Multicomponent carbide thin films of (CrNbTaTiW)C (30–40at.% C) with different metal contents were deposited at different temperatures using non-reactive DC magnetron sputtering. The lattice ...distortion for the metal lattice was estimated to vary from about 3 to 5%. Most films crystallized in the cubic B1 structure but Ta/W-rich films deposited at 600°C exhibited a tetragonal distortion. X-ray diffraction results show that near-equimolar films exhibited a strong (111) texture. In contrast, Ta/W-rich films exhibited a shift from (111) to (100) texture at 450°C. The in-plane relationship was determined to MC(111)-12-1//Al2O3(001)110 with a lattice mismatch of about 11% along the Al2O3110 direction. A segregation of Cr to the grain boundaries was observed in all films. The microstructure was found to be the most important factor for high hardness. Less dense Nb-rich and near-equimolar films deposited at low temperatures exhibited the lowest hardness (12GPa), while very dense Ta/W-rich high temperature films were found to be the hardest (36GPa). No correlation was found between the lattice distortion and the hardness. Corrosion studies revealed that the multicomponent films exhibited excellent corrosion resistance, superior to that of a reference hyper-duplex stainless steel, in 1.0M HCl.
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•A novel multicomponent carbide ((CrNbTaTiW)C) has been deposited by magnetron sputtering.•Extremely hard multicomponent carbides can be deposited by tuning of the composition and deposition temperature.•The hardest film exhibits a tetragonal distortion of the fcc-based lattice not previously observed for carbides.•(CrNbTaTiW)C films show excellent corrosion resistance superior to commercially available hyper-duplex stainless steels.
The primary objective of the present study was to evaluate the concentrations and short and long-term excess mortality attributed to PM2.5, NO2, and O3 observed in ambient air of Ahvaz during March ...2014 to March 2017 period using the AirQ + software developed by the World Health Organization (WHO), which is updated in 2016 by WHO European Centre for Environment and Health. The hourly concentrations of PM2.5, O3, and NO2 measured at different regulatory monitoring network stations in Ahvaz city were obtained from the Department of Environment (DOE) of the city. Then, for various air quality monitoring stations, the 24-h average concentration of PM2.5, 1-h average of NO2 concentration, and maximum daily 8-h O3 concentrations were calculated using Excel 2010 software. When the maximum daily 8-h ozone means exceeding the value of 35, it was subtracted from 35 to calculate SOMO35 indicator for modeling. Validation of air quality data was performed according to the Aphekom and WHO's methodologies for health impact assessment of air pollution. Year-specific city population and baseline incidence of the health outcomes were obtained. The three-year averages of PM2.5, NO2, and O3 concentrations were 68.95 (±39.86) μg/m3, 135.90 (±47.82) μg/m3, and 38.63 (±12.83) parts-per-billion-volume (ppbv), respectively. SOMO35 values of ozone were 6596.66, 3411.78, and 470.88 ppbv in 2014–2015, 2015–2016, and 2016-2017 years, respectively. The AP and number of natural deaths due to NO2 were higher than PM2.5 except the last year (2016–2017), causing about 39.18%, 40.73%, and 14.39% of deaths within the first, the second, and the third year, respectively. However, for the last year, the natural mortality for PM2.5 was higher than NO2 (34.46% versus 14.39%). The total number of natural mortality caused by PM2.5 and NO2 in all years was 4061 and 4391, respectively. A significant number of deaths was estimated to be attributed to the given air pollutants. It can be concluded that by designing and implementing air pollution control strategies and actions, both health effects and economic losses will be prevented.
•Attributed short and long term morbidity for PM2.5, NO2 and O3 was assessed.•Year-specific city population and baseline incidence of the health outcomes were obtained.•Number of death cases for IHD, COPD, lung cancer, and ALRI attributed to PM2.5 was estimated.•The attributable health effects of ozone were low and negligible.
Qualitative content analysis and other ‘standardised’ methods are sometimes considered to be technical tools used for basic, superficial, and simple sorting of text, and their results lack depth, ...scientific rigour, and evidence. To strengthen the trustworthiness of qualitative content analyses, we focus on abstraction and interpretation during the analytic process. To our knowledge, descriptions of these concepts are sparse; this paper therefore aims to elaborate on and exemplify the distinction and relation between abstraction and interpretation during the different phases of the process of qualitative content analysis. We address the relations between abstraction and interpretation when selecting, condensing, and coding meaning units and creating categories and themes on various levels. The examples used are based on our experiences of teaching and supervising students at various levels. We also highlight the phases of de-contextualisation and re-contextualisation in describing the analytic process. We argue that qualitative content analysis can be both descriptive and interpretative. When the data allow interpretations of the latent content, qualitative content analysis reveals both depth and meaning in participants’ utterances.
In the current research, an innovative biomass-based energy system is proposed for power and desalinated water production. The plant's primary components consist of a gasifier, a compressor, a heat ...exchanger, a gas turbine, a combustion chamber, and a Multi-effect desalination with thermal vapor compression (MED-TVC) unit. A comprehensive thermodynamic and thermoeconomic assessment is conducted on the proposed system. Besides, a parametric study is conducted to determine the effect of primary decision variables on the system performance. Multiple objective optimization using the multi-objective grey wolf optimizer (MOGWO) algorithm is applied to obtain the optimal solution with the highest exergy efficiency and the minimum amount of total cost rate. The artificial neural network (ANN) has an intermediary role in the optimization process to decrease computational time and enhance optimization speed. The relation between the objective function and decision variables is investigated, employing ANN to determine the energy system's optimum point. The generation rate for power and freshwater at the optimal point is equal to 5127 kW and 38.6 kg/s, respectively. Besides, the optimum value of the exergy efficiency and total cost rate are computed as 15.61% and 206.78 $/h, respectively. The results also revealed that the number of effects of the desalination unit does not affect the carbon dioxide emissions. Moreover, the scatter distribution of the key decision variable indicates that the air compressor pressure ratio is not a sensible variable, and their optimum points are distributed across the entire domain.
•To propose a novel integrated biomass system for electricity generation.•To apply energy, exergy, and exergo-economic analysis of the system.•To apply a multi-objective genetic algorithm optimization to the proposed system.•To form a Perto curve to show cost and exergy efficiency objective functions.•Optimizing the plant utilizing artificial neural network (ANN) and MOGWO.
Genomic data provide an excellent resource to improve understanding of retrovirus evolution and the complex relationships among viruses and their hosts. In conjunction with broad-scale in silico ...screening of vertebrate genomes, this resource offers an opportunity to complement data on the evolution and frequency of past retroviral spread and so evaluate future risks and limitations for horizontal transmission between different host species. Here, we develop a methodology for extracting phylogenetic signal from large endogenous retrovirus (ERV) datasets by collapsing information to facilitate broad-scale phylogenomics across a wide sample of hosts. Starting with nearly 90,000 ERVs from 60 vertebrate host genomes, we construct phylogenetic hypotheses and draw inferences regarding the designation, host distribution, origin, and transmission of the Gammaretrovirus genus and associated class I ERVs. Our results uncover remarkable depths in retroviral sequence diversity, supported within a phylogenetic context. This finding suggests that current infectious exogenous retrovirus diversity may be underestimated, adding credence to the possibility that many additional exogenous retroviruses may remain to be discovered in vertebrate taxa. We demonstrate a history of frequent horizontal interorder transmissions from a rodent reservoir and suggest that rats may have acted as important overlooked facilitators of gammaretrovirus spread across diverse mammalian hosts. Together, these results demonstrate the promise of the methodology used here to analyze large ERV datasets and improve understanding of retroviral evolution and diversity for utilization in wider applications.
Microbial hydrogen (H2) cycling underpins the diversity and functionality of diverse anoxic ecosystems. Among the three evolutionarily distinct hydrogenase superfamilies responsible, FeFe ...hydrogenases were thought to be restricted to bacteria and eukaryotes. Here, we show that anaerobic archaea encode diverse, active, and ancient lineages of FeFe hydrogenases through combining analysis of existing and new genomes with extensive biochemical experiments. FeFe hydrogenases are encoded by genomes of nine archaeal phyla and expressed by H2-producing Asgard archaeon cultures. We report an ultraminimal hydrogenase in DPANN archaea that binds the catalytic H-cluster and produces H2. Moreover, we identify and characterize remarkable hybrid complexes formed through the fusion of FeFe and NiFe hydrogenases in ten other archaeal orders. Phylogenetic analysis and structural modeling suggest a deep evolutionary history of hybrid hydrogenases. These findings reveal new metabolic adaptations of archaea, streamlined H2 catalysts for biotechnological development, and a surprisingly intertwined evolutionary history between the two major H2-metabolizing enzymes.
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•Archaea from nine different phyla encode structurally diverse FeFe hydrogenases•Active ultraminimal FeFe hydrogenases are produced by uncultured DPANN archaea•Ancient hybrid FeFe and NiFe hydrogenases are encoded by diverse archaea•Hydrogen-producing Asgard archaeal cultures express FeFe hydrogenases
Archaea produce FeFe hydrogenases, previously thought to be only made by bacteria and eukaryotes. These enzymes are remarkably diverse, spanning ultraminimal fermentative enzymes to ancient hybrid complexes, and have significant biotechnological potential.
Abstract
There has been a rapid rise in interest regarding the advantages of support materials to protect and immobilise molecular catalysts for the carbon dioxide reduction reaction (CO
2
RR) in ...order to overcome the weaknesses of many well‐known catalysts in terms of their stability and selectivity. In this Review, the state of the art of different catalyst‐support systems for the CO
2
RR is discussed with the intention of leading towards standard benchmarking for comparison of such systems across the most relevant supports and immobilisation strategies, taking into account these multiple pertinent metrics, and also enabling clearer consideration of the necessary steps for further progress. The most promising support systems are described, along with a final note on the need for developing more advanced experimental and computational techniques to aid the rational design principles that are prerequisite to prospective industrial upscaling.
In this paper, we use deep feedforward artificial neural networks to approximate solutions to partial differential equations in complex geometries. We show how to modify the backpropagation algorithm ...to compute the partial derivatives of the network output with respect to the space variables which is needed to approximate the differential operator. The method is based on an ansatz for the solution which requires nothing but feedforward neural networks and an unconstrained gradient based optimization method such as gradient descent or a quasi-Newton method.
We show an example where classical mesh based methods cannot be used and neural networks can be seen as an attractive alternative. Finally, we highlight the benefits of deep compared to shallow neural networks and device some other convergence enhancing techniques.
A novel MED-based desalination system for low-grade heat sources with a temperature between 65 °C and 90 °C has been proposed. Low-grade heat-driven desalination systems are of the most important ...methods for increasing energy efficiency and assisting the environment along with alleviating the water scarcity problem. The new proposed system is known as cascade multi-effect distillation (CMED). It is designed based on multi-step heat extraction from the heat source fluid (HSF). Multi-step heat absorption helps to form two arrays of MED effects and to utilize two boosters to achieve better performance. The advantage of this system is less complexity (for example, lower vapor injection), and improved performance along with reduced electricity consumption in comparison with the most recent MED-based configurations, including flash boosted MED (FB-MED) and distributed boosted MED (DBMED). The results show that the CMED’s production rate is increased on average by 15.5% compared to FB-MED, and up to 7.3% relative to DBMED. The normalized pumping power consumption (NPPC) is dropped by 14.5% and 11.5% on average compared to FB-MED and DBMED, respectively. Also, the specific capital cost is reduced by about 1.15% and 0.80% on average.
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