Operation of the quasi-optical gyrotron at harmonics of the gyrofrequency

This paper investigates the performance of a quasioptical gyrotron, when the electron beam interacts with the radiation fields at harmonics of the gyrofrequency. The nonlinear equations of motion are obtained in the slow-timescale. The expression for the linear gain is derived and the conditions for excitation are given (frequency threshold, optimal operating point, bean current and resonator quality thresholds). In the nonlinear regime, it is shown that maximum efficiencies comparable to those at the fundemental (50%) are possible, albeit at a prohitively high radiation field amplitude, while realistically feasible field amplitudes can give somewhat smaller, but nevertheless still high efficiencies (15%). Finally, the results are suplemented by empirical scaling laws, useful for experimental designs.     

Estimating reaction parameters in mechanism-enabled population balance models of nanoparticle size distributions: A Bayesian inverse problem approach

In order to quantitatively predict nano- as well as other particle-size distributions, one needs to have both a mathematical model and estimates of the parameters that appear in these models. Here, we show how one can use Bayesian inversion to obtain statistical estimates for the parameters that appear in recently derived mechanism-enabled population balance models (ME-PBM) of nanoparticle growth. The Bayesian approach addresses the question of “how well do we know our parameters, along with their uncertainties?.” The results reveal that Bayesian inversion statistical analysis on an example, prototype nanoparticle formation system allows one to estimate not just the most likely rate constants and other parameter values, but also their SDs, confidence intervals, and other statistical information. Moreover, knowing the reliability of the mechanistic model's parameters in turn helps inform one about the reliability of the proposed mechanism, as well as the reliability of its predictions. The paper can also be seen as a tutorial with the additional goal of achieving a “Gold Standard” Bayesian inversion ME-PBM benchmark that others can use as a control to check their own use of this methodology for other systems of interest throughout nature. Overall, the results provide strong support for the hypothesis that there is substantial value in using a Bayesian inversion methodology for parameter estimation in particle formation systems.     

Self-organization of polymer particles on hydrophobic solid substrates in aqueous media. II. Self-organization of cationic polymer particles on polymer films and wettability control with particle monolayers

Self-organization of cationic polymer particles through hydrophobic interaction on polymer films in aqueous system and characteristic properties of the resulting particle monolayers were investigated. Cationic polymer particles bearing quaternary ammonium groups on their surfaces effectively self-organized on polymer films. With an increase of the particle surface charge density, the surface coverage and average aggregate size (N _a) decreased. The surface coverage control was accomplished by tuning the ionic strength of the media. The wettability of polymer films for water was imparted by the formation of particle monolayers on them. Annealing of the particle monolayers resulted in the increase of the adhesive strength, while the wettability for water was lost. Further improvements of both wettability and adhesive strength of particle monolayers were achieved by the immobilization of silica colloids on the particle monolayers. This method would be effective for the hydrophilization of polymer films.     

ToF‐SIMS observation of PTFE surfaces modified by α‐particle irradiation

The surface structure of polytetrafluoroethylene (PTFE) upon α‐particle irradiation has been investigated at doses in the range of 1 × 10⁷ to 1 × 10¹¹ Rad and compared with the surface structure of the unirradiated polymer. Both neat and 25% fiberglass content PTFE were studied. The samples, maintained at nominal room temperature, were irradiated in vacuum by 5.5 MeV ⁴He²⁺ ions generated in a tandem accelerator beam line. Static time‐of‐flight SIMS (ToF‐SIMS) was employed to probe chemical changes at the surface as a function of the irradiation level. In general, the data are indicative of increased cross‐linking at α‐doses less than 1 × 10⁹ Rad, followed by increased fragmentation and unsaturation at α‐doses greater than 1 × 10⁹ Rad. Throughout the irradiation regime, scission is a constant factor promoting cross‐linking, branching, and unsaturation. However, at α‐doses greater than 1 × 10¹⁰ Rad, extreme structural degradation of the polymer becomes evident and is accompanied by conversion to oxygen‐functionalized and aliphatic compounds. Thus, for PTFE in an α‐particle field, an upper exposure limit of ～10¹⁰ Rad is essential for nominal retention of molecular structure. Finally, a quantitative relationship between α‐dose and characteristic fragment ion intensity is developed. Copyright © 2005 John Wiley & Sons, Ltd.     

Characterisation of River Po particles by sedimentation field-flow fractionation coupled to GFAAS and ICP-MS

A procedure for elemental composition determination of water-borne river particles (Po River) on both size-fractionated and unfractionated submicron particles (0.1–1 μm) by graphite furnace atomic absorption spectroscopy (GFAAS) and inductively coupled plasma-mass spectrometry (ICP-MS) is reported. Sample fractionation was performed using sedimentation field-flow fractionation (SdFFF). The distribution of relative mass vs. particle size was determined using UV detection. Fractions were collected over a narrow size range for scanning electron microscopy. With this combination of techniques the mass, elemental composition, and shape distributions can be obtained across the size spectrum of the sample.

The size distributions of the major elements (Al, Fe) were determined by coupling both GFAAS and ICP-MS techniques to the SdFFF. The procedure was validated using a reference clay sample. Satisfactory agreement was found between both the GFAAS and ICP-MS aluminium signal and the UV detector signal. Some discrepancies were observed in the Fe/Al ratios when comparing GFAAS and ICP-MS. Thus further investigation is in order to fully assess the role of SdFFF-ICP-MS and SdFFF-GFAAS techniques for elemental characterisation of aquatic colloids. Both GFAAS and ICP-MS signals unambiguously indicate a significantly higher Fe content in the lower size range, which is consistent with previous investigations.

Trace element levels in unfractionated Po River particles, determined by both GFAAS and ICP-MS, show good agreement. The high levels of Cu, Pb, Cr and Cd found associated with the colloidal particles underlines the significance of the environmental role played by the suspended matter in rivers in both highly industrialised and intensively cultivated areas.     

Three‐dimensional wave impact on a rigid structure using smoothed particle hydrodynamics

Navier–Stokes computations of a wave–structure interaction are performed with the aim of assessing the potential of smoothed particle hydrodynamics to accurately estimate impact loading time history. A three‐dimensional dam‐break flow with a rectangular column located downstream is considered. The net force and impulse exerted on the column is monitored throughout the simulation with the results correlating well with existing experimental data. Initial and boundary conditions and numerical parameters are varied and their effect on the column load investigated. The column load is found to be most sensitive to the choice of boundary treatment. Copyright © 2011 John Wiley & Sons, Ltd.     

Dust modelling using a combined CFD and discrete element formulation

The production and dispersal of airborne dust is an important issue in both environmental and industrial contexts. Dust pollution is a major environmental concern, and long exposure in occupational settings has been linked with numerous respiratory health issues. Industrial dust pollution can also present a significant explosion hazard, even in facilities with dust extraction systems. Computational models for dust generation and dispersal have, however, generally been formulated for specific geophysical applications and restricted to static, two‐dimensional, approaches. Here, we present a method for simulating dust production from a dynamic granular bed by using a three‐dimensional coupled discrete element method and Navier–Stokes computational model. Dust production is based on an energy formulation in which micro‐scale dust particles are assumed to overcome cohesion to macro‐scale grains. This model is used over the entire range of energies present within the system, from macro‐scale collisions to aerodynamic entrainment and bombardment of micro‐scale particles. The dust concentration is modelled as a scalar density field, which is advected and diffused through turbulence in the gas flow field. The model is tested against empirical predictions for two test cases, a slug of granular material dropped from a set height and air flow over a granular stockpile. Both give good agreement to the empirical relations, showing that the model can accurately predict the production and subsequent dispersal of dust from a dynamic granular bed. Copyright © 2012 John Wiley & Sons, Ltd.     

Synthesis and characterization of silica-supported Preyssler nano particles and its catalytic activity for photodegradation of methyl orange

Abstract

Heteropolyacid (H₁₄ [NaP₅W₃₀O₁₁₀])/SiO₂ nano particles were synthesized by a micro emulsion technique. The morphology and size of these nano particles were characterized using, transmission electron microscopy and X-ray diffraction. In a designed photo reactor, the photo degradation of methyl orange as common azo dye pollutants in the environment was selected as a test reaction to estimate the catalytic activity of the synthesized nano particles and found to be excellent.     

Application of DEM modified with enlarged particle model to simulation of bead motion in a bead mill

We applied the discrete element method （DEM） of simulation modified by an enlarged particle model to simulate bead motion in a large bead mill. The stainless-steel bead mill has inner diameter of 102 mm and mill length of 198 mm. The bead diameter and filling ratio were fixed respectively at 0.5 mm and 85%. The agitator rotational speed was changed from 1863 to 3261 rpm. The bead motion was monitored experimentally using a high-speed video camera through a transparent mill body. For the simulation, enlarged particle sizes were set as 3-6 mm in diameter. With the DEM modified by the enlarged particle model, the motion of enlarged particles in a mill was simulated.The velocity data of the simulated enlarged particles were compared with those obtained in the experiment. The simulated velocity of the enlarged particles depends on the virtual frictional coefficient in the DEM model. The optimized value of the virtual frictional coefficient can be determined by considering the accumulated mean value. Results show that the velocity of the enlarged particles simulated increases with an increase in the optimum virtual frictional coefficient, but the simulated velocity agrees well with that determined experimentally by optimizing the virtual frictional coefficient in the simulation. The computing time in the simulation decreases with increased particle size.