Preparation of gold nanoparticles (GNP) aqueous suspensions by a new method involving Tiron

A new method is proposed to produce gold nanoparticles (GNP) by in situ reduction of a gold salt dissolved in water. The reducing agent used is Tiron instead of the citrate anion most often mentioned in literature. The influence of various parameters has been investigated, such as the content of Tiron with respect to that of the precursor of gold HAuCl₄, or the initial pH of the solution after mixing of reactants. It is shown that Tiron also exerts a positive influence as a dispersant, which impedes agglomeration of gold nanoparticles. The typical average size of GNP synthesized in the present work is close to 7 nm.     

Fast internal dynamics in polyelectrolyte gels measured by dynamic light scattering

Summary Dynamic light scattering was used to investigate the dynamics of sodium poly(styrene sulfonate) and fully neutralized poly(acrylic acid) gels as a function of the degree of swelling and weight ratio of cross-linking agent. It was shown that the collective diffusion coefficient increases with increasing degree of swelling and that the diffusion coefficient shows stronger concentration dependence than predicted by scaling arguments. For gel samples measured at the swelling equilibrium, the diffusion coefficient increases with increasing gel concentration for both gel systems.     

Stimulation of negative magnetoresistance by an electric field and light in silicon doped with boron and manganese

It is experimentally ascertained that light stimulates the negative magnetoresistance observed in a high electric field in silicon doped with boron and manganese. The optimum conditions (the electric field, temperature, illumination, and resistivity of the material) for observation of the largest magnitude of negative magnetoresistance in (Si:B):Mn are determined. The dependence of the negative magnetoresistance on the concentration of compensating impurity is established.     

The stress intensity factors for a short crack partially penetrating an inclusion of arbitrary shape

Some approximate solutions for predicting the stress intensity factor of a short crack penetrating an inclusion of arbitrary shape have been developed under mode I and mode II loading conditions. The derivation of the fundamental formula is based on the transformation toughening theory. The transformation strains in the inclusion are induced by the crack-tip field and remotely applied stresses, and approximately evaluated by the Eshelby equivalent inclusion theory. As validated by detailed finite element (FE) analyses, the developed solutions have good accuracy for different inclusion shape and for a wide range of modulus ratio between inclusion and matrix material.     

An overview of nondestructive evaluation methods

ondestructive evaluation is described as nondestructive testing (NDT), nondestructive inspection (NDI), and nondestructive examination (NDE). The activities associated with the evaluation include testing, inspection, and examination and primarily involve looking at (or through) and/or measuring some characteristic of an object. Frequently there is a desire to determine some characteristic of the object or to determine whether the object contains irregularities, discontinuities, or flaws. These examinations, inspections, or tests are used to determine the physical soundness of a material without impairing its usefulness. Nondestructive evaluation is a powerful tool that can help assure safety, quality, and reliability; increase productivity; decrease liability; protect the environment; and save money. In this article, nondestructive evaluation is represented by the acronym NDE.     

Influence of the preparation conditions on the size and morphology of nanocrystalline lanthanum orthoferrite

Nanocrystalline LaFeO₃ is prepared by the dehydration of coprecipitated lanthanum and iron(III) hydroxides. It is shown that the behavior of the samples during heating and the size distribution of LaFeO₃ nanocrystals can be considerably different depending on the scheme used for coprecipitation of lanthanum and iron hydroxides; independently of the method employed for coprecipitation of the initial compounds, sintering of the samples at 950°C leads to the formation of lanthanum orthoferrite crystals up to 100 nm in size.     

Modeling tool wear in end-milling using enhanced GMDH learning networks

This paper presents an enhanced approach to predictive modeling for determining tool-wear in end-milling operations based on enhanced-group method of data handling (e-GMDH). Using milling input parameters (speed, feed, and depth-of-cut) and response (tool wear), the data for the model is partitioned into training and testing datasets, and the training dataset is used to realize a predictive model that is a function of the input parameters and the coefficients determined. In our approach, we first present a methodology for modeling, and then develop predictive model(s) of the problem being solved in the form of second-order equations based on the input data and coefficients realized. This approach leads to some generalization because it becomes possible to predict not only the test data obtained during experimentation, but other test data outside the experimental results can also be used. Moreover, this approach makes it easy to present the realized solution in a form that can be further optimized for the input parameters using some optimization techniques. The results realized using our e-GMDH method are promising, and the comparative study presented shows that the e-GMDH outperforms polynomial neural network (PNN); moreover, it is more flexible than the conventional GMDH, which tends to produce nonlinear solutions even for simple problems. In the investigation, the extended particle swarm optimization (PSO) technique was applied to obtain the optimal parameters. Consequently, the modeling approach is extremely useful in realizing a computer-aided process-planning system in an advanced manufacturing environment.