Spin pumping damping and magnetic proximity effect in Pd and Pt spin-sink layers

We investigated the spin pumping damping contributed by paramagnetic layers (Pd, Pt) in both direct and indirect contact with ferromagnetic Ni$_{81}$Fe$_{19}$ films. We find a nearly linear dependence of the interface-related Gilbert damping enhancement $\Delta\alpha$ on the heavy-metal spin-sink layer thicknesses t$_\textrm{N}$ in direct-contact Ni$_{81}$Fe$_{19}$/(Pd, Pt) junctions, whereas an exponential dependence is observed when Ni$_{81}$Fe$_{19}$ and (Pd, Pt) are separated by \unit[3]{nm} Cu. We attribute the quasi-linear thickness dependence to the presence of induced moments in Pt, Pd near the interface with Ni$_{81}$Fe$_{19}$, quantified using X-ray magnetic circular dichroism (XMCD) measurements. Our results show that the scattering of pure spin current is configuration-dependent in these systems and cannot be described by a single characteristic length

Design and testing of a static rig for tesla turbine flow visualization

The aim of this work is to describe the design and the use of an innovative test rig for investigating the expansion of subcooled fluids inside a converging nozzle and the evolution of two-phase flows in Tesla-type turbines. The flow exiting the nozzle enters tangentially into a thin flat circular chamber and it finally is discharged in the center through a duct perpendicular to it. The experimental test rig has two nozzles placed in diametric position. This peculiar shape reproduces the geometry of a single gap between two discs of a Tesla turbine, a machine that potentially could replace the throttling valve in chillers and heat pumps to increase their COP. The study of a simple and static geometry is necessary in order to calibrate the CFD modeling of the phase change in nozzle and rotor chamber. The rig was designed and assembled by TPG of the University of Genoa in the framework of the Pump-Heat H2020 project. Here it is used subcooled water and, in order to fully characterize the expansion conditions, the rig has been equipped with pressure sensors at the nozzle inlet and at the rig outlet. A Coriolis mass flow meter and a temperature sensor were also placed at nozzle inlet. High-resolution cameras provided and managed by Ansaldo Energia were used to look at the position and shape of the front of the fluid phase change along and around the nozzle as a function of varying pressure and temperature conditions. The tests were performed in the 2.1- 5.1barG pressure range and in the 132-155\ub0C temperature range, feeding either one or both nozzles. Future work involves the use of different nozzle profiles, such as a convergent/divergent in order to test both subsonic and supersonic flows, and experimental analysis of pressures in the rotor chamber, aimed to optimize the geometry of nozzles and Tesla turbines in two-phase applications

The Adoption of Industry 4.0 Technologies Through the Implementation of Continuous Improvement Tools

In recent years, the term Industry 4.0 refers to a multiplicity of changes which are revolutionizing the production methods of different industrial sectors. The purpose of this chapter is to identify different tools to support continuous improvement of performance in order to adopt Industry 4.0 model (see figure below). To reach this aim, the authors carried out an analysis on possible implementation and integration of different Quality Management approaches, as World Class Manufacturing (WCM) and RAMI 4.0 in an Italian aerospace,defense and security company, within the scope of national program PON 2014– 2020, Leonardo 4.0, and the program ECSEL-Innovation Actions-2018. This research provides information about possible integration between managerial approaches and 4.0 technologies. This integration will allow the real implementation Industry 4.0 model. This can serve to academicians and practitioners in the field as incipit for development of actionable strategies and practices for successful transition from traditional manufacturing into the Industry 4.0. The present chapter contributes to the debate surrounding Industry 4.0 by stressing that willing firms undertake the transition from actually manufacturing into the Industry 4.0, can’t build this phase on only application of enabling technologies but must be aware that is necessary have to implement precise organizational and managerial approaches. All stakeholders need to be aware that to adopt the Industry 4.0 model requires not only the application of the new technologies but also the development and implementation of a series of Quality Management tools and practices that become an essential key to face the fourth Industrial Revolution. In fact, better managerial practices can support the correct adoption of the Industry 4.0 model

A case study in smart manufacturing: predictive analysis of cure cycle results for a composite component

Aim: This work proposes a workflow monitoring sensor observations over time to identify and predict relevant changes or anomalies in the cure cycle (CC) industrial process. CC is a procedure developed in an autoclave consisting of applying high temperatures to provide composite materials. Knowing anomalies in advance could improve efficiency and avoid product discard due to poor quality, benefiting sustainability and the environment.Methods: The proposed workflow exploits machine learning techniques for monitoring and early validating the CC process according to the time-temperature constraints in a real industrial case study. It uses CC's data produced by the thermocouples in the autoclave along the cycle to train an LSTM model. Fast Low-cost Online Semantic Segmentation algorithm is used for better characterizing the time series of temperature. The final objective is predicting future temperatures minute by minute to forecast if the cure will satisfy the constraints of quality control or raise the alerts for eventually recovering the process.Results: Experimentation, conducted on 142 time series (of 550 measurements, on average), shows that the framework identifies invalid CCs with significant precision and recall values after the first 2 hours of the process.Conclusion: By acting as an early-alerting system for the quality control office, the proposal aims to reduce defect rates and resource usage, bringing positive environmental impacts. Moreover, the framework could be adapted to other manufacturing targets by adopting specific datasets and tuning thresholds

Temperature dependence of the superconducting proximity effect quantified by scanning tunneling spectroscopy

Here, we present the first systematic study on the temperature dependence of the extension of the superconducting proximity effect in a 1–2 atomic layer thin metallic film, surrounding a superconducting Pb island. Scanning tunneling microscopy/spectroscopy (STM/STS) measurements reveal the spatial variation of the local density of state on the film from 0.38 up to 1.8 K. In this temperature range the superconductivity of the island is almost unaffected and shows a constant gap of a 1.20 ± 0.03 meV. Using a superconducting Nb-tip a constant value of the proximity length of 17 ± 3 nm at 0.38 and 1.8 K is found. In contrast, experiments with a normal conductive W-tip indicate an apparent decrease of the proximity length with increasing temperature. This result is ascribed to the thermal broadening of the occupation of states of the tip, and it does not reflect an intrinsic temperature dependence of the proximity length. Our tunneling spectroscopy experiments shed fresh light on the fundamental issue of the temperature dependence of the proximity effect for atomic monolayers, where the intrinsic temperature dependence of the proximity effect is comparably weak

Effects of surface oxidation on the exchange-bias properties of the single-crystal antiferromagnetic/ferromagnetic junction Mn/Co/Cu(001)

The effects of a chemical alteration of the antiferromagnet surface in the exchange-biased ultrathin epitaxial antiferromagnetic/ferromagnetic bilayer Mn/Co/Cu(001) have been investigated. The formation of a nanometer-thick paramagnetic oxide at the surface of the Mn layer was induced through the controlled exposure to oxygen. Although the buried Mn/Co interface was not affected by the oxidation, strong changes of the exchange-bias properties of the system, which cannot be accounted for by the mere reduction of the antiferromagnetic Mn thickness, were observed. We propose that the produced surface modification affects the magnetic configuration of the near-surface region and the domain structure in the whole antiferromagnet layer which, in turn, influences the pinned uncompensated spin density responsible for the exchange bias