arXiv subjects

Cecilia Pennetta

Publications and source records attributed to Cecilia Pennetta.

6 recordsLinked to original sources

arXiv2010

Trapping-detrapping fluctuations in organic space-charge layers

A trapping-detrapping model is proposed for explaining the current fluctuation behavior in organic semiconductors (polyacenes) operating under current-injection conditions. The fraction of ionized traps obtained from the current-voltage characteristics, is related to the relative current noise spectral density at the trap-filling transition. The agreement between theory and experiments validates the model and provides an estimate of the concentration and energy level of deep traps.

cond-mat.mtrl-sci↗

arXiv2009

Topological change and impedance spectrum of rat olfactory receptor I7: A comparative analysis with bovine rhodopsin and bacterior

We present a theoretical investigation on possible selection of olfactory receptors (ORs) as sensing components of nanobiosensors. Accordingly, we generate the impedance spectra of the rat OR I7 in the native and activated state and analyze their differences. In this way, we connect the protein morphological transformation, caused by the sensing action, with its change of electrical impedance. The results are compared with those obtained by studying the best known protein of the GPCR family: bovine rhodopsin. Our investigations indicate that a change in morphology goes with a change in impedance spectrum mostly associated with a decrease of the static impedance up to about 60 % of the initial value, in qualitative agreement with existing experiments on rat OR I7. The predictiveness of the model is tested successfully for the case of recent experiments on bacteriorhodopsin. The present results point to a promising development of a new class of nanobiosensors based on the electrical properties of GPCR and other sensing proteins.

q-bio.BM↗

arXiv2007

Statistics of Extreme Values in Time Series with Intermediate-Term Correlations

It will be discussed the statistics of the extreme values in time series characterized by finite-term correlations with non-exponential decay. Precisely, it will be considered the results of numerical analyses concerning the return intervals of extreme values of the fluctuations of resistance and defect-fraction displayed by a resistor with granular structure in a nonequilibrium stationary state. The resistance and defect-fraction are calculated as a function of time by Monte Carlo simulations using a resistor network approach. It will be shown that when the auto-correlation function of the fluctuations displays a non-exponential and non-power-law decay, the distribution of the return intervals of extreme values is a stretched exponential, with exponent largely independent of the threshold. Recently, a stretched exponential distribution of the return intervals of extreme values has been identified in long-term correlated time series by Bunde et al. (2003) and Altmann and Kantz (2005). Thus, the present results show that the stretched exponential distribution of the return intervals is not an exclusive feature of long-term correlated time series.

cond-mat.stat-mech↗

arXiv2005

Distribution of Return Intervals of Extreme Events

The distribution of return intervals of extreme events is studied in time series characterized by finite-term correlations with non-exponential decay. Precisely, it has been analyzed the statistics of the return intervals of extreme values of the resistance fluctuations displayed by resistors with granular structure in nonequilibrium stationary states. The resistance fluctuations are calculated by Monte Carlo simulations using a resistor network approach. It has been found that for highly disordered networks, when the auto-correlation function displays a non-exponential and non-power-law decay, the distribution of return intervals of the extreme values is a stretched exponential, with exponent independent of the threshold.

physics.data-an↗

arXiv2005

Distribution of Return Periods of Rare Events in Correlated Time Series

We study the effect on the distribution of return periods of rare events of the presence in a time series of finite-term correlations with non-exponential decay. Precisely, we analyze the auto-correlation function and the statistics of the return intervals of extreme values of the resistance fluctuations displayed by a resistor with granular structure in a nonequilibrium stationary state. The resistance fluctuations, $δR$, are calculated by Monte Carlo simulations using the SBRN model introduced some years ago by Pennetta, Trefán and Reggiani and based on a resistor network approach. A rare event occurs when $δR$ overcomes a threshold value $q$ significantly higher than the average value of the resistance. We have found that for highly disordered networks, when the auto-correlation function displays a non-exponential decay but yet the resistance fluctuations are characterized by a finite correlation time, the distribution of return intervals of the extreme values is well described by a stretched exponential, with exponent largely independent of the threshold $q$. We discuss this result and some of the main open questions related to it, also in connection with very recent findings by other authors concerning the observation of stretched exponential distributions of return intervals of extreme events in long-term correlated time series.

physics.data-an↗

arXiv2004

Resistance Noise Near to Electrical Breakdown: Steady State of Random Networks as a Function of the Bias

A short review is presented of a recently developed computational approach which allows the study of the resistance noise over the full range of bias values, from the linear regime up to electrical breakdown. Resistance noise is described in terms of two competing processes in a random resistor network. The two processes are thermally activated and driven by an electrical bias. In the linear regime, a scaling relation has been found between the relative variance of resistance fluctuations and the average resistance. The value of the critical exponent is significantly higher than that associated with 1/f noise. In the nonlinear regime, occurring when the bias overcomes the threshold value, the relative variance of resistance fluctuations scales with the bias. Two regions can be identified in this regime: a moderate bias region and a pre-breakdown one. In the first region, the scaling exponent has been found independent of the values of the model parameters and of the bias conditions. A strong nonlinearity emerges in the pre-breakdown region which is also characterized by non-Gaussian noise. The results compare well with measurements of electrical breakdown in composites and with electromigration experiments in metallic lines.

cond-mat.dis-nn↗