Size Control in the Nanoprecipitation Process of Stable Iodine (127I) Using Microchannel Reactor—Optimization by Artificial Neural Networks

In this study, nanosuspension of stable iodine (127I) was prepared by nanoprecipitation process in microfluidic devices. Then, size of particles was optimized using artificial neural networks (ANNs) modeling. The size of prepared particles was evaluated by dynamic light scattering. The response surfaces obtained from ANNs model illustrated the determining effect of input variables (solvent and antisolvent flow rate, surfactant concentration, and solvent temperature) on the output variable (nanoparticle size). Comparing the 3D graphs revealed that solvent and antisolvent flow rate had reverse relation with size of nanoparticles. Also, those graphs indicated that the solvent temperature at low values had an indirect relation with size of stable iodine (127I) nanoparticles, while at the high values, a direct relation was observed. In addition, it was found that the effect of surfactant concentration on particle size in the nanosuspension of stable iodine (127I) was depended on the solvent temperature. © 2015, American Association of Pharmaceutical Scientists

Variation of mass in primordial nucleosynthesis as a test of Induced Matter Brane Gravity

The variation of mass in induced matter theory using Ceroch-Stewart-Walter perturbations of submanifolds [1] is redefined. It is shown that the deviation of primordial Helium production due to a variation on the difference between the rest mass of the nucleus is in agrement with induced matter brane gravity.Comment: 11 pages, to appear in PL

Effect of Bio Ethanol and Diesel Blend on Small Diesel Engine Vibration

The use of Bio-ethanol as an alternative diesel engine fuel is rapidly increasing. Bio-ethanol is mixed with diesel fuel at different ratios and used in CI and SI engines. Since vibrations have direct effects on users and engine components, for this reason analysis of vibration resulting from combustion in CI engines is very important. In this study, evaluation of vibration was performed for both diesel and ethanol blends. Commercial diesel fuel (D100), E2 (2% ethanol and 98% diesel fuel), E5, E10, E15 and E20 were used in a two-wheel MITSUBISHI tractor. The engine was tested in 1200, 1600, 2000 and 2400 rpm for all fuel blends, and also the effect of load was investigated for D100 and E10. Results showed that vibration is significantly affected by fuel blend. It was observed that E10 had the lowest vibration while E20 had the highest value. It was also observed that vibration increased as engine speed increased for all fuel blends. It was found that both axial and lateral vibrations affected significantly by load. The lateral vibrations decreased continuously with load rise , but the axial vibrations increased initially but started to follow a reverse trend

Statistical optimization, soft computing prediction, mechanistic and empirical evaluation for fundamental appraisal of copper, lead and malachite green adsorption

This paper describes an efficient and low cost material for treatment of Cu2+, Pb2+ and malachite green from aquatic environments. Aerated Autoclave Concrete (AAC) was used as a low cost bed and modified by chitosan to synthesize of AAC?CH composite. Then, it was analyzed by the Energy Dispersive X-ray spectroscopy (EDX), X-Ray Fluorescence (XRF), Field Emission Scanning Electron Microscopy (FE-SEM) and Fourier Transform Infrared spectrophotometry (FT-IR) analysis. The key factors influencing on the removal percentage among each run including, sample's pH, amounts of adsorbent and contact time were optimized by the Central Composite Design in Response Surface Methodology (CCD-RSM). Based on the obtained results, the optimum conditions for the removal of both Cu2+ and Pb2+ are pH 5.8, amounts of adsorbent: 14 mg and 58 min contact time. Also, for MG, its maximum removal percentage obtained at pH 9.7, 13 mg adsorbent and 55 min removal time. In addition, the variations of adsorptive behaviors were scrutinized by Adaptive Network-based Fuzzy Inference System (ANFIS) based on Sugeno model with focusing on removal percentage predictions. Also, to evaluate the adsorption mechanism, Dubinin?Radushkevich (D-R), Langmuir, Temkin, Freundlich (two parameter equations) and Sips, Khan and Toth isotherms (Three parameter equations) were appraised and the outcomes demonstrate that the adsorptive reaction of Pb2+, Cu2+ and MG governed by the Freundlich isotherm with the maximum adsorption capacities of 78.12, 56.82 and 833.33 mg g?1, correspondingly. Likewise, outputs of the D-R and Temkin isotherms show that the physiosorption process is the main interaction of analytes with AAC?CH composite. The consequences of the kinetic modeling illustrated that the adsorptive reaction of Cu2+, Pb2+ and MG followed by the pseudo second order adsorption kinetic. The geometry kinetic computing depicted that the adsorption/desorption rates don't have any interfering during reaction process. The advantages such as high efficiency, low cost, reusability and green aspect, make AAC?CH composite as a high performance adsorbent for decontamination of Pb2+, Cu2+ and MG from water resources.Scopu