First Results of Magnetic Field Penetration Measurements of Multilayer SIS Structures

The performance of superconducting RF cavities made of bulk Nb is limited by a breakdown field of Bp ≈200 mT, close to the superheating field for Nb. A potentially promising solution to enhance the breakdown field of the SRF cavities beyond the intrinsic limits of Nb is a multilayer coating suggested in [1]. In the simplest case, such a multilayer may be a superconductor-insulator-superconductor (S-I-S) coating, for example, bulk niobium (S) coated with a thin film of insulator (I) followed by a thin layer of another superconductor (S) which could be e.g. dirty niobium [2]. Here we report the first results of our measurements of field penetration in Nb thin films and Nb-AlN-Nb multilayer samples at 4.2 K using the magnetic field penetration facility designed, built and tested in ASTeC

Low secondary electron yield of laser treated surfaces of copper, aluminium and stainless steel

Reduction of SEY was achieved by surface engineering through laser ablation with a laser operating at • = 355 nm. It was shown that the SEY can be reduced to near or below 1 on copper, aluminium and 316LN stainless steel. The laser treated surfaces show an increased surface resistance, with a wide variation in resistance found de-pending on the exact treatment details. However, a treated copper surface with similar surface resistance to aluminium was produced

Analyzing and predicting the spatial penetration of Airbnb in U.S. cities

In the hospitality industry, the room and apartment sharing platform of Airbnb has been accused of unfair competition. Detractors have pointed out the chronic lack of proper legislation. Unfortunately, there is little quantitative evidence about Airbnb's spatial penetration upon which to base such a legislation. In this study, we analyze Airbnb's spatial distribution in eight U.S. urban areas, in relation to both geographic, socio-demographic, and economic information. We find that, despite being very different in terms of population composition, size, and wealth, all eight cities exhibit the same pattern: that is, areas of high Airbnb presence are those occupied by the \newpart{``talented and creative''} classes, and those that are close to city centers. This result is consistent so much so that the accuracy of predicting Airbnb's spatial penetration is as high as 0.725