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Antimony trisulfide (Sb 2 S 3 ) is an emerging semiconductor with a high absorption coefficient and a bandgap in the visible range. This makes it a promising material for various electronic and optoelectronic applications. However, one of the main challenges is still the synthesis of the material, as it is usually obtained either as a nanomaterial in its amorphous form with inferior optical properties or in crystalline rod-like structures in the micrometer or sub-micrometer range, which leads to application-related difficulties such as clogging in inkjet printing or spraying processes or highly porous layers in film applications. In this study, a one-pot synthesis of highly crystalline, spherical Sb 2 S 3 sub-micron particles is presented. The particles are growing encapsulated in a removable, wax-like matrix that is formed together with an intermediate from the precursors SbCl 3 and l-cysteine. Both substances are insoluble in the reaction mixture but well-dispersable in the solvent 1-octadecene (ODE). The intermediate forms a complex crosslinked architecture whose basic building block consists of an Sb atom attached to three cysteine molecules via Sb-S bonds. Embedded in the matrix consisting of excess cysteine, ODE, and chlorine, the intermediate decomposes into amorphous Sb 2 S 3 particles that crystallize as the reaction proceeds at 240 °C. The final particles are highly crystalline, spherical, and in the sub-micron range (420 ± 100 nm), making them ideal for further processing. The encapsulation method could not only provide a way to extend the size range of colloidal particles, but in the case of Sb 2 S 3 , this method circumvents the risk of carbonization of ligands or insufficient crystallization during the annealing of amorphous material., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

Sb 2 S 3 is a promising nanomaterial for application in solar cells and in the fields of electronics and optoelectronics. Herein, Sb 2 S 3 nanoparticles were prepared via the hot-injection approach. In contrast to earlier work, the reaction temperature was decreased to 150 °C so that the reaction was slowed down and could be stopped at defined reaction stages. Thereby, the formation mechanism of the nanomaterial and the associated kinetics could be revealed. Based on morphological and structural analyses, it is suggested that seed particles (type 0) formed immediately after injecting the antimony precursor into the sulfur precursor. These seeds fused to form amorphous nanoparticles (type I) that contained a lower percentage of sulfur than that corresponding to the expected stoichiometric ratio of Sb 2 S 3 . The reason for this possibly lies in the formation of an oxygen- or carbon-containing intermediate during the seeding process. Afterward, the type I nanoparticles aggregated into larger amorphous nanoparticles (type II) in a second hierarchical assembly process and formed superordinate structures (type III). This process was followed by the crystallization of these particles and a layer-like growth of the crystalline particles by an Ostwald ripening process at the expense of the amorphous particles. It was demonstrated that the kinetic control of the reaction allowed tuning of the optical band gap of the amorphous nanoparticles in the range of 2.2-2.0 eV. On the contrary, the optical band gap of the crystalline particles decreased to a value of 1.7 eV and remained constant when the reaction progressed. Based on the proposed formation mechanism, future syntheses for Sb 2 S 3 particles can be developed, allowing tuning of the particle properties in a broad range. In this way, the selective use of this material in a wide range of applications will become possible., (Copyright © 2021, Joschko et al.)

Earthworms are an important soil taxon as ecosystem engineers, providing a variety of crucial ecosystem functions and services. Little is known about their diversity and distribution at large spatial scales, despite the availability of considerable amounts of local-scale data. Earthworm diversity data, obtained from the primary literature or provided directly by authors, were collated with information on site locations, including coordinates, habitat cover, and soil properties. Datasets were required, at a minimum, to include abundance or biomass of earthworms at a site. Where possible, site-level species lists were included, as well as the abundance and biomass of individual species and ecological groups. This global dataset contains 10,840 sites, with 184 species, from 60 countries and all continents except Antarctica. The data were obtained from 182 published articles, published between 1973 and 2017, and 17 unpublished datasets. Amalgamating data into a single global database will assist researchers in investigating and answering a wide variety of pressing questions, for example, jointly assessing aboveground and belowground biodiversity distributions and drivers of biodiversity change.

Soil samples from several European countries were scanned using medical computer tomography (CT) device and are now available as CT images. The analysis of these samples was carried out using deep learning methods. For this purpose, a VGG16 network was trained with the CT images (X). For the annotation (y) a new method for automated annotation, 'surrogate' learning, was introduced. The generated neural networks (NNs) were subjected to a detailed analysis. Among other things, transfer learning was used to check whether the NN can also be trained to other y-values. Visually, the NN was verified using a gradient-based class activation mapping (grad-CAM) algorithm. These analyses showed that the NN was able to generalize, i.e. to capture the spatial structure of the soil sample. Possible applications of the models are discussed., (© 2021 The Authors.)

Background: Earthworms are important for maintaining soil ecosystem functioning and serve as indicators of soil fertility. However, detection of earthworms is time-consuming, which hinders the assessment of earthworm abundances with high sampling density over entire fields. Recent developments of mobile terrestrial sensor platforms for proximal soil sensing (PSS) provided new tools for collecting dense spatial information of soils using various sensing principles. Yet, the potential of PSS for assessing earthworm habitats is largely unexplored. This study investigates whether PSS data contribute to the spatial prediction of earthworm abundances in species distribution models of agricultural soils., Methodology/principal Findings: Proximal soil sensing data, e.g., soil electrical conductivity (EC), pH, and near infrared absorbance (NIR), were collected in real-time in a field with two management strategies (reduced tillage / conventional tillage) and sandy to loam soils. PSS was related to observations from a long-term (11 years) earthworm observation study conducted at 42 plots. Earthworms were sampled from 0.5 x 0.5 x 0.2 m³ soil blocks and identified to species level. Sensor data were highly correlated with earthworm abundances observed in reduced tillage but less correlated with earthworm abundances observed in conventional tillage. This may indicate that management influences the sensor-earthworm relationship. Generalized additive models and state-space models showed that modelling based on data fusion from EC, pH, and NIR sensors produced better results than modelling without sensor data or data from just a single sensor. Regarding the individual earthworm species, particular sensor combinations were more appropriate than others due to the different habitat requirements of the earthworms. Earthworm species with soil-specific habitat preferences were spatially predicted with higher accuracy by PSS than more ubiquitous species., Conclusions/significance: Our findings suggest that PSS contributes to the spatial modelling of earthworm abundances at field scale and that it will support species distribution modelling in the attempt to understand the soil-earthworm relationships in agroecosystems.

Cortico-cortical connections of motor cortex in the marsupial brushtailed possum were traced by making injections of horseradish peroxidase (HRP) into two parts of motor cortex: the rostral agranular part which does not overlap somatosensory cortex, and the caudal part which does. Following injections in motor cortex, labelled neurons were observed on the same side of the brain within somatosensory areas 1 and 2 and in parietal cortex just caudal to S1, with most neurons in cortical Layers 2-4. Commissural connections were found in half of the experiments, with many labelled neurons in cortical Layer 5. We have compared the pattern of cortico-cortical connections in the possum with those seen in some other mammals, which appear generally similar.