Electrical Transport and Fluctuation Processes in NbRe and NbReN Ultrathin Films for Superconducting Electronics Applications

NbRe-based superconducting thin films recently received relevant interest in the field of low-temperature electronics. However, for these materials the electrical conduction mechanisms, in particular in the normal state, still need to be investigated in more detail. Here, NbRe and NbReN films of different thicknesses have been deposited on two different substrates, namely monocrystalline Si and SiO2 buffered Si. The films were characterized by DC electrical transport measurements. Moreover, a connection with the charge carriers fluctuation processes has been made by analyzing the electrical noise generated in the normal state region. Despite the films morphology seems not to be affected by the substrate used, a lower noise level has been found for the ones grown on SiO2, in particular for NbReN. From this study it emerges that both NbRe and NbReN ultrathin films are of very good quality, as far as the low-temperature electrical noise and conduction are concerned, with noise levels competitive with NbN. These results may further support the proposal of using these materials in a nanowire form in the field of superconducting electronics.

Novel U-net based deep neural networks for transmission tomography

BACKGROUND: The fusion of computer tomography and deep learning is an effective way of achieving improved image quality and artifact reduction in reconstructed images. OBJECTIVE: In this paper, we present two novel neural network architectures for tomographic reconstruction with reduced effects of beam hardening and electrical noise. METHODS: In the case of the proposed novel architectures, the image reconstruction step is located inside the neural networks, which allows the network to be trained by taking the mathematical model of the projections into account. This strong connection enables us to enhance the projection data and the reconstructed image together. We tested the two proposed models against three other methods on two datasets. The datasets contain physically correct simulated data, and they show strong signs of beam hardening and electrical noise. We also performed a numerical evaluation of the neural networks on the reconstructed images according to three error measurements and provided a scoring system of the methods derived from the three measures. RESULTS: The results showed the superiority of the novel architecture called TomoNet2. TomoNet2 improved the quality of the images according to the average Structural Similarity Index from 0.9372 to 0.9977 and 0.9519 to 0.9886 on the two data sets, when compared to the FBP method. This network also yielded the best results for 79.2 and 53.0 percent for the two datasets according to Peak-Signal-to-Noise-Ratio compared to the other improvement techniques. CONCLUSIONS: Our experimental results showed that the reconstruction step used in skip connections in deep neural networks improves the quality of the reconstructions. We are confident that our proposed method can be effectively applied to other datasets for tomographic purposes.

Electronics improvements for low-level control in the humanoid robot TEO

This work began with developing the first electronic integration to allow the operation of commercial TEO devices pre-selected. However, different problems were discovered during the implementation of the whole set. These were caused by the malfunction of the system and the particular design. For this reason, this paper is focused on the analysis of the first hardware architecture to propose and develop a solution that improves the performance of the joint motor control.Significantly, the detected problems are voltage drops in the power supply signals of some devices, electrical noise coupling or overshoots produced by the switching of the power inverter of the driver, and the electromechanical disconnections of various signals caused by the relative motion between devices. The consequence was that the robot joints control was not robust, preventing them from moving accurately. After the analysis, new interconnection electronics was developed. This electronic has been designed to be more integrated with the mechanic parts, improving subsystems location, and integrating new solutions to reduce the electrical problems. The new electronics have been tested in the humanoid robot arms with good results.

Influence of penetrating radiations on electrical low frequency noise of semiconductors

The influence of penetrating radiations on the electrical low-frequency noise of semiconductors is studied. Expression is calculated that determines the number of structural defects in semiconductors arising from exposure to penetrating radia-tion. General form expression is calculated for the spectrum of electrical low-frequency noise in semiconductors when exposed to penetrating radiation. Quanti-tative relationship was established between the spectrum of electrical low-frequency noise and the development of disturbances in the structure of semicon-ductors caused by penetrating radiations. The results obtained can be used to de-termine the spectra of electrical noise in semiconductors of various types and in numerous semiconductor devices. The results of the article have practical applica-tions. Calculated expressions allow to make estimates of the intensity of electrical low-frequency noise, from which conclusions can be drawn about possibility of functioning and reliability of semiconductor devices. Established relationship be-tween electrical noise and radiation defects can be used to estimate, based on spec-tral characteristics of the noise, the defectiveness of structure of semiconductors subjected to radiation damage.

Analysis of Excitability in Resonant Tunneling Diode-Photodetectors

We investigate the dynamic behaviour of resonant tunneling diode-photodetectors (RTD-PDs) in which the excitability can be activated by either electrical noise or optical signals. In both cases, we find the characteristics of the stochastic spiking behavior are not only dependent on the biasing positions but also controlled by the intensity of the input perturbations. Additionally, we explore the ability of RTD-PDs to perform optical signal transmission and neuromorphic spike generation simultaneously. These versatile functions indicate the possibility of making use of RTD-PDs for innovative applications, such as optoelectronic neuromorphic circuits for spike-encoded signaling and data processing.

Graphene and Its Nanocomposites Based Humidity Sensors: Recent Trends and Challenges

Humidity sensors are of utmost importance in certain areas of life, in processing industries, in fabrication laboratories and in agriculture. Precise evaluation of humidity percentage in air is the need of various applications. Graphene and its composites have shown great potential in performing as humidity sensors owing to enormous surface area, very low electrical noise, high electrical conductivity, mechanical and thermal stability and high room temperature mobility. There is no such extensive review on graphene-based devices for humidity sensing applications. This review extensively discusses graphene-based devices intended towards sensing humidity, starting from the methods of synthesizing graphene, its electronic and mechanical properties favoring sensing behavior and different types of sensing mechanisms. The review also studies the performance and recent trends in humidity sensor based on graphene, graphene quantum dots, graphene oxide, reduced graphene oxide and various composite materials based on graphene such as graphene/polymer, graphene/metal oxide or graphene/metal. Discussions on the limitations and challenges of the graphene-based humidity sensors along with its future trends are made.

Ozone detection by means of semiconductor gas sensors based on palladium (II) oxide

Thin film semiconductor sensors based on palladium oxide were produced to analyse the concentration of ozone in the air. The palladium oxide films were obtained by means of thermal oxidation of ~ 20-30 nm metal in air at various temperatures. The oxide films were studied using electron microscopy and reflection high-energy electron diffraction. The optical, electrophysical, and gas sensitivity properties of the films were investigated. The study determined the optimal oxidation annealing temperature that ensures the uniform composition of the films and absence of electrical noise affecting the gas detection process. The article explains that electrical noise in ultrathin films is caused by their fragmentation during oxidation annealing. The study demonstrated the high sensitivity of the obtained films to oxide.