Superconducting properties of MgB2 thin films prepared on flexible plastic substrates

Superconducting MgB2 thin films were prepared on 50-micrometer-thick, flexible polyamide Kapton-E foils by vacuum co-deposition of Mg and B precursors with nominal thickness of about 100 nm and a special ex-situ rapid annealing process in an Ar or vacuum atmosphere. In the optimal annealing process, the Mg-B films were heated to approximately 600 C, but at the same time, the backside of the structures was attached to a water-cooled radiator to avoid overheating of the plastic substrate. The resulting MgB2 films were amorphous with the onset of the superconducting transition at T_(c,on) about 33 K and the transition width of approximately 3 K. The critical current density was > 7x10^5 A/cm^2 at 4.2 K, and its temperature dependence indicated a granular film composition with a network of intergranular weak links. The films could be deposited on large-area foils (up to 400 cm^2) and, after processing, cut into any shapes (e.g., stripes) with scissors or bent multiple times, without any observed degradation of their superconducting properties.Comment: 3 figure

Switching the Conductance of a Molecular Junction using a Proton Transfer Reaction

A novel mechanism for switching a molecular junction based on a proton transfer reaction triggered by an external electrostatic field is proposed. As a specific example to demonstrate the feasibility of the mechanism, the tautomers [2,5-(4-hydroxypyridine)] and {2,5-[4(1H)-pyridone]} are considered. Employing a combination of first-principles electronic structure calculations and Landauer transport theory, we show that both tautomers exhibit very different conductance properties and realize the "on" and "off" states of a molecular switch. Moreover, we provide a proof of principle that both forms can be reversibly converted into each other using an external electrostatic field.Comment: 14 pages, 5 figure

Managing wind power generation via indexed semi-markov model and copula

Because of the stochastic nature of wind turbines, the output power management of wind power generation (WPG) is a fundamental challenge for the integration of wind energy systems into either power systems or microgrids (i.e., isolated systems consisting of local wind energy systems only) in operation and planning studies. In general, a wind energy system can refer to both one wind farm consisting of a number of wind turbines and a given number of wind farms sited at the area in question. In power systems (microgrid) planning, a WPG should be quantified for the determination of the expected power flows and the analysis of the adequacy of power generation. Concerning this operation, the WPG should be incorporated into an optimal operation decision process, as well as unit commitment and economic dispatch studies. In both cases, the probabilistic investigation of WPG leads to a multivariate uncertainty analysis problem involving correlated random variables (the output power of either wind turbines that constitute wind farm or wind farms sited at the area in question) that follow different distributions. This paper advances a multivariate model of WPG for a wind farm that relies on indexed semi-Markov chains (ISMC) to represent the output power of each wind energy system in question and a copula function to reproduce the spatial dependencies of the energy systems’ output power. The ISMC model can reproduce long-term memory effects in the temporal dependence of turbine power and thus understand, as distinct cases, the plethora of Markovian models. Using copula theory, we incorporate non-linear spatial dependencies into the model that go beyond linear correlations. Some copula functions that are frequently used in applications are taken into consideration in the paper; i.e., Gumbel copula, Gaussian copula, and the t-Student copula with different degrees of freedom. As a case study, we analyze a real dataset of the output powers of six wind turbines that constitute a wind farm situated in Poland. This dataset is compared with the synthetic data generated by the model thorough the calculation of three adequacy indices commonly used at the first hierarchical level of power system reliability studies; i.e., loss of load probability (LOLP), loss of load hours (LOLH) and loss of load expectation (LOLE). The results will be compared with those obtained using other models that are well known in the econometric field; i.e., vector autoregressive models (VAR)

Investigation of Dark Counts in Innovative Materials for Superconducting Nanowire Single-photon Detector Applications

The phenomenon of dark counts in nanostripes of different superconductor systems such as high-temperature superconducting YBa2Cu3O7-x and superconductor/ferromagnet hybrids consisting of either NbN/NiCu or YBa2Cu3O7- x/L0.7Sr0.3MnO3 bilayers have been investigated. For NbN/NiCu the rate of dark-count transients have been reduced with respect to pure NbN nanostripes and the events were dominated by a single vortex entry from the edge of the stripe. In the case of nanostripes based on YBa2Cu3O7-x, we have found that thermal activation of vortices was also, apparently, responsible for triggering dark-count signals

Monte Carlo studies of the intrinsic time-domain response of nanoscale three-branch junctions

We present a Monte Carlo time-domain study of nanostructured ballistic three-branch junctions (TBJs) excited by both step-function and Gaussian picosecond transients. Our TBJs were based on InGaAs 2-dimensional electron gas heterostructures and their geometry followed exactly the earlier experimental studies. Time-resolved, picosecond transients of both the central branch potential and the between-the-arms current demonstrate that the bandwidth of the intrinsic TBJ response reaches the THz frequency range, being mainly limited by the large-signal, intervalley scattering, when the carrier transport regime changes from ballistic to diffusive

Errare machinale est: The use of error-related potentials in brain-machine interfaces

The ability to recognize errors is crucial for efficient behavior. Numerous studies have identified electrophysiological correlates of error recognition in the human brain (error-related potentials, ErrPs). Consequently, it has been proposed to use these signals to improve human-computer interaction (HCI) or brain-machine interfacing (BMI). Here, we present a review of over a decade of developments towards this goal. This body of work provides consistent evidence that ErrPs can be successfully detected on a single-trial basis, and that they can be effectively used in both HCI and BMI applications. We first describe the ErrP phenomenon and follow up with an analysis of different strategies to increase the robustness of a system by incorporating single-trial ErrP recognition, either by correcting the machine's actions or by providing means for its error-based adaptation. These approaches can be applied both when the user employs traditional HCI input devices or in combination with another BMI channel. Finally, we discuss the current challenges that have to be overcome in order to fully integrate ErrPs into practical applications. This includes, in particular, the characterization of such signals during real(istic) applications, as well as the possibility of extracting richer information from them, going beyond the time-locked decoding that dominates current approaches

Error Potentials for Brain-Computer Interfaces

The idea to use EEG correlates of errors to correct or reinforce BCI operation has been proposed over a decade ago. Since then a body of evidence has corroborated this approach. In this paper we give an overview of our recent work exploring the possibilities of error-potential applications, involving removing constraints of laboratory paradigms to increase “real-life” validity, and investigating EEG feature-spaces to increase detection robustness

Y-Ba-Cu-O Nanostripes for Optical Photon Detection

Nanowires of Y-Ba-Cu-O, with the thickness of 50 nm and the width ranging from 90 nm to 500 nm have been successfully grown on lanthanum aluminate substrates for photon detection experiments. The nanowires were up to 10-mu m long and formed a meander structure, covering the area of up to 30x10 mu m(2) with a fill factor of 50%. The samples were excited using optical laser pulses at a 1550 nm wavelength and resulting photoresponse signals were measured as a function of both temperature and normalized bias current. Presence of two, distinct regimes in the photoresponse temperature dependence has been clearly evidenced, suggesting different physical mechanisms of the signal formation. Presented experimental results shed new light on prospects of implementation of high-temperature superconducting oxides in photon detection and counting