Phase formation and thermal stability of ultrathin nickel-silicides on Si(100)

The solid-state reaction and agglomeration of thin nickel-silicide films was investigated from sputter deposited nickel films (1-10 nm) on silicon-on-insulator (100) substrates. For typical anneals at a ramp rate of 3 degrees C/s, 5-10 nm Ni films react with silicon and form NiSi, which agglomerates at 550-650 degrees C, whereas films with a thickness of 3.7 nm of less were found to form an epitaxylike nickel-silicide layer. The resulting films show an increased thermal stability with a low electrical resistivity up to 800 degrees C

On the growth kinetics of Ni(Pt) silicide thin films

We report on the effect of Pt on the growth kinetics of δ-Ni2Si and Ni 1−xPtxSi thin films formed by solid phase reaction of a Ni(Pt) alloyed thin film on Si(100). The study was performed by real-time Rutherford backscattering spectrometry examining the silicide growth rates for initial Pt concentrations of 0, 1, 3, 7, and 10 at. % relative to the Ni content. Pt was found to exert a drastic effect on the growth kinetics of both phases. δ-Ni2Si growth is slowed down tremendously, which results in the simultaneous growth of this phase with Ni 1−xPtxSi. Activation energies extracted for the Ni 1−xPtxSi growth process exhibit an increase from Ea = 1.35 ± 0.06 eV for binary NiSi to Ea = 2.7 ± 0.2 eV for Ni 1−xPtxSi with an initial Pt concentration of 3 at. %. Further increasing the Pt content to 10 at. % merely increases the activation energy for Ni 1−xPtxSi growth to Ea = 3.1 ± 0.5 eV

Stratification of hospitalized COVID-19 patients into clinical severity progression groups by immuno-phenotyping and machine learning

Quantitative or qualitative differences in immunity may drive clinical severity in COVID-19. Although longitudinal studies to record the course of immunological changes are ample, they do not necessarily predict clinical progression at the time of hospital admission. Here we show, by a machine learning approach using serum pro-inflammatory, anti-inflammatory and anti-viral cytokine and anti-SARS-CoV-2 antibody measurements as input data, that COVID-19 patients cluster into three distinct immune phenotype groups. These immune-types, determined by unsupervised hierarchical clustering that is agnostic to severity, predict clinical course. The identified immune-types do not associate with disease duration at hospital admittance, but rather reflect variations in the nature and kinetics of individual patient's immune response. Thus, our work provides an immune-type based scheme to stratify COVID-19 patients at hospital admittance into high and low risk clinical categories with distinct cytokine and antibody profiles that may guide personalized therapy. Developing predictive methods to identify patients with high risk of severe COVID-19 disease is of crucial importance. Authors show here that by measuring anti-SARS-CoV-2 antibody and cytokine levels at the time of hospital admission and integrating the data by unsupervised hierarchical clustering/machine learning, it is possible to predict unfavourable outcome

Conservation Planning for Ecosystem Services

Despite increasing attention to the human dimension of conservation projects, a rigorous, systematic methodology for planning for ecosystem services has not been developed. This is in part because flows of ecosystem services remain poorly characterized at local-to-regional scales, and their protection has not generally been made a priority. We used a spatially explicit conservation planning framework to explore the trade-offs and opportunities for aligning conservation goals for biodiversity with six ecosystem services (carbon storage, flood control, forage production, outdoor recreation, crop pollination, and water provision) in the Central Coast ecoregion of California, United States. We found weak positive and some weak negative associations between the priority areas for biodiversity conservation and the flows of the six ecosystem services across the ecoregion. Excluding the two agriculture-focused services—crop pollination and forage production—eliminates all negative correlations. We compared the degree to which four contrasting conservation network designs protect biodiversity and the flow of the six services. We found that biodiversity conservation protects substantial collateral flows of services. Targeting ecosystem services directly can meet the multiple ecosystem services and biodiversity goals more efficiently but cannot substitute for targeted biodiversity protection (biodiversity losses of 44% relative to targeting biodiversity alone). Strategically targeting only biodiversity plus the four positively associated services offers much promise (relative biodiversity losses of 7%). Here we present an initial analytical framework for integrating biodiversity and ecosystem services in conservation planning and illustrate its application. We found that although there are important potential trade-offs between conservation for biodiversity and for ecosystem services, a systematic planning framework offers scope for identifying valuable synergies

Techno-Ecological Synergy: A Framework for Sustainable Engineering

Even though the importance of ecosystems in sustaining all human activities is well-known, methods for sustainable engineering fail to fully account for this role of nature. Most methods account for the demand for ecosystem services, but almost none account for the supply. Incomplete accounting of the very foundation of human well-being can result in perverse outcomes from decisions meant to enhance sustainability and lost opportunities for benefiting from the ability of nature to satisfy human needs in an economically and environmentally superior manner. This paper develops a framework for understanding and designing synergies between technological and ecological systems to encourage greater harmony between human activities and nature. This framework considers technological systems ranging from individual processes to supply chains and life cycles, along with corresponding ecological systems at multiple spatial scales ranging from local to global. The demand for specific ecosystem services is determined from information about emissions and resource use, while the supply is obtained from information about the capacity of relevant ecosystems. Metrics calculate the sustainability of individual ecosystem services at multiple spatial scales and help define necessary but not sufficient conditions for local and global sustainability. Efforts to reduce ecological overshoot encourage enhancement of life cycle efficiency, development of industrial symbiosis, innovative designs and policies, and ecological restoration, thus combining the best features of many existing methods. Opportunities for theoretical and applied research to make this framework practical are also discussed