Mechanical Response of He- Implanted Amorphous SiOC/ Crystalline Fe Nanolaminates

This study investigates the microstructural evolution and mechanical response of sputter-deposited amorphous silicon oxycarbide (SiOC)/crystalline Fe nanolaminates, a single layer SiOC film, and a single layer Fe film subjected to ion implantation at room temperature to obtain a maximum He concentration of 5 at. %. X-ray diffraction and transmission electron microscopy indicated no evidence of implantation-induced phase transformation or layer breakdown in the nanolaminates. Implantation resulted in the formation of He bubbles and an increase in the average size of the Fe grains in the individual Fe layers of the nanolaminates and the single layer Fe film, but the bubble density and grain size were found to be smaller in the former. By reducing the thicknesses of individual layers in the nanolaminates, bubble density and grain size were further decreased. No He bubbles were observed in the SiOC layers of the nanolaminates and the single layer SiOC film. Nanoindentation and scanning probe microscopy revealed an increase in the hardness of both single layer SiOC and Fe films after implantation. For the nanolaminates, changes in hardness were found to depend on the thicknesses of the individual layers, where reducing the layer thickness to 14 nm resulted in mitigation of implantation-induced hardening

Coupling of morphology to surface transport in ion-beam irradiated surfaces. I. Oblique incidence

We propose and study a continuum model for the dynamics of amorphizable surfaces undergoing ion-beam sputtering (IBS) at intermediate energies and oblique incidence. After considering the current limitations of more standard descriptions in which a single evolution equation is posed for the surface height, we overcome (some of) them by explicitly formulating the dynamics of the species that transport along the surface, and by coupling it to that of the surface height proper. In this we follow recent proposals inspired by ``hydrodynamic'' descriptions of pattern formation in aeolian sand dunes and ion-sputtered systems. From this enlarged model, and by exploiting the time-scale separation among various dynamical processes in the system, we derive a single height equation in which coefficients can be related to experimental parameters. This equation generalizes those obtained by previous continuum models and is able to account for many experimental features of pattern formation by IBS at oblique incidence, such as the evolution of the irradiation-induced amorphous layer, transverse ripple motion with non-uniform velocity, ripple coarsening, onset of kinetic roughening and other. Additionally, the dynamics of the full two-field model is compared with that of the effective interface equation.Comment: 23 pages, 14 figures. Movies of figures 6, 7, and 8 available at http://gisc.uc3m.es/~javier/Movies

Self-Organized Ordering of Nanostructures Produced by Ion-Beam Sputtering

We study the self-organized ordering of nanostructures produced by ion-beam sputtering (IBS) of targets amorphizing under irradiation. By introducing a model akin to models of pattern formation in aeolian sand dunes, we extend consistently the current continuum theory of erosion by IBS. We obtain new non-linear effects responsible for the in-plane ordering of the structures, whose strength correlates with the degree of ordering found in experiments. Our results highlight the importance of redeposition and surface viscous flow to this nanopattern formation process.Comment: 4 pages, 2 figure

Enhanced surveillance of invasive listeriosis in the Lombardy region, Italy, in the years 2006-2010 reveals major clones and an increase in serotype 1/2a.

Background Invasive listeriosis is a rare, life-threatening foodborne disease. Lombardy, an Italian region accounting for 16% of the total population, reported 55% of all listeriosis cases in the years 2006-2010. The aim of our study was to provide a snapshot of listeriosis epidemiology in this region after the implementation of a voluntary laboratory-based surveillance system. Methods We characterized by serotyping, pulsed-field gel electrophoresis, multilocus sequence typing and detection of epidemic clone markers, 134 isolates from 132 listeriosis cases, including 15 pregnancy-related cases, occurring in the years 2006-2010 in Lombardy. Demographic and clinical characteristics of cases have also been described. Results The mean age of non pregnancy-associated cases was 64.7\u2009years, with 55.9% of cases being older than 65\u2009years. Cases having no underlying medical conditions accounted for 11.6%. The all-cause fatality rate of 83 cases with a known survival outcome was 25.3%. Serotypes 1/2a and 4b comprised 52.2% and 38.8% of isolates, respectively. Seventy-three AscI pulsotypes and 25 sequence types assigned to 23 clonal complexes were recognized. Moreover, 53 (39.5%) isolates tested positive for the epidemic clone markers. Twelve molecular subtype clusters including at least three isolates were detected, with cluster 11 (1/2a/ST38) including 31 isolates identified during the entire study period. No outbreaks were notified to public health authorities during this period. Conclusions The findings of our study proved that epidemiology of listeriosis in Lombardy is characterized by a high prevalence of major clones and the increasing role of serotype 1/2a. Molecular subtyping is an essential tool in the epidemiology and surveillance of listeriosis. Rapid molecular cluster detection could alert about putative outbreaks, thus increasing the chance of detecting and inactivating routes of transmission

Nucleation and growth of platelets in hydrogen-ion-implanted silicon

H ion implantation into crystalline Si is known to result in the precipitation of planar defects in the form of platelets. Hydrogen-platelet formation is critical to the process that allows controlled cleavage of Si along the plane of the platelets and subsequent transfer and integration of thinly sliced Si with other substrates. Here we show that H-platelet formation is controlled by the depth of the radiation-induced damage and then develop a model that considers the influence of stress to correctly predict platelet orientation and the depth at which platelet nucleation density is a maximum. © 2005 American Institute of Physics

Mechanical Response of He- Implanted Amorphous SiOC/ Crystalline Fe Nanolaminates

This study investigates the microstructural evolution and mechanical response of sputter-deposited amorphous silicon oxycarbide (SiOC)/crystalline Fe nanolaminates, a single layer SiOC film, and a single layer Fe film subjected to ion implantation at room temperature to obtain a maximum He concentration of 5 at. %. X-ray diffraction and transmission electron microscopy indicated no evidence of implantation-induced phase transformation or layer breakdown in the nanolaminates. Implantation resulted in the formation of He bubbles and an increase in the average size of the Fe grains in the individual Fe layers of the nanolaminates and the single layer Fe film, but the bubble density and grain size were found to be smaller in the former. By reducing the thicknesses of individual layers in the nanolaminates, bubble density and grain size were further decreased. No He bubbles were observed in the SiOC layers of the nanolaminates and the single layer SiOC film. Nanoindentation and scanning probe microscopy revealed an increase in the hardness of both single layer SiOC and Fe films after implantation. For the nanolaminates, changes in hardness were found to depend on the thicknesses of the individual layers, where reducing the layer thickness to 14 nm resulted in mitigation of implantation-induced hardening

The road to developing economically feasible plans for green, comfortable and energy efficient buildings

Owing to the current challenges in energy and environmental crises, improving buildings, as one of the biggest concerns and contributors to these issues, is increasingly receiving attention from the world. Due to a variety of choices and situations for improving buildings, it is important to review the building performance optimization studies to find the proper solution. In this paper, these studies are reviewed by analyzing all the different key parameters involved in the optimization process, including the considered decision variables, objective functions, constraints, and case studies, along with the software programs and optimization algorithms employed. As the core literature, 44 investigations recently published are considered and compared. The current investigation provides sufficient information for all the experts in the building sector, such as architects and mechanical engineers. It is noticed that EnergyPlus and MATLAB have been employed more than other software for building simulation and optimization, respectively. In addition, among the nine different aspects that have been optimized in the literature, energy consumption, thermal comfort, and economic benefits are the first, second, and third most optimized, having shares of 38.6%, 22.7%, and 17%, respectively

The upcoming role of Artificial Intelligence (AI) for retinal and glaucomatous diseases

: In recent years, the role of artificial intelligence (AI) and deep learning (DL) models is attracting increasing global interest in the field of ophthalmology. DL models are considered the current state-of-art among the AI technologies. In fact, DL systems have the capability to recognize, quantify and describe pathological clinical features. Their role is currently being investigated for the early diagnosis and management of several retinal diseases and glaucoma. The application of DL models to fundus photographs, visual fields and optical coherence tomography (OCT) imaging has provided promising results in the early detection of diabetic retinopathy (DR), wet age-related macular degeneration (w-AMD), retinopathy of prematurity (ROP) and glaucoma. In this review we analyze the current evidence of AI applied to these ocular diseases, as well as discuss the possible future developments and potential clinical implications, without neglecting the present limitations and challenges in order to adopt AI and DL models as powerful tools in the everyday routine clinical practice

In vivo confinement promotes collective migration of neural crest cells

Collective cell migration is fundamental throughout development and in many diseases. Spatial confinement using micropatterns has been shown to promote collective cell migration in vitro, but its effect in vivo remains unclear. Combining computational and experimental approaches, we show that the in vivo collective migration of neural crest cells (NCCs) depends on such confinement. We demonstrate that confinement may be imposed by the spatiotemporal distribution of a nonpermissive substrate provided by versican, an extracellular matrix molecule previously proposed to have contrasting roles: barrier or promoter of NCC migration. We resolve the controversy by demonstrating that versican works as an inhibitor of NCC migration and also acts as a guiding cue by forming exclusionary boundaries. Our model predicts an optimal number of cells in a given confinement width to allow for directional migration. This optimum coincides with the width of neural crest migratory streams analyzed across different species, proposing an explanation for the highly conserved nature of NCC streams during development

integrated dynamic energy management for steel production

Abstract The steel industry is an important consumer of electrical energy having a significant impact on the electricity network and accounting to a significant part of production costs. Thus, there is the opportunity of closer cooperation between grid operators and steel industry to improve the power consumption prediction and actively contribute to a secure network operation. This paper aims to describe an overall dynamical approach for electricity demand monitoring and timely reactions to the grid situation, to avoid non flexible equipment disconnection, financial fines when deviating from energy contingent and contributing to the grid stability. Energy management, simulation, decision support procedures and process control tools will be integrated in an agent based system able to predict and manage power consumption