Prediction of ultrasonic wave velocity in particleboard and fiberboard

Ultrasonic wave velocities were determined at parallel and perpendicular to manufacturing direction and at the interval angles of 15° in clockwise and counterclockwise directions of particleboard and fiberboard. The experimental results were compared with the predicted values using some empirical formulae such as Hankinson and Jacoby equations. The results showed that the ultrasonic wave velocity were the highest in parallel direction in particleboard and fiberboard and decreases with increase of angle and the lowest values occurred in perpendicular direction. The predicted ultrasonic velocity using Hankinson and Jacoby equations are in close agreement with the measured values. Relationship between ultrasonic wave velocities and particles and fibers angle could be successfully presented by cubic and quadratic regression equations as well.     

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.     

Nanostructured polymer blends: Synthesis and structure

Nanostructured polymer blends prepared via anionic ring opening polymerizations of cyclic monomers in the presence of a pre-made polymer melt exhibit a number of special properties over traditional polymer blends and homopolymers. Here, we report on a simple and versatile method of in situ polymerization of macrocyclic carbonates in the presence of a maleic anhydride polypropylene (mPP) matrix and a surface-active compatibilizer (i.e. PC grafted onto a mPP backbone generated in situ) to yield a micro- and nanostructured polymer blends consisting of a polycarbonate (PC) minor phase, and a polypropylene (PP) major phase. By varying the processing conditions and concentration of the macrocyclic carbonate it was possible to reduce the size of the PC dispersions to an average minor diameter of 150 nm. NMR and TEM characterizations indicate that the PC dispersions do not influence crystal content in the PP phase. Overall, the results point to a simple strategy and versatile route to new polymeric materials with enhanced benefits.     

Axial-Field Electrical Machines - Design and Applications

Axial-field electrical machines offer an alternative to the conventional machines. In the axial-field machine, the airgap flux is axial in direction and the active current carrying conductors are radially positioned. This paper presents the design characteristics, special features, manufacturing aspects and potential applications for axial-field electrical machines. The experimental results from several prototypes, including d.c. machines, synchronous machines and single-phase machines are given. The special features of the axial-field machine, such as its planar and adjustable airgap, flat shape, ease of diversification, etc., enable axial-field machines to have distinct advantages over conventional machines in certain applications, especially in special-purpose applications.     

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.     

A Recursive Frequency Estimator Using Linear Prediction and a Kalman-Filter-Based Iterative Algorithm

This paper proposes a new Kalman-filter-based recursive frequency estimator for discrete-time multicomponent sinusoidal signals whose frequencies may be time-varying. The frequency estimator is based on the linear prediction approach and it employs the Kalman filter to track the linear prediction coefficients (LPCs) recursively. Frequencies of the sinusoids can then be computed using the estimated LPCs. Due to the coloredness of the linear prediction error, an iterative algorithm is employed to estimate the covariance matrix of the prediction error and the LPCs alternately in the Kalman filter in order to improve the tracking performance. Simulation results show that the proposed Kalman-filter-based iterative frequency estimator can achieve better tracking results than the conventional recursive least-squares-based estimators.