Room temperature magneto-optic effect in silicon light-emitting diodes

In weakly spin-orbit coupled materials, the spin-selective nature of recombination can give rise to large magnetic-field effects, for example on electro-luminescence from molecular semiconductors. While silicon has weak spin-orbit coupling, observing spin-dependent recombination through magneto-electroluminescence is challenging due to the inefficiency of emission due to silicon's indirect band-gap, and to the difficulty in separating spin-dependent phenomena from classical magneto-resistance effects. Here we overcome these challenges to measure magneto-electroluminescence in silicon light-emitting diodes fabricated via gas immersion laser doping. These devices allow us to achieve efficient emission while retaining a well-defined geometry thus suppressing classical magnetoresistance effects to a few percent. We find that electroluminescence can be enhanced by up to 300\% near room temperature in a seven Tesla magnetic field showing that the control of the spin degree of freedom can have a strong impact on the efficiency of silicon LEDs

Silicon Superconducting Quantum Interference Device

We have studied a Superconducting Quantum Interference SQUID device made from a single layer thin film of superconducting silicon. The superconducting layer is obtained by heavily doping a silicon wafer with boron atoms using the Gas Immersion Laser Doping (GILD) technique. The SQUID device is composed of two nano-bridges (Dayem bridges) in a loop and shows magnetic flux modulation at low temperature and low magnetic field. The overall behavior shows very good agreement with numerical simulations based on the Ginzburg-Landau equations.Comment: Published in Applied Physics Letters (August 2015

STEM analysis of deformation and B distribution in nanosecond laser ultra-doped Si1−x_{1-x} Bx_x

We report on the structural properties of highly B-doped silicon (> 2 at. %) realised by nanosecond laser doping. We investigate the crystalline quality, deformation and B distribution profile of the doped layer by STEM analysis followed by HAADF contrast studies and GPA, and compare the results to SIMS analyses and Hall measurements. When increasing the active B concentration above 4.3 at.%, the fully strained, perfectly crystalline, Si:B layer starts showing dislocations and stacking faults. These only disappear around 8 at.% when the Si:B layer is well accommodated to the substrate. When increasing B incorporation, we increasingly observe small precipitates, filaments with higher active B concentration and stacking faults. At the highest concentrations studied, large precipitates form, related to the decrease of active B concentration. The structural deformation, defect type and concentration, and active B distribution are connected to the initial increase and subsequent gradual loss of superconductivity

Subkelvin tunneling spectroscopy showing Bardeen-Cooper-Schrieffer superconductivity in heavily boron-doped silicon epilayers

Scanning tunneling spectroscopies in the subKelvin temperature range were performed on superconducting Silicon epilayers doped with Boron in the atomic percent range. The resulting local differential conductance behaved as expected for a homogeneous superconductor, with an energy gap dispersion below +/- 10%. The spectral shape, the amplitude and temperature dependence of the superconductivity gap follow the BCS model, bringing further support to the hypothesis of a hole pairing mechanism mediated by phonons in the weak coupling limit.Comment: 4 pages, 3 figure

Killing them softly:managing pathogen polymorphism and virulence in spatially variable environments

Understanding why pathogen populations are genetically variable is vital because genetic variation fuels evolution, which often hampers disease control efforts. Here I argue that classical models of evolution in spatially variable environments – specifically, models of hard and soft selection – provide a useful framework to understand the maintenance of pathogen polymorphism and the evolution of virulence. First, the similarities between models of hard and soft selection and pathogen life cycles are described, highlighting how the type and timing of pathogen control measures impose density regulation that may affect both the level of pathogen polymorphism and virulence. The article concludes with an outline of potential lines of future theoretical and experimental work

Thickness dependence of the superconducting critical temperature in heavily doped Si:B epilayers

International audienceWe report on the superconducting properties of a series of heavily doped Si:B epilayers grown by gas immersion laser doping with boron content (nB) ranging from ∼3 × 1020 cm−3 to ∼6 × 1021cm−3 and thickness (d) varying between ∼20 nm and ∼210 nm. We show that superconductivity is only observed for nB values exceeding a threshold value (nc,S ) which scales as nc,S ∝ 1/d. The critical temperature (Tc) then rapidly increases with nB, largely exceeding the theoretical values which can be estimated by introducing the electron-phonon coupling constant (λe-ph) deduced from ab initio calculations into the McMillan equation. Surprisingly Tc(nB,d) is fully determined by the boron dose (nB × d) and can be well approximated by a simple Tc(nB,d) ≈ Tc,0[1 − A/(nB.d)] law, with Tc,0 ∼ 750 mK and A ∼ 8(±1) × 1015 cm−2

Carbon nanotubes adhesion and nanomechanical behavior from peeling force spectroscopy

Applications based on Single Walled Carbon Nanotube (SWNT) are good example of the great need to continuously develop metrology methods in the field of nanotechnology. Contact and interface properties are key parameters that determine the efficiency of SWNT functionalized nanomaterials and nanodevices. In this work we have taken advantage of a good control of the SWNT growth processes at an atomic force microscope (AFM) tip apex and the use of a low noise (1E-13 m/rtHz) AFM to investigate the mechanical behavior of a SWNT touching a surface. By simultaneously recording static and dynamic properties of SWNT, we show that the contact corresponds to a peeling geometry, and extract quantities such as adhesion energy per unit length, curvature and bending rigidity of the nanotube. A complete picture of the local shape of the SWNT and its mechanical behavior is provided

Population-Wide Emergence of Antiviral Resistance during Pandemic Influenza

Background: The emergence of neuraminidase inhibitor resistance has raised concerns about the prudent use of antiviral drugs in response to the next influenza pandemic. While resistant strains may initially emerge with compromised viral fitness, mutations that largely compensate for this impaired fitness can arise. Understanding the extent to which these mutations affect the spread of disease in the population can have important implications for developing pandemic plans. Methodology/Principal Findings: By employing a deterministic mathematical model, we investigate possible scenarios for the emergence of population-wide resistance in the presence of antiviral drugs. The results show that if the treatment level (the fraction of clinical infections which receives treatment) is maintained constant during the course of the outbreak, there is an optimal level that minimizes the final size of the pandemic. However, aggressive treatment above the optimal level can substantially promote the spread of highly transmissible resistant mutants and increase the total number of infections. We demonstrate that resistant outbreaks can occur more readily when the spread of disease is further delayed by applying other curtailing measures, even if treatment levels are kept modest. However, by changing treatment levels over the course of the pandemic, it is possible to reduce the final size of the pandemic below the minimum achieved at the optimal constant level. This reduction can occur with low treatment levels during the early stages of the pandemic, followed by a sharp increase in drug-use before the virus becomes widely spread. Conclusions/Significance: Our findings suggest that an adaptive antiviral strategy with conservative initial treatment levels, followed by a timely increase in the scale of drug-use, can minimize the final size of a pandemic while preventing large outbreaks of resistant infections

Strong Neutral Spatial Effects Shape Tree Species Distributions across Life Stages at Multiple Scales

Traditionally, ecologists use lattice (regional summary) count data to simulate tree species distributions to explore species coexistence. However, no previous study has explicitly compared the difference between using lattice count and basal area data and analyzed species distributions at both individual species and community levels while simultaneously considering the combined scenarios of life stage and scale. In this study, we hypothesized that basal area data are more closely related to environmental variables than are count data because of strong environmental filtering effects. We also address the contribution of niche and the neutral (i.e., solely dependent on distance) factors to species distributions. Specifically, we separately modeled count data and basal area data while considering life stage and scale effects at the two levels with simultaneous autoregressive models and variation partitioning. A principal coordinates of neighbor matrix (PCNM) was used to model neutral spatial effects at the community level. The explained variations of species distribution data did not differ significantly between the two types of data at either the individual species level or the community level, indicating that the two types of data can be used nearly identically to model species distributions. Neutral spatial effects represented by spatial autoregressive parameters and the PCNM eigenfunctions drove species distributions on multiple scales, different life stages and individual species and community levels in this plot. We concluded that strong neutral spatial effects are the principal mechanisms underlying the species distributions and thus shape biodiversity spatial patterns

Antiviral resistance during pandemic influenza: implications for stockpiling and drug use

<p>Abstract</p> <p>Background</p> <p>The anticipated extent of antiviral use during an influenza pandemic can have adverse consequences for the development of drug resistance and rationing of limited stockpiles. The strategic use of drugs is therefore a major public health concern in planning for effective pandemic responses.</p> <p>Methods</p> <p>We employed a mathematical model that includes both sensitive and resistant strains of a virus with pandemic potential, and applies antiviral drugs for treatment of clinical infections. Using estimated parameters in the published literature, the model was simulated for various sizes of stockpiles to evaluate the outcome of different antiviral strategies.</p> <p>Results</p> <p>We demonstrated that the emergence of highly transmissible resistant strains has no significant impact on the use of available stockpiles if treatment is maintained at low levels or the reproduction number of the sensitive strain is sufficiently high. However, moderate to high treatment levels can result in a more rapid depletion of stockpiles, leading to run-out, by promoting wide-spread drug resistance. We applied an antiviral strategy that delays the onset of aggressive treatment for a certain amount of time after the onset of the outbreak. Our results show that if high treatment levels are enforced too early during the outbreak, a second wave of infections can potentially occur with a substantially larger magnitude. However, a timely implementation of wide-scale treatment can prevent resistance spread in the population, and minimize the final size of the pandemic.</p> <p>Conclusion</p> <p>Our results reveal that conservative treatment levels during the early stages of the outbreak, followed by a timely increase in the scale of drug-use, will offer an effective strategy to manage drug resistance in the population and avoid run-out. For a 1918-like strain, the findings suggest that pandemic plans should consider stockpiling antiviral drugs to cover at least 20% of the population.</p