model. Diffusivities of both moisture loss (D _m) and solids gain (D _s) obtained from the diffusion model were related to sucrose concentration, temperature, and flow rate. Optimization was evaluated using a desirability function model which could be used with several imposed constraints. The optimum conditions obtained depended on the imposed constraints. A set of constraints involving maximizing moisture loss and weight reduction while keeping the solids gain below 3.5% gave the following optimal conditions: a 30-min osmotic treatment at 65°B, 60 °C, and 2,800 ml/min flow rate yielding a moisture loss of 40.9%, weight reduction of 37.7%, with a solids gain of 3.32%.     

PREDICTION OF QUALITY CHANGES DURING OSMO-CONVECTIVE DRYING OF BLUEBERRIES USING NEURAL NETWORK MODELS FOR PROCESS OPTIMIZATION

Artificial neural network (ANN) models were used for predicting quality changes during osmo-convective drying of blueberries for process optimization. Osmotic drying usually involves treatment of fruits in an osmotic solution of predetermined concentration, temperature and time, and generally affects several associated quality factors such as color, texture, rehydration ratio as well as the finish drying time in a subsequent drier (usually air drying). Multi-layer neural network models with 3 inputs (concentration, osmotic temperature and contact time) were developed to predict 5 outputs: air drying time, color, texture, and rehydration ratio as well as a defined comprehensive index. The optimal configuration of neural network model was obtained by varying the main parameters of ANN: transfer function, learning rule, number of neurons and layers, and learning runs. The predictability of ANN models was compared with that of multiple regression models, confirming that ANN models had much better performance than conventional mathematical models. The prediction matrices and corresponding response curves for main processing properties under various osmotic dehydration conditions were used for searching the optimal processing conditions. The results indicated that it is feasible to use ANN for prediction and optimization of osmo-convective drying for blueberries.