In situ growth of Prussian blue nanocubes on polypyrrole nanoparticles: facile synthesis,characterization and their application as fiber optic gas sensor

Polypyrrole (PPy) and polypyrrole/Prussian blue (PPy–PB) nanocomposite-based fiber optic gas sensors are developed for gas sensing application. Prussian blue (PB) nanocubes are successfully grown on polypyrrole (PPy) nanoparticles by in situ oxidative polymerization method to obtain PPy–PB nanocomposite. PPy and PPy–PB are evaluated based on structural, morphological and electrical properties. The characteristic peaks present in the FTIR spectra of pure PPy and PB nanoparticles are also present in the FTIR spectrum of PPy–PB nanocomposite with small shifts in the absorption maximum. The XRD pattern reveals the semicrystalline structure of PPy–PB nanocomposite with an average crystallite size of 22 nm, and the morphology (FESEM) shows the formation of PB nanocubes over PPy matrix. AC conductivity measurements show slight improvement in the conductivity value of PPy–PB in comparison with PPy. Dielectric studies in the frequency range of 50 Hz–5 MHz reveal that PPy–PB nanocomposite is a high-k dielectric material. At 50 Hz, PPy–PB exhibits high dielectric constants of 1149 and 766 with low dielectric loss values of 9.9 and 4.6 at 150 and 120 °C, respectively. Further, their application as fiber optic gas sensors in sensing various gases is studied using fiber optic technique. The spectral response is studied for various concentrations (0–500 ppm) of ammonia, acetone and ethanol gases at room temperature. The study shows that the spectral intensity increases linearly with different concentrations of all gases. The clad-modified fiber optic sensor with PPy–PB nanocomposite exhibits enhanced sensitivity for ethanol than clad-modified fiber optic sensor with PPy nanoparticles. TGA studies reveal the high thermal stability of PPy–PB nanocomposite. Hence, PPy–PB-based fiber optic sensors can be used to sense toxic ethanol vapor not only at room temperature but also in a composite environment where a temperature variation is expected.     

Attic radiant barrier systems: A sensitivity analysis of performance parameters

During the past seven years, the Florida Solar Energy Center (FSEC) has conducted extensive experimental research on radiant barrier systems (RBS). This paper presents recent research on the development of mathematical attic models and results from a sensitivity analysis of RBS performance parameters. Two levels of modelling capability have been developed. A very simplified model based on ASHRAE procedures is used to study the sensitivity of RBS performance parameters, and a very detailed finite-element model is used to study highly complex phenomena, including moisture adsorption and desorption in attics. The speed of the simple model allows a large range of attic parameters to be studied quickly, and the finite-element model provides a detailed understanding of combined heat and moisture transport in attics. This paper concentrates on the sensitivity analysis of attic RBS performance parameters using the simplified model. The development of the model is described, and results of the analyses are presented and discussed. Results from the finite-element model are also presented and compared with measurements from a test attic to illustrate the effects of moisture adsorption and desorption in common attics. The simplified steady-state model shows excellent agreement with measured steady-state data when thermal stratification of the attic air is modelled. Results of the sensitivity analysis using this model show that the radiant barrier surface emittance and the attic ventilation inlet air temperature are the most sensitive performance parameters for attic radiant barrier systems. The detailed, finite-element model shows that moisture sorption phenomena can have significant effects in attics. The daily temperature extremes in attics are significant, and they induce a moisture flux at the surfaces of the materials bounding the air zone(s). If this moisture flux is not accounted for in detail (i.e. with fully coupled heat and moisture transport equations) inaccurate surface temperature predictions are likely to occur.     

Effect of storage period on provitamin-A carotenoids retention in biofortified maize hybrids

Vitamin A-rich maize hybrids provide sustainable solutions to malnutrition. However, significant loss of carotenoids during storage reduces its efficacy. Grains of nine sub-tropically adapted crtRB1-based biofortified hybrids along with six normal hybrids were stored under conventional storage for five months. PVAC (β-carotene and β-cryptoxanthin) among crtRB1-based hybrids degraded from initial level of 18.77 to 3.24 µg g⁻¹, while NPVAC (lutein and zeaxanthin) reduced to 10.79 µg g⁻¹ from 19.00 µg g⁻¹ during storage. Among PVAC, β-cryptoxanthin (21.8%) possessed more stability than β-carotene (16.4%). For NPVAC, lutein (61.2%) showed the highest retention than zeaxanthin (50.4%). Majority of the PVAC loss occurred within first three months of storage. Retention for PVAC among crtRB1-based hybrids varied from 14% to 23% indicating the role of favourable genetic factors. APQH1, APQH7 and APH2 were the promising hybrids with higher retention (>20%) of PVAC. This is the first report on identification of provitamin A-rich crtRB1-based biofortified maize hybrids with higher retention during sub-tropical storage.     

Advance electrochemical oxidation of fipronil contaminated wastewater by graphite anodes and sorbent nano hydroxyapatite

Degradation of C₁₂H₄Cl₂F₆N₄OS phenylpyrazole insecticide (Fipronil) by advance electrochemical oxidation in aqueous water solution was studied. The process efficiency was figured based on the COD, chloride, and fluoride reduction from fipronil. Further, we tried to highlight the importance of nano-hydroxyapatite (n-Hap) as a cost-effective nano sorbent for removal of fluoride from fipronil. From the advance electrochemical oxidation experiment, it was found that the COD removal was 79%, chloride 52%, and fluoride 80%. The intermediate of fipronil compounds was examined by GC-MS. The final results conclude that advance electrochemical oxidation process was effective for removal of fipronil synthetic wastewater.     

Energy use efficiency of Indian cement companies: a data envelopment analysis

The present paper aims at measuring energy use efficiency in Indian cement industry and estimating the factors explaining inter-firm variations in energy use efficiency. Within the framework of production theory, data envelopment analysis has been used to measure energy use efficiency. Using firm-level data from electronic PROWESS database for the years 1989–1990 through 2006–2007, the study first estimates energy use efficiency of the firms and then compares the efficiency scores across. Empirical results suggest that there is enough scope for the Indian cement firms to reduce energy uses, though this potential for energy saving varies across firms. A second-stage regression analysis reveals that firms with larger production volume have higher energy efficiency scores and that age of the firms impacts differently on energy use efficiency obtained from two different models. Also, higher quality of labor force associates with higher energy use efficiency.     

Mechanical properties of high temperature cyanate ester/BMI blend composites

A new Schiff base functionalized dicyanate ester was synthesized and the monomer was characterized by FTIR, ¹H-NMR, ¹³C-NMR and elemental analysis techniques. This prepared dicyanate ester with catalyst was then blended with BMI resin at different ratios by solution technique. The composites were made by impregnating the fibers with the blend solution followed by curing at various time-temperature schedules. The mechanical properties of the blend composites were tested. The fiber volume fraction of the composites were found to be in the range 41 ± 3%. The mechanical properties such as tensile modulus (32–35 GPa), flexural modulus (56–59 GPa) and Mode I fracture toughness (G_IC = 104–136 J/m²) and impact response (1,121–1,218 J/m) were found to increase with increasing cyanate ester content in the Cy/BMI blends. From the DMA study it was observed that as the cyanate content increases from 3 to 9% in the blend the tan δ value increases from 0.112 to 0.126 and the storage modulus decreases from 24,750 to 22,870 MPa indicating that the crosslink density of the blends decreases. The SEM analysis shows the absence of phase separation. Moisture absorption and chemical resistance of the blend composites increase with increasing cyanate content. POLYM. COMPOS., 2009. © 2009 Society of Plastics Engineers     

Multivariate polynomial fit: Decay heat removal system and pectin degrading Fe3O4‐SiO2 nanobiocatalyst activity

Herein, multivariate Lagrange''s interpolation polynomial (MLIP) and multivariate least square (MLS) methods are used to derive linear and higher‐order polynomials for two varied applications. (1) For an effective fabrication of Pectin degrading Fe₃O₄‐SiO₂ Nanobiocatalyst activity (IU/mg). Here, the three parameters namely: pH value, pectinase loading and temperature as independent variables are optimized for the maximal of anobiocatalyst activity as a dependent variable. (2) For a passive system reliability estimation of decay heat removal (DHR) of a nuclear power plant. The success criteria of the system depend on three types temperature that do not exceed their respective design safety limits and are considered as dependent variables and 14 significant parameters were used as independent variables. Statistically, the validation of these multivariate polynomials are done by testing of hypothesis. Comparative study of the proposed approach gives significance results in the first application have the optimum conditions for maximum activity using linear MLIP method is: 58.64 with pH = 4, pL = 250 and Temp = 4°C. The maximum activity using second order MLIP method is 59.825 and method of MLS is 59.8249 with the optimized values of an independent variables pH = 4, pL = 300 and Temp = 8°C depicted in Table 1. In DHR system, the significance results are obtained and depicted in Table 2.     

Stability analysis and implementation of chopper fed DC series motor with hybrid PID-ANN controller

The attempt is made to enhance the performance of a closed loop control of DC series motor fed by DC chopper (DC-DC buck converter) by hybridization of PID controller with an intelligent control using ANN (Artificial Neural Network) controller. This system consists of inner current controller loop and outer PID-ANN based speed controller loop. The current controller allows the PWM (Pulse Width Modulation) signal when the motor current is less than set value. The PID-ANN speed controller controls the motor voltage by controlling the duty cycle of the chopper thereby the motor speed is regulated. The PID-ANN controller performances are analyzed in both steady state and dynamic operating condition with various set speed and various load torque. The rise time, maximum over shoot, settling time, steady state error and speed drops are taken for comparison with conventional PID controller and existing work. The steady state stability analysis of the system also is made by using the transfer function model with MATLAB. The training data for PID-ANN controller is taken from conventional PID controller. The Hybrid PID-ANN controller with DC chopper has better control over the conventional PID controller and the reported existing work. This system is simulated using MATLAB/Simulink and also it is implemented with a NXP 80C51 family Microcontroller (P89V51RD2 BN) based Embedded System.