Fabrication of device quality films of high loaded PPy/MWCNT nanocomposites using pulsed laser deposition

Polypyrrole (PPy) - multiwalled carbonnanotubes (MWCNT) nanocomposites with various MWCNT loading were prepared by in situ inversion emulsion polymerization technique. High loading of the nano filler were evaluated because of available inherent high interface area for charge separation in the nanocomposites. Solution processing of these conducting polymer nanocomposites is difficult because, most of them are insoluble in organic solvents. Device quality films of these composites were prepared by using pulsed laser deposition techniques (PLD). Comparative study of X-ray photoelectron spectroscopy (XPS) of bulk and film show that there is no chemical modification of polymer on ablation with laser. TEM images indicate PPy layer on MWCNT surface. SEM micrographs indicate that the MWCNT's are distributed throughout the film. It was observed that MWCNT in the composite held together by polymer matrix. Further more MWCNT diameter does not change from bulk to film indicating that the polymer layer remains intact during ablation. Even for very high loadings (80 wt.% of MWCNT's) of nanocomposites device quality films were fabricated, indicating laser ablation is a suitable technique for fabrication of device quality films. Conductivity of both bulk and films were measured using collinear four point probe setup. It was found that overall conductivity increases with increase in MWCNT loading. Comparative study of thickness with conductivity indicates that maximum conductivity was observed around 0.2 mu m. (C) 2010 Elsevier B.V. All rights reserved.

Risk minimization in water quality control problems of a river system

Methodologies are presented for minimization of risk in a river water quality management problem. A risk minimization model is developed to minimize the risk of low water quality along a river in the face of conflict among various stake holders. The model consists of three parts: a water quality simulation model, a risk evaluation model with uncertainty analysis and an optimization model. Sensitivity analysis, First Order Reliability Analysis (FORA) and Monte-Carlo simulations are performed to evaluate the fuzzy risk of low water quality. Fuzzy multiobjective programming is used to formulate the multiobjective model. Probabilistic Global Search Laussane (PGSL), a global search algorithm developed recently, is used for solving the resulting non-linear optimization problem. The algorithm is based on the assumption that better sets of points are more likely to be found in the neighborhood of good sets of points, therefore intensifying the search in the regions that contain good solutions. Another model is developed for risk minimization, which deals with only the moments of the generated probability density functions of the water quality indicators. Suitable skewness values of water quality indicators, which lead to low fuzzy risk are identified. Results of the models are compared with the results of a deterministic fuzzy waste load allocation model (FWLAM), when methodologies are applied to the case study of Tunga-Bhadra river system in southern India, with a steady state BOD-DO model. The fractional removal levels resulting from the risk minimization model are slightly higher, but result in a significant reduction in risk of low water quality. (c) 2005 Elsevier Ltd. All rights reserved.

High-quality annotation of promoter regions for 913 bacterial genomes

Motivation: The number of bacterial genomes being sequenced is increasing very rapidly and hence, it is crucial to have procedures for rapid and reliable annotation of their functional elements such as promoter regions, which control the expression of each gene or each transcription unit of the genome. The present work addresses this requirement and presents a generic method applicable across organisms. Results: Relative stability of the DNA double helical sequences has been used to discriminate promoter regions from non-promoter regions. Based on the difference in stability between neighboring regions, an algorithm has been implemented to predict promoter regions on a large scale over 913 microbial genome sequences. The average free energy values for the promoter regions as well as their downstream regions are found to differ, depending on their GC content. Threshold values to identify promoter regions have been derived using sequences flanking a subset of translation start sites from all microbial genomes and then used to predict promoters over the complete genome sequences. An average recall value of 72% (which indicates the percentage of protein and RNA coding genes with predicted promoter regions assigned to them) and precision of 56% is achieved over the 913 microbial genome dataset.