arXiv subjects

C. Pennetta

Publications and source records attributed to C. Pennetta.

17 recordsLinked to original sources

arXiv2018

Current voltage characteristics and excess noise at the trap filling transition in polyacenes

Experiments in organic semiconductors (polyacenes) evidence a strong super quadratic increase of the current-voltage (I-V) characteristic at voltages in the transition region between linear (Ohmic) and quadratic (trap free space-charge-limited-current) behaviours. Similarly, excess noise measurements at a given frequency and increasing voltages evidence a sharp peak of the relative spectral density of the current noise in concomitance with the strong super-quadratic I-V characteristics. Here we discuss the physical interpretation of these experiments in terms of an essential contribution from field assisted trapping-detrapping processes of injected carriers. To this purpose, the fraction of filled traps determined by the I-V characteristics is used to evaluate the excess noise in the trap filled transition (TFT) regime. We have found an excellent agreement between the predictions of our model and existing experimental results in tetracene and pentacene thin films of different length in the range $0.65 \div 35 \ \mu m$.

cond-mat.mtrl-sci↗

arXiv2009

Tuning the Correlation Decay in the Resistance Fluctuations of Multi-Species Networks

A new network model is proposed to describe the $1/f^α$ resistance noise in disordered materials for a wide range of $α$ values ($0< α< 2$). More precisely, we have considered the resistance fluctuations of a thin resistor with granular structure in different stationary states: from nearly equilibrium up to far from equilibrium conditions. This system has been modelled as a network made by different species of resistors, distinguished by their resistances, temperature coefficients and by the energies associated with thermally activated processes of breaking and recovery. The correlation behavior of the resistance fluctuations is analyzed as a function of the temperature and applied current, in both the frequency and time domains. For the noise frequency exponent, the model provides $0< α< 1$ at low currents, in the Ohmic regime, with $α$ decreasing inversely with the temperature, and $1< α<2$ at high currents, in the non-Ohmic regime. Since the threshold current associated with the onset of nonlinearity also depends on the temperature, the proposed model qualitatively accounts for the complicate behavior of $α$ versus temperature and current observed in many experiments. Correspondingly, in the time domain, the auto-correlation function of the resistance fluctuations displays a variety of behaviors which are tuned by the external conditions.

cond-mat.mtrl-sci↗

arXiv2007

A network model to investigate structural and electrical properties of proteins

One of the main trend in to date research and development is the miniaturization of electronic devices. In this perspective, integrated nanodevices based on proteins or biomolecules are attracting a major interest. In fact, it has been shown that proteins like bacteriorhodopsin and azurin, manifest electrical properties which are promising for the development of active components in the field of molecular electronics. Here we focus on two relevant kinds of proteins: The bovine rhodopsin, prototype of GPCR protein, and the enzyme acetylcholinesterase (AChE), whose inhibition is one of the most qualified treatments of Alzheimer disease. Both these proteins exert their functioning starting with a conformational change of their native structure. Our guess is that such a change should be accompanied with a detectable variation of their electrical properties. To investigate this conjecture, we present an impedance network model of proteins, able to estimate the different electrical response associated with the different configurations. The model resolution of the electrical response is found able to monitor the structure and the conformational change of the given protein. In this respect, rhodopsin exhibits a better differential response than AChE. This result gives room to different interpretations of the degree of conformational change and in particular supports a recent hypothesis on the existence of a mixed state already in the native configuration of the protein.

q-bio.QM↗

arXiv2007

Long-term Correlations and 1/f^alpha Noise in the Steady States of Multi-Species Resistor Networks

We introduce a multi-species network model which describes the resistance fluctuations of a resistor in a non-equilibrium stationary state. More precisely, a thin resistor characterized by a 1/f^alpha resistance noise is described as a two-dimensional network made by different species of elementary resistors. The resistor species are distinguished by their resistances and by their energies associated with thermally activated processes of breaking and recovery. Depending on the external conditions, stationary states of the network can arise as a result of the competition between these processes. The properties of the network are studied as a function of the temperature by Monte Carlo simulations carried out in the temperature range 300 ÷800 K. At low temperatures, the resistance fluctuations display long-term correlations expressed by a power-law behavior of the auto-correlation function and by a value approx 1 of the alpha-exponent of the spectral density. On the contrary, at high temperatures the resistance fluctuations exhibit a finite and progressively smaller correlation time associated with a non-exponential decay of correlations and with a value of the alpha-exponent smaller than one. This temperature dependence of the alpha coefficient reproduces qualitatively well the experimental findings.

cond-mat.mtrl-sci↗

arXiv2005

Modelization of Thermal Fluctuations in G Protein-Coupled Receptors

We simulate the electrical properties of a device realized by a G protein coupled receptor (GPCR), embedded in its membrane and in contact with two metallic electrodes through which an external voltage is applied. To this purpose, recently, we have proposed a model based on a coarse graining description, which describes the protein as a network of elementary impedances. The network is built from the knowledge of the positions of the C-alpha atoms of the amino acids, which represent the nodes of the network. Since the elementary impedances are taken depending of the inter-nodes distance, the conformational change of the receptor induced by the capture of the ligand results in a variation of the network impedance. On the other hand, the fluctuations of the atomic positions due to thermal motion imply an impedance noise, whose level is crucial to the purpose of an electrical detection of the ligand capture by the GPCR. Here, in particular, we address this issue by presenting a computational study of the impedance noise due to thermal fluctuations of the atomic positions within a rhodopsin molecule. In our model, the C-alpha atoms are treated as independent, isotropic, harmonic oscillators, with amplitude depending on the temperature and on the position within the protein (alpha-helix or loop). The relative fluctuation of the impedance is then calculated for different temperatures.

q-bio.QM↗

arXiv2005

Non-Gaussian Fluctuations in Biased Resistor Networks: Size Effects versus Universal Behavior

We study the distribution of the resistance fluctuations of biased resistor networks in nonequilibrium steady states. The stationary conditions arise from the competition between two stochastic and biased processes of breaking and recovery of the elementary resistors. The fluctuations of the network resistance are calculated by Monte Carlo simulations which are performed for different values of the applied current, for networks of different size and shape and by considering different levels of intrinsic disorder. The distribution of the resistance fluctuations generally exhibits relevant deviations from Gaussianity, in particular when the current approaches the threshold of electrical breakdown. For two-dimensional systems we have shown that this non-Gaussianity is in general related to finite size effects, thus it vanishes in the thermodynamic limit, with the remarkable exception of highly disordered networks. For these systems, close to the critical point of the conductor-insulator transition, non-Gaussianity persists in the large size limit and it is well described by the universal Bramwell-Holdsworth-Pinton distribution. In particular, here we analyze the role of the shape of the network on the distribution of the resistance fluctuations. Precisely, we consider quasi-one-dimensional networks elongated along the direction of the applied current or trasversal to it. A significant anisotropy is found for the properties of the distribution. These results apply to conducting thin films or wires with granular structure stressed by high current densities.

cond-mat.stat-mech↗

arXiv2004

Non-Gaussian Resistance Fluctuations in Disordered Materials

We study the distribution of resistance fluctuations of conducting thin films with different levels of internal disorder. The film is modeled as a resistor network in a steady state determined by the competition between two biased processes, breaking and recovery of the elementary resistors. The fluctuations of the film resistance are calculated by Monte Carlo simulations which are performed under different bias conditions, from the linear regime up to the threshold for electrical breakdown. Depending on the value of the external current, on the level of disorder and on the size of the system, the distribution of the resistance fluctuations can exhibit significant deviations from Gaussianity. As a general trend, a size dependent, non universal distribution is found for systems with low and intermediate disorder. However, for strongly disordered systems, close to the critical point of the conductor-insulator transition, the non-Gaussianity persists when the size is increased and the distribution of resistance fluctuations is well described by the universal Bramwell-Holdsworth-Pinton distribution.

cond-mat.dis-nn↗

arXiv2004

Shot Noise in Linear Macroscopic Resistors

We report on a direct experimental evidence of shot noise in a linear macroscopic resistor. The origin of the shot noise comes from the fluctuation of the total number of charge carriers inside the resistor associated with their diffusive motion under the condition that the dielectric relaxation time becomes longer than the dynamic transit time. Present results show that neither potential barriers nor the absence of inelastic scattering are necessary to observe shot noise in electronic devices.

cond-mat.mtrl-sci↗

arXiv2004

Fluctuations of Complex Networks: Electrical Properties of Single Protein Nanodevices

We present for the first time a complex network approach to the study of the electrical properties of single protein devices. In particular, we consider an electronic nanobiosensor based on a G-protein coupled receptor. By adopting a coarse grain description, the protein is modeled as a complex network of elementary impedances. The positions of the alpha-carbon atoms of each amino acid are taken as the nodes of the network. The amino acids are assumed to interact electrically among them. Consequently, a link is drawn between any pair of nodes neighboring in space within a given distance and an elementary impedance is associated with each link. The value of this impedance can be related to the physical and chemical properties of the amino acid pair and to their relative distance. Accordingly, the conformational changes of the receptor induced by the capture of the ligand, are translated into a variation of its electrical properties. Stochastic fluctuations in the value of the elementary impedances of the network, which mimic different physical effects, have also been considered. Preliminary results concerning the impedance spectrum of the network and its fluctuations are presented and discussed for different values of the model parameters.

q-bio.MN↗

arXiv2004

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.

cond-mat.stat-mech↗

arXiv2004

Non-Gaussian Resistance Noise near Electrical Breakdown in Granular Materials

The distribution of resistance fluctuations of conducting thin films with granular structure near electrical breakdown is studied by numerical simulations. The film is modeled as a resistor network in a steady state determined by the competition between two biased processes, breaking and recovery. Systems of different sizes and with different levels of internal disorder are considered. Sharp deviations from a Gaussian distribution are found near breakdown and the effect increases with the degree of internal disorder. However, we show that in general this non-Gaussianity is related to the finite size of the system and vanishes in the large size limit. Nevertheless, near the critical point of the conductor-insulator transition, deviations from Gaussianity persist when the size is increased and the distribution of resistance fluctuations is well fitted by the universal Bramwell-Holdsworth-Pinton distribution.

cond-mat.stat-mech↗

arXiv2003

Non-Gaussianity of resistance fluctuations near electrical breakdown

We study the resistance fluctuation distribution of a thin film near electrical breakdown. The film is modeled as a stationary resistor networkunder biased percolation. Depending on the value of the external current,on the system sizes and on the level of internal disorder, the fluctuation distribution can exhibit a non-Gaussian behavior. We analyze this non-Gaussianity in terms of the generalized Gumbel distribution recently introduced in the context of highly correlated systems near criticality. We find that when the average fraction of defects approaches the random percolation threshold, the resistance fluctuation distribution is well described by the universal behavior of the Bramwell-Holdsworth-Pinton distribution.

cond-mat↗

arXiv2002

A Percolative Model of Soft Breakdown in Ultrathin Oxides

The degradation of ultrathin oxide layers in the presence of a stress voltage is modeled in terms of two antagonist percolation processes taking place in a random resistor network. The resistance and leakage current fluctuations are studied by MonteCarlo simulations for voltages below the breakdown threshold. An increase of excess noise together with a noticeable non-Gaussian behavior is found in the pre-breakdown regime in agreement with experimental results.

cond-mat↗

arXiv2002

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.

cond-mat↗

arXiv2002

Linear and nonlinear regime of a Random Resistor Network under biased percolation

We investigate the steady state of a two-dimensional random resistor network subjected to two competing biased percolations as a function of the bias strength. The properties of the linear and nonlinear regimes are studied by means of Monte Carlo simulations. In constant current conditions, a scaling relation is found between $ / _0$ and $I/I_0$, where $ $ is the average network resistance, $ _0$ the Ohmic resistance and $I_0$ an appropriate threshold value for the onset of nonlinearity. A similar scaling relation is found also for the relative variance of resistance fluctuations. These results are in good agreement with electrical breakdown measurements performed in composite materials.

cond-mat.stat-mech↗

arXiv2001

Monte Carlo simulation of electromigration phenomena in metallic lines

The electromigration (EM) of metallic lines is studied in terms of competition between two percolative processes taking place in a random resistor network. The effects associated with the transport of mass and with the consequent growth of the internal stress are accounted for by stochastic generation and recovery of voids, driven by the external current. Monte Carlo simulations enable us to investigate within a unified theoretical framework a variety of relevant aspects of EM degradation as: damage patterns, the distribution of the time to failures, early stage resistance change in the presence of compositional effects, Black's law, geometrical effects, etc. A general agreement is found with the experimental findings.

cond-mat↗

arXiv2001

Stationary Regime of Random Resistor Networks Under Biased Percolation

The state of a 2-D random resistor network, resulting from the simultaneous evolutions of two competing biased percolations, is studied in a wide range of bias values. Monte Carlo simulations show that when the external current $I$ is below the threshold value for electrical breakdown, the network reaches a steady state with a nonlinear current-voltage characteristic. The properties of this nonlinear regime are investigated as a function of different model parameters. A scaling relation is found between $ / _0$ and $I/I_0$, where $ $ is the average resistance, $ _0$ the linear regime resistance and $I_0$ the threshold value for the onset of nonlinearity. The scaling exponent is found to be independent of the model parameters. A similar scaling behavior is also found for the relative variance of resistance fluctuations. These results compare well with resistance measurements in composite materials performed in the Joule regime up to breakdown.

cond-mat.stat-mech↗