Preparation and characterization of conductive polypyrrole/kaolinite composites

Conductive polypyrrole (PPy)/kaolinite clay composites were prepared by in situ chemical polymerization of pyrrole in the presence of kaolinite using FeCl₃ as oxidant. The PPy content and conductivity of the composites reached 32.8% and 8.3×10^?2 S/cm at HCl concentrations of 1.5 M and 0.5 M, respectively. The microhardness of the composites containing different amounts of PPy was higher than that of the PPy and kaolinite components. The highest microhardness observed was 30.17 kg/mm² for the composite containing 9.6% PPy. The electrical resistance of the composites was monitored during heating–cooling cycles over the range 5–120 °C. The change in resistance with temperature was more repeatable for the composite than for PPy. The composites were characterized by Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), thermogravimetric analysis (TGA) and scanning electron microscopy (SEM). The humidity-sensing properties were also examined.     

Conductive polyaniline/poly(methyl methacrylate) films obtained by electropolymerization

Electrochemical polymerization of aniline, on a Pt foil electrode coated with poly(methyl methacrylate) (PMMA), produces a homogeneous, free-standing, flexible, and conductive polymer film. The conductivity of the films depends on the aniline content and reaches 0.1–0.2 S/cm for films having aniline content of 15% or more. The optimum thickness of precoated PMMA to obtain durable conducting films was found to be in the range of 10–15 μm. Cyclic voltammetric investigation revealed that aniline exhibits a similar electrochemical behavior on a PMMA coated platinum electrode similar to a bare Pt surface. The film gives a fast and reproducible response against ammonia gas within a concentration range of 1.0–0.01%. Scanning electron micrographs indicate that the films have a rough structure consisting of globular regions. © 1996 John Wiley & Sons, Inc.     

Potassium persulfate-mediated preparation of conducting polypyrrole/polyacrylonitrile composite fibers: Humidity and temperature-sensing properties

Conducting polypyrrole (PPy)/polyacrylonitrile (PAN) composite fibers were prepared by the polymerization of pyrrole in the presence of PAN fibers with potassium persulfate in an acidic aqueous solution. We obtained composite fibers containing concentrations of PPy as high as 1.14% and having surface resistivities as low as 0.6 kΩ/cm² by changing the polymerization parameters, including the temperature and concentrations of pyrrole and oxidant. The tensile strength of 10.02 N/m² and breaking elongation of 32.68% for the pure PAN fiber increased up to 10.45 N/m² and 33.23%, respectively, for the composite fiber containing 0.13% PPy. The change in the resistivity of the PPy/PAN composite fiber during heating–cooling cycles in the temperature range of +5 to 120°C was examined. Scanning electron microscopy and optical microscopy images of the composite fibers showed that the PPy coating was restricted to the surfaces of the PAN fibers. Surface resistivity measurements, Fourier transform infrared spectroscopy, and thermogravimetric analysis techniques were also used to characterize the composite fibers. © 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Preparation of nanocoatings in the presence of precipitated CaCO3 fillers by UV-curing

Various methods were employed to prepare precipitated calcium carbonate (PCC) particles. Particle size and morphology were dependent on reaction conditions as well as temperature, reagents and stirring, either mechanical or by ultrasound probe sonication. Sonication helped to reduce the size of CaCO₃ particles as well as the precipitation time. Sonication was also used to disperse PCC particles in the UV-curable formulations as well as for preparation of the PCC. Formulations containing precipitated calcium carbonates and ground calcium carbonates in various grades were cured by a Mini UV-Cure device. Mechanical and thermal properties of films were characterized with a Dynamic Mechanical Analyzer (DMA). SEM analysis was also used to determine the shape and the size of the PCCs. Sonication decreased the precipitation time of calcium carbonate at least four times more than that of conventional precipitation procedures and the dispersion of particles in the formulations increased to a great extent.     

Structural,thermal, and mechanical properties of silanized boron carbide doped epoxy nanocomposites

In the presented study, the structural, thermal, and mechanical properties of the nanocomposites were investigated by doping silanized hexagonal boron carbide (h-B₄C) nanoparticles in varying proportions (0.5%, 1%, 2%, 3%, 4%, and 5%) into the epoxy resin by weight. For this purpose, the surfaces of h-B₄C nanoparticles were silanized by using 3-(glycidyloxypropyl) trimethoxysilane (GPS) to improve adhesion between h-B₄C nanoparticles and epoxy matrix. Then, the silanized nanoparticles were added to the resin by ultrasonication and mechanical stirring techniques to produce nanocomposites. The bond structure differences of silanized B₄C nanoparticles (s-B₄C) and nanoparticle doped composites were investigated by using Fourier transform infrared spectroscopy. Scanning electron microscopy and energy dispersion X-ray spectroscopy (SEM-EDS) technique was used to examine the distribution of nanoparticles in the modified nanocomposites. Differential scanning calorimetry and thermogravimetric analysis techniques were used to determine the thermal properties of the neat and s-B₄C doped nanocomposites. The tensile test and dynamic mechanical analysis were performed to determine the mechanical properties. When the experimental results were examined, changes in the bonding structure of the s-B₄C nanoparticles doped nanocomposites and significant improvements in the mechanical and thermal properties were observed. The optimum doping ratio was determined as 2% by weight. At this doping ratio, the T_g, tensile strength and storage modulus increased approximately 18%, 35%, and 44% compared to the neat composite, respectively.     

Comparative Analysis of Coding and Non-Coding Features within Insect Tolerance Loci in Wheat with Their Homologs in Cereal Genomes

Food insecurity and malnutrition have reached critical levels with increased human population, climate fluctuations, water shortage; therefore, higher-yielding crops are in the spotlight of numerous studies. Abiotic factors affect the yield of staple food crops; among all, wheat stem sawfly (Cephus cinctus Norton) and orange wheat blossom midge (Sitodiplosis mosellana) are two of the most economically and agronomically harmful insect pests which cause yield loss in cereals, especially in wheat in North America. There is no effective strategy for suppressing this pest damage yet, and only the plants with intrinsic tolerance mechanisms such as solid stem phenotypes for WSS and antixenosis and/or antibiosis mechanisms for OWBM can limit damage. A major QTL and a causal gene for WSS resistance were previously identified in wheat, and 3 major QTLs and a causal gene for OWBM resistance. Here, we present a comparative analysis of coding and non-coding features of these loci of wheat across important cereal crops, barley, rye, oat, and rice. This research paves the way for our cloning and editing of additional WSS and OWBM tolerance gene(s), proteins, and metabolites.     

Hydrogen storage capability of carbon nanotube Be@C120

PM3 (RHF) type semiempirical quantum chemical calculations have been carried out on (nH₂+Be)@C₁₂₀ systems where C₁₂₀ is a capped tube and n15. The results indicate that all these systems are stable but endothermic in nature. (7H₂+Be)@C₁₂₀ system has the lowest heat of formation value.     

An Estimation of the Suspended Sediment Load Using Adaptive Network Based Fuzzy Inference System,Support Vector Machine and Artificial Neural Network Models

Sediment transport in streams and rivers takes two forms as suspended load and bed load. Suspended load comprises sand + silt + clay-sized particles that are held in suspension due to the turbulence and will only settle when the stream velocity decreases, such as when the streambed becomes flatter, or the streamflow into a pond or lake. The sources of the suspended sediments are the sediments transported from the river basin by runoff or wind and the eroded sediments of the river bed and banks. Suspended-sediment load is a key indicator for assessing the effect of land use changes, water quality studies and engineering practices in watercourses. Measuring suspended sediment in streams is real sampling and the collection process is both complex and expensive. In recent years, artificial intelligence methods have been used as a predictor for hydrological phenomenon namely to estimate the amount of suspended sediment. In this paper the abilities of Support Vector Machine (SVM), Artificial Neural Networks (ANNs) and Adaptive Network Based Fuzzy Inference System (ANFIS) models among the artificial intelligence methods have been investigated to estimate the suspended sediment load (SSL) in Ispir Bridge gauging station on Coruh River (station number: 2316). Coruh River is located in the northern east part of Turkey and it is one of the world”s the fastest, the deepest and the largest rivers of the Coruh Basin. In this study, in order to estimate the suspended sediment load, different combinations of the streamflow and the SSL were used as the model inputs. Its results accuracy was compared with the results of conventional correlation coefficient analysis between input and output variables and the best combination was identified. Finally, in order to predict SSL, the SVM, ANFIS and various ANNs models were used. The reliability of SVM, ANFIS and ANN models were determined based on performance criteria such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Efficiency Coefficient (EC) and Determination Coefficient (R²).