Mechanistic insights into the reversible lithium storage in an open porous carbon via metal cluster formation in all solid-state batteries

Porous carbons are promising anode materials for next generation lithium batteries due to their large lithium storage capacities. However, their high voltage slope during lithiation and delithiation as well as capacity fading due to intense formation of solid electrolyte interphase (SEI) limit their gravimetric and volumetric energy densities. Herein we compare a microporous carbide-derived carbon material (MPC) as promising future anode for all solid-state batteries with a commercial high-performance hard carbon anode. The MPC obtains high and reversible lithiation capacities of 1000 mAh g−1carbon in half-cells exhibiting an extended plateau region near 0 V vs. Li/Li+ preferable for full-cell application. The well-defined micro porosity of the MPC with a specific surface area of >1500 m2 g−1 combines well with the argyrodite-type electrolyte (Li6PS5Cl) suppressing extensive SEI formation to deliver high coulombic efficiencies. Preliminary full-cell measurements vs. nickel-rich NMC-cathodes (LiNi0.9Co0.05Mn0.05O2) provide a considerably improved average potential of 3.76 V leading to a projected energy density as high as 449 Wh kg−1 and reversible cycling for more than 60 cycles. 7Li Nuclear Magnetic Resonance spectroscopy was combined with ex-situ Small Angle X-ray Scattering to elucidate the storage mechanism of lithium inside the carbon matrix. The formation of extended quasi-metallic lithium clusters after electrochemical lithiation was revealed

Electrochemical Generation of Catalytically Active Edge Sites in C₂N‐Type Carbon Materials for Artificial Nitrogen Fixation

The electrochemical nitrogen reduction reaction (NRR) to ammonia (NH₃) is a potentially carbon‐neutral and decentralized supplement to the established Haber–Bosch process. Catalytic activation of the highly stable dinitrogen molecules remains a great challenge. Especially metal‐free nitrogen‐doped carbon catalysts do not often reach the desired selectivity and ammonia production rates due to their low concentration of NRR active sites and possible instability of heteroatoms under electrochemical potential, which can even contribute to false positive results. In this context, the electrochemical activation of nitrogen‐doped carbon electrocatalysts is an attractive, but not yet established method to create NRR catalytic sites. Herein, a metal‐free C₂N material (HAT‐700) is electrochemically etched prior to application in NRR to form active edge‐sites originating from the removal of terminal nitrile groups. Resulting activated metal‐free HAT‐700‐A shows remarkable catalytic activity in electrochemical nitrogen fixation with a maximum Faradaic efficiency of 11.4% and NH₃ yield of 5.86 µg mg⁻¹cat h⁻¹. Experimental results and theoretical calculations are combined, and it is proposed that carbon radicals formed during activation together with adjacent pyridinic nitrogen atoms play a crucial role in nitrogen adsorption and activation. The results demonstrate the possibility to create catalytically active sites on purpose by etching labile functional groups prior to NRR

Morphological segmentation analysis and texture-based support vector machines classification on mice liver fibrosis microscopic images

Background To reduce the intensity of the work of doctors, pre-classification work needs to be issued. In this paper, a novel and related liver microscopic image classification analysis method is proposed. Objective For quantitative analysis, segmentation is carried out to extract the quantitative information of special organisms in the image for further diagnosis, lesion localization, learning and treating anatomical abnormalities and computer-guided surgery. Methods in the current work, entropy based features of microscopic fibrosis mice’ liver images were analyzed using fuzzy c-cluster, k-means and watershed algorithms based on distance transformations and gradient. A morphological segmentation based on a local threshold was deployed to determine the fibrosis areas of images. Results the segmented target region using the proposed method achieved high effective microscopy fibrosis images segmenting of mice liver in terms of the running time, dice ratio and precision. The image classification experiments were conducted using Gray Level Co-occurrence Matrix (GLCM). The best classification model derived from the established characteristics was GLCM which performed the highest accuracy of classification using a developed Support Vector Machine (SVM). The training model using 11 features was found to be as accurate when only trained by 8 GLCMs. Conclusion The research illustrated the proposed method is a new feasible research approach for microscopy mice liver image segmentation and classification using intelligent image analysis techniques. It is also reported that the average computational time of the proposed approach was only 2.335 seconds, which outperformed other segmentation algorithms with 0.8125 dice ratio and 0.5253 precision

An increase in food production in Europe could dramatically affect farmland biodiversity

Conversion of semi-natural habitats, such as field margins, fallows, hedgerows, grassland, woodlots and forests, to agricultural land could increase agricultural production and help meet rising global food demand. Yet, the extent to which such habitat loss would impact biodiversity and wild species is unknown. Here we survey species richness for four taxa (vascular plants, earthworms, spiders, wild bees) and agricultural yield across a range of arable, grassland, mixed, horticulture, permanent crop, for organic and non-organic agricultural land on 169 farms across 10 European regions. We find that semi-natural habitats currently constitute 23% of land area with 49% of species unique to these habitats. We estimate that conversion of semi-natural land that achieves a 10% increase in agricultural production will have the greatest impact on biodiversity in arable systems and the least impact in grassland systems, with organic practices having better species retention than non-organic practices. Our findings will help inform sustainable agricultural development

Gains to species diversity in organically farmed fields are not propagated at the farm level

Organic farming is promoted to reduce environmental impacts of agriculture, but surprisingly little is known about its effects at the farm level, the primary unit of decision making. Here we report the effects of organic farming on species diversity at the field, farm and regional levels by sampling plants, earthworms, spiders and bees in 1470 fields of 205 randomly selected organic and nonorganic farms in twelve European and African regions. Species richness is, on average, 10.5% higher in organic than nonorganic production fields, with highest gains in intensive arable fields (around +45%). Gains to species richness are partly caused by higher organism abundance and are common in plants and bees but intermittent in earthworms and spiders. Average gains are marginal +4.6% at the farm and +3.1% at the regional level, even in intensive arable regions. Additional, targeted measures are therefore needed to fulfil the commitment of organic farming to benefit farmland biodiversity

Farmland biodiversity and agricultural management on 237 farms in 13 European and two African regions

Farmland is a major land cover type in Europe and Africa and provides habitat for numerous species. The severe decline in farmland biodiversity of the last decades has been attributed to changes in farming practices, and organic and low-input farming are assumed to mitigate detrimental effects of agricultural intensification on biodiversity. Since the farm enterprise is the primary unit of agricultural decision making, management-related effects at the field scale need to be assessed at the farm level. Therefore, in this study, data were collected on habitat characteristics, vascular plant, earthworm, spider, and bee communities and on the corresponding agricultural management in 237 farms in 13 European and two African regions. In 15 environmental and agricultural homogeneous regions, 6–20 farms with the same farm type (e.g., arable crops, grassland, or specific permanent crops) were selected. If available, an equal number of organic and non-organic farms were randomly selected. Alternatively, farms were sampled along a gradient of management intensity. For all selected farms, the entire farmed area was mapped, which resulted in total in the mapping of 11 338 units attributed to 194 standardized habitat types, provided together with additional descriptors. On each farm, one site per available habitat type was randomly selected for species diversity investigations. Species were sampled on 2115 sites and identified to the species level by expert taxonomists. Species lists and abundance estimates are provided for each site and sampling date (one date for plants and earthworms, three dates for spiders and bees). In addition, farmers provided information about their management practices in face-to-face interviews following a standardized questionnaire. Farm management indicators for each farm are available (e.g., nitrogen input, pesticide applications, or energy input). Analyses revealed a positive effect of unproductive areas and a negative effect of intensive management on biodiversity. Communities of the four taxonomic groups strongly differed in their response to habitat characteristics, agricultural management, and regional circumstances. The data has potential for further insights into interactions of farmland biodiversity and agricultural management at site, farm, and regional scale

Direct observation of ion dynamics in supercapacitor electrodes using in situ diffusion NMR spectroscopy

Ionic transport inside porous carbon electrodes underpins the storage of energy in supercapacitors and the rate at which they can charge and discharge, yet few studies have elucidated the materials properties that influence ion dynamics. Here we use in situ pulsed field gradient NMR spectroscopy to measure ionic diffusion in supercapacitors directly. We find that confinement in the nanoporous electrode structures decreases the effective self-diffusion coefficients of ions by over two orders of magnitude compared with neat electrolyte, and in-pore diffusion is modulated by changes in ion populations at the electrode/electrolyte interface during charging. Electrolyte concentration and carbon pore size distributions also affect in-pore diffusion and the movement of ions in and out of the nanopores. In light of our findings we propose that controlling the charging mechanism may allow the tuning of the energy and power performances of supercapacitors for a range of different applications

Biomarkers of the involvement of mast cells, basophils and eosinophils in asthma and allergic diseases

Biomarkers of disease activity have come into wide use in the study of mechanisms of human disease and in clinical medicine to both diagnose and predict disease course; as well as to monitor response to therapeutic intervention. Here we review biomarkers of the involvement of mast cells, basophils, and eosinophils in human allergic inflammation. Included are surface markers of cell activation as well as specific products of these inflammatory cells that implicate specific cell types in the inflammatory process and are of possible value in clinical research as well as within decisions made in the practice of allergy-immunology