Improved nanopatterning for YBCO nanowires approaching the depairing current

An improved nanopatterning procedure has been developed to obtain YBCO nanowires with cross sections as small as 50x50 nm^2, protected by an Au capping layer. To probe the effective role of the Au protecting layer, we have measured the current-voltage characteristics and the resistive transition in temperature of the nanowires. Critical current densities up to 10^8 A/cm^2 have been achieved at T=4.2 K, approaching the theoretical depairing current limit. The resistance, measured as a function of temperature close to Tc, has been fitted with a thermal activated phase slip model, including the effect of the gold layer. The extracted values of the superconducting coherence length and of the London penetration depth give current densities consistent with the measured ones. These results cannot be achieved with same nanowires, without the Au capping layer.Comment: ASC 2012 conference contributio

Influence of Topological Edge States on the Properties of Al/Bi2Se3/Al Hybrid Josephson Devices

In superconductor-topological insulator-superconductor hybrid junctions, the barrier edge states are expected to be protected against backscattering, to generate unconventional proximity effects, and, possibly, to signal the presence of Majorana fermions. The standards of proximity modes for these types of structures have to be settled for a neat identification of possible new entities. Through a systematic and complete set of measurements of the Josephson properties we find evidence of ballistic transport in coplanar Al-Bi2Se3-Al junctions that we attribute to a coherent transport through the topological edge state. The shunting effect of the bulk only influences the normal transport. This behavior, which can be considered to some extent universal, is fairly independent of the specific features of superconducting electrodes. A comparative study of Shubnikov - de Haas oscillations and Scanning Tunneling Spectroscopy gave an experimental signature compatible with a two dimensional electron transport channel with a Dirac dispersion relation. A reduction of the size of the Bi2Se3 flakes to the nanoscale is an unavoidable step to drive Josephson junctions in the proper regime to detect possible distinctive features of Majorana fermions.Comment: 11 pages, 14 figure

Characterization of Magnetic Steels for the FCC-ee Magnet Prototypes

At the European Organization for the Nuclear Research (CERN), several efforts were combined for a preliminary design of a new accelerator, the Future Circular Collider (FCC), a 100-TeV double-ring hadron collider to be installed in a 100-km tunnel. As potential intermediate step, a high-luminosity lepton collider called FCC-ee is foreseen with more than 9,000 magnets. This paper provides an insight into the magnetic properties of the steels, potentially considered for the new dipole magnets, with nominal field of only 56 mT. The influence of the properties of these steels on the magnet transfer function has been assessed analytically using an equivalent reluctance network to model the first 1-m long dipole prototypes. The analytical results were validated experimentally. The proposed approach can be a useful tool for traceability and quality control during the series production

Dynamical charge density fluctuations pervading the phase diagram of a Cu-based high-Tc superconductor

Charge density waves are a common occurrence in all families of high critical temperature superconducting cuprates. Although consistently observed in the underdoped region of the phase diagram and at relatively low temperatures, it is still unclear to what extent they influence the unusual properties of these systems. Using resonant x-ray scattering we carefully determined the temperature dependence of charge density modulations in (Y,Nd)Ba$_2$Cu$_3$O$_{7-{\delta}}$ for three doping levels. We discovered short-range dynamical charge density fluctuations besides the previously known quasi-critical charge density waves. They persist up to well above the pseudogap temperature T*, are characterized by energies of few meV and pervade a large area of the phase diagram, so that they can play a key role in shaping the peculiar normal-state properties of cuprates.Comment: 34 pages, 4 figures, 11 supplementary figure

Transport and noise properties of YBCO nanowire based nanoSQUIDs

The development of quantum limited magnetic flux sensors has recently gained a lot of attention for the possibility of detecting the magnetic moment of nanoscaled systems. Here, the ultimate goal is the observation of a single spin. Such sensors are of fundamental importance for applications, ranging from spintronics and spin-based quantum information processing, to fundamental studies of nano-magnetism in molecules and magnetic nanoclusters. A nano-scale superconducting quantum interference device (nanoSQUID) is indeed a promising candidate to reach this ambitious goal. Nanowires, fabricated of high critical temperature superconductors (HTS), have been shown to be a valid candidate for the realization of nanoSQUIDs. A crucial requirement to achieve the necessary flux sensitivity and spatial resolution, is a SQUID loop on the nanometer scale. Moreover, HTS nanowire-based SQUIDs in combination with large area pickup loops or flux transformers might become instrumental in magnetometer applications, such as magneto encephalography and low field magnetic resonance imaging, where low intrinsic magnetic field noise is required. In this review we will give a survey on the state of the art of YBa2Cu3O7-δ thin film nanowires and their implementation in low noise nanoSQUIDs and magnetometers

Enhancement of SSVEPs Classification in BCI-based Wearable Instrumentation Through Machine Learning Techniques

This work addresses the adoption of Machine Learning classifiers and Convolutional Neural Networks to improve the performance of highly wearable, single-channel instrumentation for Brain-Computer Interfaces. The proposed measurement system is based on the classification of Steady-State Visually Evoked Potentials (SSVEPs). In particular, Head-Mounted Displays for Augmented Reality are used to generate and display the flickering stimuli for the SSVEPs elicitation. Four experiments were conducted by employing, in turn, a different Head-Mounted Display. For each experiment, two different algorithms were applied and compared with the state-of-the-art-techniques. Furthermore, the impact of different Augmented Reality technologies in the elicitation and classification of SSVEPs was also explored. The experimental metrological characterization demonstrates (i) that the proposed Machine Learning-based processing strategies provide a significant enhancement of the SSVEP classification accuracy with respect to the state of the art, and (ii) that choosing an adequate Head-Mounted Display is crucial to obtain acceptable performance. Finally, it is also shown that the adoption of inter-subjective validation strategies such as the Leave-One-Subject-Out Cross Validation successfully leads to an increase in the inter-individual 1-σ reproducibility: this, in turn, anticipates an easier development of ready-to-use systems

A ML-based Approach to Enhance Metrological Performance of Wearable Brain-Computer Interfaces

In this paper, the adoption of Machine Learning (ML) classifiers is addressed to improve the performance of highly wearable, single-channel instrumentation for Brain-Computer Interfaces (BCIs). The proposed BCI is based on the classification of Steady-State Visually Evoked Potentials (SSVEPs). In this setup, Augmented Reality Smart Glasses are used to generate and display the flickering stimuli for the SSVEP elicitation. An experimental campaign was conducted on 20 adult volunteers. Successively, a Leave-One-Subject-Out Cross Validation was performed to validate the proposed algorithm. The obtained experimental results demonstrate that suitable ML-based processing strategies outperform the state-of-the-art techniques in terms of classification accuracy. Furthermore, it was also shown that the adoption of an inter-subjective model successfully led to a decrease in the 3-σ uncertainty: this can facilitate future developments of ready-to-use systems

Assessment of blood perfusion quality in laparoscopic colorectal surgery by means of Machine Learning

An innovative algorithm to automatically assess blood perfusion quality of the intestinal sector in laparoscopic colorectal surgery is proposed. Traditionally, the uniformity of the brightness in indocyanine green-based fluorescence consists only in a qualitative, empirical evaluation, which heavily relies on the surgeon’s subjective assessment. As such, this leads to assessments that are strongly experience-dependent. To overcome this limitation, the proposed algorithm assesses the level and uniformity of indocyanine green used during laparoscopic surgery. The algorithm adopts a Feed Forward Neural Network receiving as input a feature vector based on the histogram of the green band of the input image. It is used to (i) acquire information related to perfusion during laparoscopic colorectal surgery, and (ii) support the surgeon in assessing objectively the outcome of the procedure. In particular, the algorithm provides an output that classifies the perfusion as adequate or inadequate. The algorithm was validated on videos captured during surgical procedures carried out at the University Hospital Federico II in Naples, Italy. The obtained results show a classification accuracy equal to 99.9 % , with a repeatability of 1.9 %. Finally, the real-time operation of the proposed algorithm was tested by analyzing the video streaming captured directly from an endoscope available in the OR

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