A Fluctuation-Dissipation Model for Electrical Noise

This paper shows that today’s modelling of electrical noise as coming from noisy resistances is a non sense one contradicting their nature as systems bearing an electrical noise. We present a new model for electrical noise that including Johnson and Nyquist work also agrees with the Quantum Mechanical description of noisy systems done by Callen and Welton, where electrical energy fluctuates and is dissipated with time. By the two currents the Admittance function links in frequency domain with their common voltage, this new model shows the connection Cause-Effect that exists between Fluctuation and Dissipation of energy in time domain. In spite of its radical departure from today’s belief on electrical noise in resistors, this Complex model for electrical noise is obtained from Nyquist result by basic concepts of Circuit Theory and Thermo- dynamics that also apply to capacitors and inductors.

Revisiting the Classics to recover the Physical Sense in electrical noise

This paper shows a physically cogent model for electrical noise in resistors that has been obtained from Thermodynamical reasons. This new model derived from the works of Johnson and Nyquist also agrees with the Quantum model for noisy systems handled by Callen and Welton in 1951, thus unifying these two Physical viewpoints. This new model is a Complex or 2-D noise model based on an Admittance that considers both Fluctuation and Dissipation of electrical energy to excel the Real or 1-D model in use that only considers Dissipation. By the two orthogonal currents linked with a common voltage noise by an Admittance function, the new model is shown in frequency domain. Its use in time domain allows to see the pitfall behind a paradox of Statistical Mechanics about systems considered as energy-conserving and deterministic on the microscale that are dissipative and unpredictable on the macroscale and also shows how to use properly the Fluctuation-Dissipation Theorem.

InN/GaN heterojunction electrical behavior

Indium nitride (InN) has been the subject of intense research in recent years. Some of its most attractive features are its excellent transport properties such as its small band edge electron effective mass, high electron mobilities and peak drift velocities, and high frequency transient drift velocity oscillations [1]. These suggest enormous potential applications for InN in high frequency electronic devices. But to date the high unintentional bulk electron concentration (n~1018 cm-3) of undoped InN samples and the surface electron accumulation layer make it a hard task to create a reliable metalsemiconductor Schottky barrier. Some attempts have been made to overcome this problem by means of material oxidation [2] or deposition of insulators [3]. In this work we present a way to obtain an electrical rectification behaviour by means of heterojunction growth. Due to the big band gap differences among nitride semiconductors, it’s possible to create a structure with high band offsets. In InN/GaN heterojunctions, depending on the GaN doping, the magnitude of conduction and valence band offset are critical parameters which allow distinguishing among different electrical behaviours. The earliest estimate of the valence band offset at an InN–GaN heterojunction in a wurtzite structure was measured to be ~0.85 eV [4], while the Schottky barrier heights were determined to be ~ 1,4 eV [5].We grew In-face InN layer with varying thickness (between 150 nm and 1 mm) by plasma assisted molecular beam epitaxy (PA-MBE) on GaNntemplates (GaN/Al2O3), with temperatures ranging between 300°C and 450°C. The different doping in GaN template (Si doping, Fe doping and Mg doping) results in differences in band alignments of the two semiconductors changing electrical barriers for carriers and consequently electrical conduction behaviour. The processing of the devices includes metallization of the ohmic contacts on InN and GaN, for which we used Ti/Al/Ni/Au. Whereas an ohmic contact on InN is straightforward, the main issue was the fabrication of the contact on GaN due to the very low decomposition temperature of InN. A standard ohmic contact on GaN is generally obtained by high temperature rapid thermal annealing (RTA), typically done between 500ºC and 900ºC[6]. In this case, the limitation due to the presence of In-face InN imposes an upper limit on the temperature for the thermal annealing process and ohmic contact formation of about 450°C. We will present results on the morphology of the InN layers by X-Ray diffraction and SEM, and electrical measurements, in particular current-voltage and capacitance-voltage characteristics.

Heterogeneous Collaborative Sensor Network for Electrical Management of an Automated House with PV Energy

In this paper we present a heterogeneous collaborative sensor network for electrical management in the residential sector. Improving demand-side management is very important in distributed energy generation applications. Sensing and control are the foundations of the “Smart Grid” which is the future of large-scale energy management. The system presented in this paper has been developed on a self-sufficient solar house called “MagicBox” equipped with grid connection, PV generation, lead-acid batteries, controllable appliances and smart metering. Therefore, there is a large number of energy variables to be monitored that allow us to precisely manage the energy performance of the house by means of collaborative sensors. The experimental results, performed on a real house, demonstrate the feasibility of the proposed collaborative system to reduce the consumption of electrical power and to increase energy efficiency.

Individualization and Electrical Characterization of SiGe Nanowires

SiGe nanowires of different Ge atomic fractions up to 15% were grown and ex-situ n-type doped by diffusion from a solid source in contact with the sample. The phenomenon of dielectrophoresis was used to locate single nanowires between pairs of electrodes in order to carry out electrical measurements. The measured resistance of the as-grown nanowires is very high, but it decreases more than three orders of magnitude upon doping, indicating that the doping procedure used has been effective

Probabilistic versus incremental presynaptic learning in biological plausible synapses

In this paper, the presynaptic rule, a classical rule for hebbian learning, is revisited. It is shown that the presynaptic rule exhibits relevant synaptic properties like synaptic directionality, and LTP metaplasticity (long-term potentiation threshold metaplasticity). With slight modifications, the presynaptic model also exhibits metaplasticity of the long-term depression threshold, being also consistent with Artola, Brocher and Singer’s (ABS) influential model. Two asymptotically equivalent versions of the presynaptic rule were adopted for this analysis: the first one uses an incremental equation while the second, conditional probabilities. Despite their simplicity, both types of presynaptic rules exhibit sophisticated biological properties, specially the probabilistic version

Solution-processed organic devices developed by a novel cost-effective patterning technique based on electrical erosion

Application of arc erosion to the patterning of metallic contacts in organic devices is presented. A home-made systems and details of the working principles are described. Advantages and drawbacks of this novel technology are discussed.

ESPINA: a tool for the automated segmentation and counting of synapses in large stacks of electron microscopy images

The synapses in the cerebral cortex can be classified into two main types, Gray’s type I and type II, which correspond to asymmetric (mostly glutamatergic excitatory) and symmetric (inhibitory GABAergic) synapses, respectively. Hence, the quantification and identification of their different types and the proportions in which they are found, is extraordinarily important in terms of brain function. The ideal approach to calculate the number of synapses per unit volume is to analyze 3D samples reconstructed from serial sections. However, obtaining serial sections by transmission electron microscopy is an extremely time consuming and technically demanding task. Using focused ion beam/scanning electron microscope microscopy, we recently showed that virtually all synapses can be accurately identified as asymmetric or symmetric synapses when they are visualized, reconstructed, and quantified from large 3D tissue samples obtained in an automated manner. Nevertheless, the analysis, segmentation, and quantification of synapses is still a labor intensive procedure. Thus, novel solutions are currently necessary to deal with the large volume of data that is being generated by automated 3D electron microscopy. Accordingly, we have developed ESPINA, a software tool that performs the automated segmentation and counting of synapses in a reconstructed 3D volume of the cerebral cortex, and that greatly facilitates and accelerates these processes.

Pre-Feasibility Study of Hybrid Wind Power-H-2 System Connected to Electrical Grid

The growth of wind power as an electric energy source is profitable from an environmental point of view and improves the energetic independence of countries with little fossil fuel resources. However, the wind resource randomness poses a great challenge in the management of electric grids. This study raises the possibility of using hydrogen as a mean to damp the variability of the wind resource. Thus, it is proposed the use of all the energy produced by a typical wind farm for hydrogen generation, that will in turn be used after for suitable generation of electric energy according to the operation rules in a liberalized electric market.