Characterization of an extrapolation chamber for low-energy X-rays: Experimental and Monte Carlo preliminary results

The extrapolation chamber is a parallel-plate ionization chamber that allows variation of its air-cavity volume. In this work, an experimental study and MCNP-4C Monte Carlo code simulations of an ionization chamber designed and constructed at the Calibration Laboratory at IFEN to be used as a secondary dosimetry standard for low-energy X-rays are reported. The results obtained were within the international recommendations, and the simulations showed that the components of the extrapolation chamber may influence its response up to 11.0%. (C) 2011 Elsevier Ltd. All rights reserved.

Optimization of x-ray spectra in digital mammography through Monte Carlo simulations

In this work, a Monte Carlo code was used to investigate the performance of different x-ray spectra in digital mammography, through a figure of merit (FOM), defined as FOM = CNR2/(D) over bar (g), with CNR being the contrast-to-noise ratio in image and (D) over bar (g) being the average glandular dose. The FOM was studied for breasts with different thicknesses t (2 cm <= t <= 8 cm) and glandular contents (25%, 50% and 75% glandularity). The anode/filter combinations evaluated were those traditionally employed in mammography (Mo/Mo, Mo/Rh, Rh/Rh), and a W anode combined with Al or K-edge filters (Zr, Mo, Rh, Pd, Ag, Cd, Sn), for tube potentials between 22 and 34 kVp. Results show that the W anode combined with K-edge filters provides higher values of FOM for all breast thicknesses investigated. Nevertheless, the most suitable filter and tube potential depend on the breast thickness, and for t >= 6 cm, they also depend on breast glandularity. Particularly for thick and dense breasts, a W anode combined with K-edge filters can greatly improve the digital technique, with the values of FOM up to 200% greater than that obtained with the anode/filter combinations and tube potentials traditionally employed in mammography. For breasts with t < 4 cm, a general good performance was obtained with the W anode combined with 60 mu m of the Mo filter at 24-25 kVp, while 60 mu m of the Pd filter provided a general good performance at 24-26 kVp for t = 4 cm, and at 28-30 and 29-31 kVp for t = 6 and 8 cm, respectively.

Quantum Monte Carlo study of small aluminum clusters Al-n (n=2-13)

Using fixed node diffusion quantum Monte Carlo (FN-DMC) simulations and density functional theory (DFT) within the generalized gradient approximations, we calculate the total energies of the relaxed and unrelaxed neutral, cationic, and anionic aluminum clusters, Al-n (n = 1-13). From the obtained total energies, we extract the ionization potential and electron detachment energy and compare with previous theoretical and experimental results. Our results for the electronic properties from both the FN-DMC and DFT calculations are in reasonably good agreement with the available experimental data. A comparison between the FN-DMC and DFT results reveals that their differences are a few tenths of electron volt for both the ionization potential and the electron detachment energy. We also observe two distinct behaviors in the electron correlation contribution to the total energies from smaller to larger clusters, which could be assigned to the structural transition of the clusters from planar to three-dimensional occurring at n = 4 to 5.

Generalized Metropolis dynamics with a generalized master equation: An approach for time-independent and time-dependent Monte Carlo simulations of generalized spin systems

The extension of Boltzmann-Gibbs thermostatistics, proposed by Tsallis, introduces an additional parameter q to the inverse temperature beta. Here, we show that a previously introduced generalized Metropolis dynamics to evolve spin models is not local and does not obey the detailed energy balance. In this dynamics, locality is only retrieved for q = 1, which corresponds to the standard Metropolis algorithm. Nonlocality implies very time-consuming computer calculations, since the energy of the whole system must be reevaluated when a single spin is flipped. To circumvent this costly calculation, we propose a generalized master equation, which gives rise to a local generalized Metropolis dynamics that obeys the detailed energy balance. To compare the different critical values obtained with other generalized dynamics, we perform Monte Carlo simulations in equilibrium for the Ising model. By using short-time nonequilibrium numerical simulations, we also calculate for this model the critical temperature and the static and dynamical critical exponents as functions of q. Even for q not equal 1, we show that suitable time-evolving power laws can be found for each initial condition. Our numerical experiments corroborate the literature results when we use nonlocal dynamics, showing that short-time parameter determination works also in this case. However, the dynamics governed by the new master equation leads to different results for critical temperatures and also the critical exponents affecting universality classes. We further propose a simple algorithm to optimize modeling the time evolution with a power law, considering in a log-log plot two successive refinements.

Monte Carlo Semi-Empirical Model for Si(Li) X-Ray Detector: Differences between Nominal and Fitted Parameters.

A detailed characterization of a X-ray Si(Li) detector was performed to obtain the energy dependence of efficiency in the photon energy range of 6.4 - 59.5 keV. which was measured and reproduced by Monte Carlo (MC) simulations. Significant discrepancies between MC and experimental values were found when lhe manufacturer parameters of lhe detector were used in lhe simulation. A complete Computerized Tomagraphy (CT) detector scan allowed to find the correct crystal dimensions and position inside the capsule. The computed efficiencies with the resulting detector model differed with the measured values no more than 10% in most of the energy range.

Response functions of Si(Li), SDD and CdTe detectors for mammographic x-ray spectroscopy

In this work, the energy response functions of Si(Li), SDD and CdTe detectors were studied in the mammographic energy range through Monte Carlo simulation. The code was modified to take into account carrier transport effects and the finite detector energy resolution. The results obtained show that all detectors exhibit good energy response at low energies. The most important corrections for each detector were discussed, and the corrected mammographic x-ray spectra obtained with each one were compared. Results showed that all detectors provided similar corrected spectra, and, therefore, they could be used to accurate mammographic x-ray spectroscopy. Nevertheless, the SDD is particularly suitable for clinic mammographic x-ray spectroscopy due to the easier correction procedure and portability. (C) 2011 Elsevier Ltd. All rights reserved.

Irreversibility by competition on a Glauber-Ising model by means of the entropy production.

An out of equilibrium Ising model subjected to an irreversible dynamics is analyzed by means of a stochastic dynamics, on a effort that aims to understand the observed critical behavior as consequence of the intrinsic microscopic characteristics. The study focus on the kinetic phase transitions that take place by assuming a lattice model with inversion symmetry and under the influence of two competing Glauber dynamics, intended to describe the stationary states using the entropy production, which characterize the system behavior and clarifies its reversibility conditions. Thus, it is considered a square lattice formed by two sublattices interconnected, each one of which is in contact with a heat bath at different temperature from the other. Analytical and numerical treatments are faced, using mean-field approximations and Monte Carlo simulations. For the one dimensional model exact results for the entropy production were obtained, though in this case the phase transition that takes place in the two dimensional counterpart is not observed, fact which is in accordance with the behavior shared by lattice models presenting inversion symmetry. Results found for the stationary state show a critical behavior of the same class as the equilibrium Ising model with a phase transition of the second order, which is evidenced by a divergence with an exponent µ ¼ 0:003 of the entropy production derivative.

Surface modification by metal ion implantation forming metallic nanoparticles in insulating matrix.

There is special interest in the incorporation of metallic nanoparticles in a surrounding dielectric matrix for obtaining composites with desirable characteristics such as for surface plasmon resonance, which can be used in photonics and sensing, and controlled surface electrical conductivity. We investigated nanocomposites produced through metallic ion implantation in insulating substrate, where the implanted metal self-assembles into nanoparticles. During the implantation, the excess of metal atom concentration above the solubility limit leads to nucleation and growth of metal nanoparticles, driven by the temperature and temperature gradients within the implanted sample including the beam-induced thermal characteristics. The nanoparticles nucleate near the maximum of the implantation depth profile (projected range), that can be estimated by computer simulation using the TRIDYN. This is a Monte Carlo simulation program based on the TRIM (Transport and Range of Ions in Matter) code that takes into account compositional changes in the substrate due to two factors: previously implanted dopant atoms, and sputtering of the substrate surface. Our study suggests that the nanoparticles form a bidimentional array buried few nanometers below the substrate surface. More specifically we have studied Au/PMMA (polymethylmethacrylate), Pt/PMMA, Ti/alumina and Au/alumina systems. Transmission electron microscopy of the implanted samples showed the metallic nanoparticles formed in the insulating matrix. The nanocomposites were characterized by measuring the resistivity of the composite layer as function of the dose implanted. These experimental results were compared with a model based on percolation theory, in which electron transport through the composite is explained by conduction through a random resistor network formed by the metallic nanoparticles. Excellent agreement was found between the experimental results and the predictions of the theory. It was possible to conclude, in all cases, that the conductivity process is due only to percolation (when the conducting elements are in geometric contact) and that the contribution from tunneling conduction is negligible.