Temperature- and doping-dependent nanoscale Schottky barrier height at the Au/Nb:SrTiO3interface

We use ballistic electron emission microscopy to investigate prototypical Au/Nb-doped SrTiO3(NSTO) Schottky barrier diodes for different temperatures and doping levels. To this end, ultrathin Au overlayers are thermally evaporated onto TiO2-terminated NSTO single crystal substrates. We show that at room temperature, regardless of the nominal doping, rectification is controlled by a spatially inhomogeneous Schottky barrier height (SBH), which varies on a length scale of tens of nanometers according to a Gaussian distribution with a mean value of 1.29-1.34 eV and the standard deviation in the range of 80-100 meV. At lower temperatures, however, doping effects become relevant. In particular, junctions with a low Nb content of 0.01 and 0.05 wt. % show an 3c300 meV decrease in the mean SBH from room temperature to 80 K, which can be explained by an electrostatic analysis assuming a temperature-dependent dielectric permittivity for NSTO. In contrast, this model fails to predict the weaker temperature dependence of SBH for junctions based on 0.5 wt. % NSTO. Our nanoscale investigation demands to reassess conventional models for the NSTO polarizability in high-intensity electric fields. Furthermore, it contributes to the comprehension and prediction of transport in metal/SrTiO3junctions and devices

Tc=21K in epitaxial FeSe0.5Te0.5 thin films with biaxial compressive strain

High purity epitaxial FeSe0.5Te0.5 thin films with different thickness were grown by Pulsed Laser Ablation on different substrates. By varying the film thickness, Tc up to 21K were observed, significantly larger than the bulk value. Structural analyses indicated that the a axis changes significantly with the film thickness and is linearly related to the Tc. The latter result indicates the important role of the compressive strain in enhancing Tc. Tc is also related to both the Fe-(Se,Te) bond length and angle, suggesting the possibility of further enhancement

Impact of upstream landslide on perialpine lake ecosystem: An assessment using multi-temporal satellite data

Monitoring freshwater and wetland systems and their response to stressors of natural or anthropogenic origin is critical for ecosystem conservation. A multi-temporal set of 87 images, acquired by Sentinel-2 satellites over three years (2016–2018), provided quantitative information for assessing the temporal evolution of key ecosystem variables in the perialpine Lake Mezzola (northern Italy), which has suffered from the impacts of a massive landslide that took place upstream of the lake basin in summer 2017. Sentinel-2 derived products revealed an increase in lake turbidity triggered by the landslide that amounted to twice the average values scored in the years preceding and following the event. Hotspots of turbidity within the lake were in particular highlighted. Moreover, both submerged and riparian vegetation showed harmful impacts due to sediment deposition. A partial loss of submerged macrophyte cover was found, with delayed growth and a possible community shift in favor of species adapted to inorganic substrates. Satellite-derived seasonal dynamics showed that exceptional sediment load can overwrite climatic factors in controlling phenology of riparian reed beds, resulting in two consecutive years with shorter than normal growing season and roughly 20% drop in productivity, according to spectral proxies. Compared to 2016, senescence came earlier by around 20 days on average in 2017 season, and green-up was delayed by up to 50 days (20 days, on average) in 2018, following the landslide. The approach presented could be easily implemented for continuous monitoring of similar ecosystems subject to external pressures with periods of high sediment loads

Light Transmission Properties and Shannon Index in One-Dimensional Photonic Media With Disorder Introduced by Permuting the Refractive Index Layers

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Influence of free charge carrier density on the magnetic behavior of (Zn,Co)O thin film studied by Field Effect modulation of magnetotransport

The origin of (ferro)magnetic ordering in transition metal doped ZnO is a still open question. For applications it is fundamental to establish if it arises from magnetically ordered impurity clusters embedded into the semiconducting matrix or if it originates from ordering of magnetic ions dilute into the host lattice. In this latter case, a reciprocal effect of the magnetic exchange on the charge carriers is expected, offering many possibilities for spintronics applications. In this paper we report on the relationship between magnetic properties and free charge density investigated by using Zinc oxide based field effect transistors, in which the charge carrier density is modulated by more than 4 order of magnitude, from 10(16) to 10(20) e(-)/cm(3). The magnetotransport properties are employed to probe the magnetic status of the channel both in pure and cobalt doped zinc oxide transistors. We find that it is widely possible to control the magnetic scattering rates by field effect. We believe that this finding is a consequence of the modulation of magnetization and carrier spin polarization by the electric field. The observed effects can be explained by the change in size of bound magnetic polarons that induces a percolation magnetic ordering in the sample

Thermal properties of SmFeAs(O1-xFx) as probe of the interplay between electrons and phonons

A comparative study of thermal properties of SmFeAsO, SmFeAs(O0.93F0.07) and SmFeAs(O0.85F0.15) samples is presented. Specific heat and thermal conductivity show clear evidences of the spin density wave (SDW) ordering below TSDW 135 K in undoped SmFeAsO. At low level of F-doping, SmFeAs(O0.93F0.07), SDW ordering is suppressed and superconducting features are not yet optimally developed in both specific heat and thermal conductivity. At optimal level of F-doping SmFeAs(O0.85F0.15) anomalies related to the superconducting transition are well noticeable. By a compared analysis of doped and undoped samples we conclude that, despite F-doping modifies definitely the electronic ground state, it does not substantially alter phonon and electron parameters, like phonon modes, Sommerfeld coefficient, electro-phonon coupling. The analysis of the thermal conductivity curves provides an evaluation of SDW and superconducting energy gap, showing that phonons can suitably probe features of electronic ground state

Network structure indexes to forecast epidemic spreading in real-world complex networks

Complex networks are the preferential framework to model spreading dynamics in several real-world complex systems. Complex networks can describe the contacts between infectious individuals, responsible for disease spreading in real-world systems. Understanding how the network structure affects an epidemic outbreak is therefore of great importance to evaluate the vulnerability of a network and optimize disease control. Here we argue that the best network structure indexes (NSIs) to predict the disease spreading extent in real-world networks are based on the notion of network node distance rather than on network connectivity as commonly believed. We numerically simulated, via a type-SIR model, epidemic outbreaks spreading on 50 real-world networks. We then tested which NSIs, among 40, could a priori better predict the disease fate. We found that the “average normalized node closeness” and the “average node distance” are the best predictors of the initial spreading pace, whereas indexes of “topological complexity” of the network, are the best predictors of both the value of the epidemic peak and the final extent of the spreading. Furthermore, most of the commonly used NSIs are not reliable predictors of the disease spreading extent in real-world networks

Considering weights in real social networks: A review

Network science offers powerful tools to model complex social systems. Most social network science research focuses on topological networks by simply considering the binary state of the links, i.e., their presence or absence. Nonetheless, complex social systems present heterogeneity in link interactions (link weight), and accounting for this heterogeneity, it is mandatory to design reliable social network models. Here, we revisit the topic of weighted social networks (WSNs). By summarizing the main notions, findings, and applications in the field of WSNs, we outline how WSN methodology may improve the modeling of several real problems in social sciences. We are convinced that WSNs may furnish ideas and insights to open interesting lines of new research in the social sciences