A Biased Resistor Network Model for Electromigration Failure and Related Phenomena in Metallic Lines

Electromigration phenomena in metallic lines are studied by using a biased resistor network model. The void formation induced by the electron wind is simulated by a stochastic process of resistor breaking, while the growth of mechanical stress inside the line is described by an antagonist process of recovery of the broken resistors. The model accounts for the existence of temperature gradients due to current crowding and Joule heating. Alloying effects are also accounted for. Monte Carlo simulations allow the study within a unified theoretical framework of a variety of relevant features related to the electromigration. The predictions of the model are in excellent agreement with the experiments and in particular with the degradation towards electrical breakdown of stressed Al-Cu thin metallic lines. Detailed investigations refer to the damage pattern, the distribution of the times to failure (TTFs), the generalized Black's law, the time evolution of the resistance, including the early-stage change due to alloying effects and the electromigration saturation appearing at low current densities or for short line lengths. The dependence of the TTFs on the length and width of the metallic line is also well reproduced. Finally, the model successfully describes the resistance noise properties under steady state conditions.Comment: 39 pages + 17 figure

Linear and nonlinear post-processing of numerically forecasted surface temperature

International audienceIn this paper we test different approaches to the statistical post-processing of gridded numerical surface air temperatures (provided by the European Centre for Medium-Range Weather Forecasts) onto the temperature measured at surface weather stations located in the Italian region of Puglia. We consider simple post-processing techniques, like correction for altitude, linear regression from different input parameters and Kalman filtering, as well as a neural network training procedure, stabilised (i.e. driven into the absolute minimum of the error function over the learning set) by means of a Simulated Annealing method. A comparative analysis of the results shows that the performance with neural networks is the best. It is encouraging for systematic use in meteorological forecast-analysis service operations

Thermal Transient Measurements of an Ultra-Low-Power MOX Sensor

This paper describes a system for the simultaneous dynamic control and thermal characterization of the heating of an Ultra Low Power (ULP) micromachined sensor. A Pulse Width Modulated (PWM) powering system has been realized using a microcontroller to characterize the thermal behavior of a device. Objectives of the research were to analyze the relation between the time period and duty cycle of the PWM signal and the operating temperature of such ULP micromachined systems, to observe the thermal time constants of the device during the heating phase and to measure the total thermal conductance. Constant target heater resistance experiments highlighted that an approximately constant heater temperature at regime can only be obtained if the time period of the heating signal is smaller than 50 s. Constant power experiments show quantitatively a thermal time constant that decreases during heating in a range from 2.3 ms to 2 ms as a function of an increasing temperature rise between the ambient and the operating temperature. Moreover, we calculated the total thermal conductance. Finally, repeatability of experimental results was assessed by guaranteeing the standard deviation of the controlled temperature which was within C in worst case conditions

From moths to caterpillars: Ideal conditions for Galleria mellonella rearing for in vivo microbiological studies.

ABSTRACT Galleria mellonella is a well-accepted insect model for the study of pathogen-host interactions and antimicrobial compounds. The main advantages of this model include the low cost of maintenance, the fast life cycle, the possibility of using a large number of caterpillars and the innate immune system, which is evolutionarily conserved relative to mammals. Because of these advantages, different research groups have been working to implement the rearing of G. mellonella in laboratory conditions. This protocol describes our experience in the rearing of G. mellonella caterpillars for experimental infection models and the influence of different artificial diets on developmental and physiological parameters. Here, we suggest a diet composition that benefits the life cycle of G. mellonella by accelerating the larval phase length and increasing the caterpillar weight. This diet also stimulated the immune system of G. mellonella by increasing the hemolymph volume and hemocyte concentration. In addition, our rearing protocol generated caterpillars that are more resistant to infection by Staphylococcus aureus, Escherichia coli and Candida albicans. A standard G. mellonella rearing protocol is fundamental to minimize external influences on the results, and this simple and easy protocol can support researchers starting to rear G. mellonella

Resistance and Resistance Fluctuations in Random Resistor Networks Under Biased Percolation

We consider a two-dimensional random resistor network (RRN) in the presence of two competing biased percolations consisting of the breaking and recovering of elementary resistors. These two processes are driven by the joint effects of an electrical bias and of the heat exchange with a thermal bath. The electrical bias is set up by applying a constant voltage or, alternatively, a constant current. Monte Carlo simulations are performed to analyze the network evolution in the full range of bias values. Depending on the bias strength, electrical failure or steady state are achieved. Here we investigate the steady-state of the RRN focusing on the properties of the non-Ohmic regime. In constant voltage conditions, a scaling relation is found between $/_0$ and $V/V_0$, where $$ is the average network resistance, $_0$ the linear regime resistance and $V_0$ the threshold value for the onset of nonlinearity. A similar relation is found in constant current conditions. The relative variance of resistance fluctuations also exhibits a strong nonlinearity whose properties are investigated. The power spectral density of resistance fluctuations presents a Lorentzian spectrum and the amplitude of fluctuations shows a significant non-Gaussian behavior in the pre-breakdown region. These results compare well with electrical breakdown measurements in thin films of composites and of other conducting materials.Comment: 15 figures, 23 page

Impact of Resistance to Fluconazole on Virulence and Morphological Aspects of Cryptococcus neoformans and Cryptococcus gattii Isolates

Cryptococcus spp. are responsible for around one million cases of meningitis every year. Fluconazole (FLU) is commonly used in the treatment of cryptococcosis, mainly in immunocompromised patients and the resistance is usually reported after long periods of treatment. In this study, the morphological characterization and virulence profile of FLU-susceptible and FLU-resistant clinical and environmental isolates of C. neoformans and C. gattii were performed both in vitro and in vivo using the Galleria mellonella model. FLU-susceptible isolates from C. neoformans were significantly more virulent than the FLU-resistant isolates. FLU-susceptible C. gattii isolates showed a different virulence profile from C. neoformans isolates where only the environmental isolate, CL, was more virulent compared with the resistant isolates. Cell morphology and capsule size were analyzed and the FLU-resistant isolates did not change significantly compared with the most sensitive isolates. Growth at 37°C was also evaluated and in both species, the resistant isolates showed a reduced growth at this temperature, indicating that FLU resistance can affect their growth. Based on the results obtained is possible suggest that FLU resistance can influence the morphology of the isolates and consequently changed the virulence profiles. The most evident results were observed for C. neoformans showing that the adaptation of isolates to antifungal selective pressure influenced the loss of virulence

Fabrication of a hydrogenated amorphous silicon detector in 3-d geometry and preliminary test on planar prototypes

Hydrogenated amorphous silicon (a-Si:H) can be produced by plasma-enhanced chemical vapor deposition (PECVD) of SiH4 (silane) mixed with hydrogen. The resulting material shows outstanding radiation hardness properties and can be deposited on a wide variety of substrates. Devices employing a-Si:H technologies have been used to detect many different kinds of radiation, namely, minimum ionizing particles (MIPs), X-rays, neutrons, and ions, as well as low-energy protons and alphas. However, the detection of MIPs using planar a-Si:H diodes has proven difficult due to their unsatisfactory S/N ratio arising from a combination of high leakage current, high capacitance, and limited charge collection efficiency (50% at best for a 30 µm planar diode). To overcome these limitations, the 3D-SiAm collaboration proposes employing a 3D detector geometry. The use of vertical electrodes allows for a small collection distance to be maintained while preserving a large detector thickness for charge generation. The depletion voltage in this configuration can be kept below 400 V with a consequent reduction in the leakage current. In this paper, following a detailed description of the fabrication process, the results of the tests performed on the planar p-i-n structures made with ion implantation of the dopants and with carrier selective contacts are illustrated