Microstructural evolution and mechanical characteristics in nanocrystalline nickel with a bimodal grain-size distribution

An attractive microstructural possibility for enhancing the ductility of high-strength nanocrystals is to develop a bimodal grain-size distribution, in which the fine grains provide strength, and the coarser grains enable strain hardening. Annealing of nanocrystalline Ni over a range of temperatures and times led to microstructures with varying volume fractions of coarse grains and a change in texture. Tensile tests revealed a drastic reduction in ductility with increasing volume fraction of coarse grains. The reduction in ductility may be related to the segregation of sulphur to grain boundaries.

The effect of particle size distribution on TG

The effect of a particle size distribution on the fractional reaction has been analysed. The analysis shows that for non-isothermal TG the activation energy and frequency factor evaluated from the fractional reaction by conventional method depend on the particle size distribution, and this may lead to a kinetic compensating effect. Particle size distribution may also lead to an erroneous conclusion about the change in the mechanism of reaction.

A broad pore size distribution mesoporous SnO2 as anode for lithium-ion batteries

We demonstrate here that mesoporous tin dioxide (abbreviated M-SnO2) with a broad pore size distribution can be a prospective anode in lithium-ion batteries. M-SnO2 with pore size ranging between 2 and 7.5 nm was synthesized using a hydrothermal procedure involving two different surfactants of slightly different sizes, and characterized. The irreversible capacity loss that occurs during the first discharge and charge cycle is 890 mAh g(-1), which is smaller than the 1,010-mAh g(-1) loss recorded for mesoporous SnO2 (abbreviated S-SnO2) synthesized using a single surfactant. After 50 cycles, the discharge capacity of M-SnO2 (504 mAh g(-1)) is higher than that of S-SnO2 (401 mAh g(-1)) and solid nanoparticles of SnO2 (abbreviated nano-SnO2 < 4 mAh g(-1)) and nano-SnO2. Transmission electron microscopy revealed higher disorder in the pore arrangement in M-SnO2. This, in turn imparts lower stiffness to M-SnO2 (elastic modulus, E (R) a parts per thousand aEuro parts per thousand 14.5 GPa) vis-a-vis S-SnO2 (E (R) a parts per thousand aEuro parts per thousand 20.5 GPa), as obtained using the nanoindentation technique. Thus, the superior battery performance of M-SnO2 is attributed to its intrinsic material mechanical property. The fluidity of the internal microstructure of M-SnO2 resulted in a lower degree of aggregation of Sn particles compared to S-SnO2 and nano-SnO2 structural stabilization and long-term cyclability.

Modeling of Bubble-Size Distribution in Water and Freon Co-Blown Free Rise Polyurethane Foams

A model has been developed to simulate the foam characteristics obtained, when chemical (water) and physical (Freon) blowing agents are used together for the formation of polyurethane foams. The model considers the rate of reaction, the consequent rise in temperature of the reaction mixture, nucleation of bubbles, and mass transfer of CO2 and Freon to them till the time of gelation. The model is able to explain the experimental results available in literature. It further predicts that the nucleation period gets reduced with increase in water (at constant Freon content), whereas with increase in Freon (at constant water) concentration nucleation period decreases marginally leading to narrower bubble-size distribution. By the use of uniform sized nuclei added initially, the model predicts that the bubble-size distribution can be made independent of the rate of homogeneous nucleation and can, thus, offer an extra parameter for its control. (C) 2014 Wiley Periodicals, Inc.

Strategy for Obtaining Bimodal Bubble Size Distribution in Water Blown Polyurethane Foams

Polyurethane foams with multimodal cell distribution exhibit superior mechanical and thermal properties. A technique for generating bimodal bubble size distribution exists in the literature, but it uses supercritical conditions. In the present work, an alternative based on milder operating conditions is proposed. It is a modification of reaction injection molding (RIM), using reactants already seeded with bubbles. The number density of the seeds determines if two nucleating events can occur. A bimodal bubble size distribution is obtained when this happens A mathematical model is used to test this hypothesis by simulating water blown free rise polyurethane foams. The effects of initial concentration of bubbles, temperature of the reactants, and the weight fraction of water are studied. The study reveals that for certain concentrations of initial number of bubbles, when initial temperature and weight fraction of water are high, it is possible to obtain a second nucleation event, leading to bimodal bubble size distribution.

On the breakdown of the most probable distribution for mayer clusters

We present an analysis of the breakdown of the most probable approximation to the Mayer cluster size distribution for clusters of size comparable to the size of the system. This failure is illustrated by considering an ideal Bose gas for which exact volume dependent reducible cluster integrals are available.

Influence of surface chemistry of mesoporous alumina with wide pore distribution on controlled drug release

The crucial role of the drug carrier surface chemical moeities on the uptake and in vitro release of drug is discussed here in a systematic manner. Mesoporous alumina with a wide pore size distribution (2-7 nm) functionalized with various hydrophilic and hydrophobic surface chemical groups was employed as the carrier for delivery of the model drug ibuprofen. Surface functionalization with hydrophobic groups resulted in low degree of drug loading (approximately 20%) and fast rate of release (85% over a period of 5 h) whereas hydrophilic groups resulted in a significantly higher drug payloads (21%-45%) and slower rate of release (12%-40% over a period of 5 h). Depending on the chemical moiety, the diffusion controlled (proportional to time(-0.5)) drug release was additionally observed to be dependent on the mode of arrangement of the functional groups on the alumina surface as well as on the pore characteristics of the matrix. For all mesoporous alumina systems the drug dosages were far lower than the maximum recommended therapeutic dosages (MRTD) for oral delivery. We envisage that the present study would aid in the design of delivery systems capable of sustained release of multiple drugs.

Room-temperature synthesis of gold nanoparticles - Size-control by slow addition

We report a simple and rapid process for the room-temperature synthesis of gold nanoparticles using tannic acid, a green reagent, as both the reducing and stabilising agent. We systematically investigated the effect of pH on the size distribution of nanoparticles synthesized. Based on induction time and zeta- potential measurements, we show that particle size distribution is controlled by a fine balance between the rates of reduction (determined by the initial pH of reactants) and coalescence (determined by the pH of the reaction mixture) in the initial period of growth. This insight led to the optimal batch process for size-controlled synthesis of 2-10 nm gold nanoparticles - slow addition (within 10 minutes) of chloroauric acid into tannic acid.

Effects of surface treatments and size of fly ash particles on the compressive properties of epoxy based particulate composites

Particulate reinforcements for polymers are selected with dual objective of improving composite properties and save on the total cost of the system. In the present study fly ash, an industrial waste with good properties is used as filler in epoxy and the compressive properties of such composites are studied. Particle surfaces are treated chemically using a silane-coupling agent to improve the compatibility with the matrix. The compressive properties of these are compared with those made of untreated fly ash particulates. Furthermore properties of fly ash composites with two different average particle sizes are first compared between themselves and then with those made using the as-received bimodal nature of particle size distribution. Microscopic observations of compression tested samples revealed a better adherence of the particles with the matrix in case of treated particles and regards the size effect the composites with lower average particle size showed improved strength at higher filler contents. Experimental values of strengths and modulii are compared with some of the theoretical models for composite properties. (C) 2002 Kluwer Academic Publishers.

Model for Predicting the Mean Drop Size in Effervescent Sprays

This paper is focused on the development of a model for predicting the mean drop size in effervescent sprays. A combinatorial approach is followed in this modeling scheme, which is based on energy and entropy principles. The model is implemented in cascade in order to take primary breakup (due to exploding gas bubbles) and secondary breakup (due to shearing action of surrounding medium) into account. The approach in this methodology is to obtain the most probable drop size distribution by maximizing the entropy while satisfying the constraints of mass and energy balance. The comparison of the model predictions with the past experimental data is presented for validation. A careful experimental study is conducted over a wide range of gas-to-liquid ratios, which shows a good agreement with the model predictions: It is observed that the model gives accurate results in bubbly and annular flow regimes. However, discrepancies are observed in the transitional slug flow regime of the atomizer.

Size-mediated cytotoxicity of nanocrystalline titanium dioxide, pure and zinc-doped hydroxyapatite nanoparticles in human hepatoma cells

Nanoparticles are highly used in biological applications including nanomedicine. In this present study, the interaction of HepG2 hepatocellular carcinoma cells (HCC) with hydroxyapatite (HAp), zinc-doped hydroxyapatite, and titanium dioxide (TiO2) nanoparticles were investigated. Hydroxyapatite, zinc-doped hydroxyapatite and titanium dioxide nanoparticles were prepared by wet precipitation method. They were subjected to isochronal annealing at different temperatures. Particle morphology and size distribution were characterized by X-ray diffraction and transmission electron microscope. The nanoparticles were co-cultured with HepG2 cells. MTT assay was employed to evaluate the proliferation of tumor cells. The DNA damaging effect of HAp, Zn-doped HAp, and TiO2 nanoparticles in human hepatoma cells (HepG2) were evaluated using DNA fragmentation studies. The results showed that in HepG2 cells, the anti-tumor activity strongly depend on the size of nanoparticles in HCC cells. Cell cycle arrest analysis for HAp, zinc-doped HAp, and TiO2 nanoparticles revealed the influence of HAp, zinc-doped HAp, and titanium dioxide nanoparticles on the apoptosis of HepG2 cells. The results imply that the novel nano nature effect plays an important role in the biomedicinal application of nanoparticles.

Effect of high gold salt concentrations on the size and polydispersity of gold nanoparticles prepared by an extended Turkevich-Frens method

The Turkevich-Frens synthesis starting conditions are expanded, ranging the gold salt concentrations up to 2 mM and citrate/gold(III) molar ratios up to 18:1. For each concentration of the initial gold salt solution, the citrate/gold(III) molar ratios are systematically varied from 2:1 to 18:1 and both the size and size distribution of the resulting gold nanoparticles are compared. This study reveals a different nanoparticle size evolution for gold salt solutions ranging below 0.8 mM compared to the case of gold salt solutions above 0.8 mM. In the case of Au3+]<0.8 mM, both the size and size distribution vary substantially with the citrate/gold(III) ratio, both displaying plateaux that evolve inversely to Au3+] at larger ratios. Conversely, for Au3+]>= 0.8 mM, the size and size distribution of the synthesized gold nanoparticles continuously rise as the citrate/gold(III) ratio is increased. A starting gold salt concentration of 0.6 mM leads to the formation of the most monodisperse gold nanoparticles (polydispersity index<0.1) for a wide range of citrate/gold(III) molar ratios (from 4:1 to 18:1). Via a model for the formation of gold nanoparticles by the citrate method, the experimental trends in size could be qualitatively predicted:the simulations showed that the destabilizing effect of increased electrolyte concentration at high initial Au3+] is compensated by a slight increase in zeta potential of gold nanoparticles to produce concentrated dispersion of gold nanoparticles of small sizes.

Evidence of clustering in an aqueous electrolyte solution: a small-angle X-ray scattering study

The work reported hen was motivated by a desire to verify the existence of structure - specifically MP-rich clusters induced by sodium bromide (NaBr) in the ternary liquid mixture 3-methylpyridine (Mf) + water(W) + NaBr. We present small-angle X-ray scattering (SAXS) measurements in this mixture. These measurements were obtained at room temperature (similar to 298 K) in the one-phase region (below the relevant lower consolute points, T(L)s) at different values of X (i.e., X = 0.02 - 0.17), where X is the weight fraction of NaBr in the mixture. Cluster-size distribution, estimated on the assumption that the clusters are spherical, shows systematic behaviour in that the peak of the distribution shifts rewards larger values of cluster radius as X increases. The largest spatial extent of the clusters (similar to 4.5 nm) is seen at X = 0.17. Data analysis assuming arbitrary shapes and sizes of clusters gives a limiting value of cluster size (- 4.5 nm) that is not very sensitive to X. It is suggested that the cluster size determined may not be the same as the usual critical-point fluctuations far removed from the critical point (T-L). The influence of the additional length scale due to clustering is discussed from the standpoint of crossover from Ising to mean-field critical behaviour, when moving away from the T-L.

Precipitation In Small Systems--II. Mean Field Equations More Effective Than Population Balance

Part I (Manjunath et al., 1994, Chem. Engng Sci. 49, 1451-1463) of this paper showed that the random particle numbers and size distributions in precipitation processes in very small drops obtained by stochastic simulation techniques deviate substantially from the predictions of conventional population balance. The foregoing problem is considered in this paper in terms of a mean field approximation obtained by applying a first-order closure to an unclosed set of mean field equations presented in Part I. The mean field approximation consists of two mutually coupled partial differential equations featuring (i) the probability distribution for residual supersaturation and (ii) the mean number density of particles for each size and supersaturation from which all average properties and fluctuations can be calculated. The mean field equations have been solved by finite difference methods for (i) crystallization and (ii) precipitation of a metal hydroxide both occurring in a single drop of specified initial supersaturation. The results for the average number of particles, average residual supersaturation, the average size distribution, and fluctuations about the average values have been compared with those obtained by stochastic simulation techniques and by population balance. This comparison shows that the mean field predictions are substantially superior to those of population balance as judged by the close proximity of results from the former to those from stochastic simulations. The agreement is excellent for broad initial supersaturations at short times but deteriorates progressively at larger times. For steep initial supersaturation distributions, predictions of the mean field theory are not satisfactory thus calling for higher-order approximations. The merit of the mean field approximation over stochastic simulation lies in its potential to reduce expensive computation times involved in simulation. More effective computational techniques could not only enhance this advantage of the mean field approximation but also make it possible to use higher-order approximations eliminating the constraints under which the stochastic dynamics of the process can be predicted accurately.