Liquid assisted plasma enhanced chemical vapour deposition with a non-thermal plasma jet at atmospheric pressure

The present study introduces a process for the synthesis of functional films onto substrates directly from the liquid phase. The reported method is based on the initialization of the synthesis by means of an atmospheric pressure plasma jet operating with argon above a thin liquid film of the starting material. The process is demonstrated by the formation of a thin, solid SiOx film from siloxane-based liquid precursors. Changes in the chemical properties of the precursor were studied in-situ during the polymerization process on the diamond crystal by using Fourier transform infrared spectroscopy The elemental composition of the SiOxCy films was analyzed by X-ray photoelectron spectroscopy (XPS). Furthermore, XPS was applied to study the effect of post-annealing processes on the composition of the films. The obtained deposits exhibit a low concentration of carbon groups. The amount of hydroxyl groups and interstitial water can be reduced significantly by post-process annealing of the films

Liquid assisted plasma enhanced chemical vapour deposition with a non-thermal plasma jet at atmospheric pressure

The present study introduces a process for the synthesis of functional films onto substrates directly from the liquid phase. The reported method is based on the initialization of the synthesis by means of an atmospheric pressure plasma jet operating with argon above a thin liquid film of the starting material. The process is demonstrated by the formation of a thin, solid SiOx film from siloxane-based liquid precursors. Changes in the chemical properties of the precursor were studied in-situ during the polymerization process on the diamond crystal by using Fourier transform infrared spectroscopy The elemental composition of the SiOxCy films was analyzed by X-ray photoelectron spectroscopy (XPS). Furthermore, XPS was applied to study the effect of post-annealing processes on the composition of the films. The obtained deposits exhibit a low concentration of carbon groups. The amount of hydroxyl groups and interstitial water can be reduced significantly by post-process annealing of the films

Very High Spatial Resolution Soil Moisture Observation of Heterogeneous Subarctic Catchment Using Nonlocal Averaging and Multitemporal SAR Data

A soil moisture estimation method was developed for Sentinel-1 synthetic aperture radar (SAR) ground range detected high resolution (GRDH) data to analyze moisture conditions in a gently undulating and heterogeneous subarctic area containing forests, wetlands, and open orographic tundra. In order to preserve the original 10-m pixel spacing, PIMSAR (pixel-based multitemporal nonlocal averaging) nonlocal mean filtering was applied. It was guided by multitemporal statistics of SAR images in the area. The gradient boosted trees (GBT) machine learning method was used for the soil moisture algorithm development. Discrete and continuous in situ soil moisture values were used for training and validation of the algorithm. For surface soil moisture, the root mean square error (RMSE) of the method was 6.5% and 8.8% for morning and evening images, respectively. The corresponding maximum errors were 34.1% and 33.8%. The pixelwise sensitivity to the training set and method choice was estimated as the variance of the soil moisture values derived using the algorithms for the three best methods with respect to the criteria: the smallest maximum error, the smallest RMSE value, and the highest coefficient of determination (R-2) value. It was, on average, 6.3% with a standard deviation of 5.7%. Our approach successfully produced instantaneous high-resolution soil moisture estimates on daily basis for the subarctic landscape and can further be applied to various hydrological, biogeochemical, and management purposes.Peer reviewe

Very High Spatial Resolution Soil Moisture Observation of Heterogeneous Subarctic Catchment Using Nonlocal Averaging and Multitemporal SAR Data

A soil moisture estimation method was developed for Sentinel-1 synthetic aperture radar (SAR) ground range detected high resolution (GRDH) data to analyze moisture conditions in a gently undulating and heterogeneous subarctic area containing forests, wetlands, and open orographic tundra. In order to preserve the original 10-m pixel spacing, PIMSAR (pixel-based multitemporal nonlocal averaging) nonlocal mean filtering was applied. It was guided by multitemporal statistics of SAR images in the area. The gradient boosted trees (GBT) machine learning method was used for the soil moisture algorithm development. Discrete and continuous in situ soil moisture values were used for training and validation of the algorithm. For surface soil moisture, the root mean square error (RMSE) of the method was 6.5% and 8.8% for morning and evening images, respectively. The corresponding maximum errors were 34.1% and 33.8%. The pixelwise sensitivity to the training set and method choice was estimated as the variance of the soil moisture values derived using the algorithms for the three best methods with respect to the criteria: the smallest maximum error, the smallest RMSE value, and the highest coefficient of determination (R-2) value. It was, on average, 6.3% with a standard deviation of 5.7%. Our approach successfully produced instantaneous high-resolution soil moisture estimates on daily basis for the subarctic landscape and can further be applied to various hydrological, biogeochemical, and management purposes.Peer reviewe

Making Sense of Complex Carbon and Metal/Carbon Systems by Secondary Electron Hyperspectral Imaging

Carbon and carbon/metal systems with a multitude of functionalities are ubiquitous in new technologies but understanding on the nanoscale remains elusive due to their affinity for interaction with their environment and limitations in available characterization techniques. This paper introduces a spectroscopic technique and demonstrates its capacity to reveal chemical variations of carbon. The effectiveness of this approach is validated experimentally through spatially averaging spectroscopic techniques and using Monte Carlo modeling. Characteristic spectra shapes and peak positions for varying contributions of sp2-like or sp3-like bond types and amorphous hydrogenated carbon are reported under circumstances which might be observed on highly oriented pyrolytic graphite (HOPG) surfaces as a result of air or electron beam exposure. The spectral features identified above are then used to identify the different forms of carbon present within the metallic films deposited from reactive organometallic inks. While spectra for metals is obtained in dedicated surface science instrumentation, the complex relations between carbon and metal species is only revealed by secondary electron (SE) spectroscopy and SE hyperspectral imaging obtained in a state-of-the-art scanning electron microscope (SEM). This work reveals the inhomogeneous incorporation of carbon on the nanoscale but also uncovers a link between local orientation of metallic components and carbon form

Nanostructures for Achieving Selective Properties of a Thermophotovoltaic Emitter

This paper focuses on the research and development of a suitable method for creating a selective emitter for the visible and near-infrared region to be able to work optimally together with silicon photovoltaic cells in a thermophotovoltaic system. The aim was to develop a new method to create very fine structures beyond the conventional standard (nanostructures), which will increase the emissivity of the base material for it to match the needs of a selective emitter for the VIS and NIR region. Available methods were used to create the nanostructures, from which we eliminated all unsuitable methods; for the selected method, we established the optimal procedure and parameters for their creation. The development of the emitter nanostructures included the necessary substrate pretreatments, where great emphasis was placed on material purity and surface roughness. Tungsten was purposely chosen as the main material for the formation of the nanostructures; we verified the effect of the formed structure on the resulting emissivity. This work presents a new method for the formation of nanostructures, which are not commonly formed in such fineness; by this, it opens the way to new possibilities for achieving the desired selectivity of the thermophotovoltaic emitter

Subarctic catchment water storage and carbon cycling – Leading the way for future studies using integrated datasets at Pallas, Finland

Subarctic ecohydrological processes are changing rapidly, but detailed and integrated ecohydrological investigations are not as widespread as necessary. We introduce an integrated research catchment site (Pallas) for atmosphere, ecosystems, and ecohydrology studies in subarctic conditions in Finland that can be used for a new set of comparative catchment investigations. The Pallas site provides unique observational data and high-intensity field measurement datasets over long periods. The infrastructure for atmosphere- to landscape-scale research in ecosystem processes in a subarctic landscape has recently been complemented with detailed ecohydrological measurements. We identify three dominant processes in subarctic ecohydrology: (a) strong seasonality drives ecohydrological regimes, (b) limited dynamic storage causes rapid stream response to water inputs (snowmelt and intensive storms), and (c) hydrological state of the system regulates catchment-scale dissolved carbon dynamics and greenhouse (GHG) fluxes. Surface water and groundwater interactions play an important role in regulating catchment-scale carbon balances and ecosystem respiration within subarctic peatlands, particularly their spatial variability in the landscape. Based on our observations from Pallas, we highlight key research gaps in subarctic ecohydrology and propose several ways forward. We also demonstrate that the Pallas catchment meets the need for sustaining and pushing the boundaries of critical long-term integrated ecohydrological research in high-latitude environments.Peer reviewe

Making Sense of Complex Carbon and Metal/Carbon Systems by Secondary Electron Hyperspectral Imaging

Carbon and carbon/metal systems with a multitude of functionalities are ubiquitous in new technologies but understanding on the nanoscale remains elusive due to their affinity for interaction with their environment and limitations in available characterization techniques. This paper introduces a spectroscopic technique and demonstrates its capacity to reveal chemical variations of carbon. The effectiveness of this approach is validated experimentally through spatially averaging spectroscopic techniques and using Monte Carlo modeling. Characteristic spectra shapes and peak positions for varying contributions of sp2-like or sp3-like bond types and amorphous hydrogenated carbon are reported under circumstances which might be observed on highly oriented pyrolytic graphite (HOPG) surfaces as a result of air or electron beam exposure. The spectral features identified above are then used to identify the different forms of carbon present within the metallic films deposited from reactive organometallic inks. While spectra for metals is obtained in dedicated surface science instrumentation, the complex relations between carbon and metal species is only revealed by secondary electron (SE) spectroscopy and SE hyperspectral imaging obtained in a state-of-the-art scanning electron microscope (SEM). This work reveals the inhomogeneous incorporation of carbon on the nanoscale but also uncovers a link between local orientation of metallic components and carbon form

Global, regional, and national burden of Alzheimer's disease and other dementias, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016.

BACKGROUND: The number of individuals living with dementia is increasing, negatively affecting families, communities, and health-care systems around the world. A successful response to these challenges requires an accurate understanding of the dementia disease burden. We aimed to present the first detailed analysis of the global prevalence, mortality, and overall burden of dementia as captured by the Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study 2016, and highlight the most important messages for clinicians and neurologists. METHODS: GBD 2016 obtained data on dementia from vital registration systems, published scientific literature and surveys, and data from health-service encounters on deaths, excess mortality, prevalence, and incidence from 195 countries and territories from 1990 to 2016, through systematic review and additional data-seeking efforts. To correct for differences in cause of death coding across time and locations, we modelled mortality due to dementia using prevalence data and estimates of excess mortality derived from countries that were most likely to code deaths to dementia relative to prevalence. Data were analysed by standardised methods to estimate deaths, prevalence, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs; computed as the sum of YLLs and YLDs), and the fractions of these metrics that were attributable to four risk factors that met GBD criteria for assessment (high body-mass index [BMI], high fasting plasma glucose, smoking, and a diet high in sugar-sweetened beverages). FINDINGS: In 2016, the global number of individuals who lived with dementia was 43·8 million (95% uncertainty interval [UI] 37·8-51·0), increased from 20.2 million (17·4-23·5) in 1990. This increase of 117% (95% UI 114-121) contrasted with a minor increase in age-standardised prevalence of 1·7% (1·0-2·4), from 701 cases (95% UI 602-815) per 100 000 population in 1990 to 712 cases (614-828) per 100 000 population in 2016. More women than men had dementia in 2016 (27·0 million, 95% UI 23·3-31·4, vs 16.8 million, 14.4-19.6), and dementia was the fifth leading cause of death globally, accounting for 2·4 million (95% UI 2·1-2·8) deaths. Overall, 28·8 million (95% UI 24·5-34·0) DALYs were attributed to dementia; 6·4 million (95% UI 3·4-10·5) of these could be attributed to the modifiable GBD risk factors of high BMI, high fasting plasma glucose, smoking, and a high intake of sugar-sweetened beverages. INTERPRETATION: The global number of people living with dementia more than doubled from 1990 to 2016, mainly due to increases in population ageing and growth. Although differences in coding for causes of death and the heterogeneity in case-ascertainment methods constitute major challenges to the estimation of the burden of dementia, future analyses should improve on the methods for the correction of these biases. Until breakthroughs are made in prevention or curative treatment, dementia will constitute an increasing challenge to health-care systems worldwide