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The solution synthesis of complex and asymmetric nanostructures is still challenging. For many applications, it will be important to gain simultaneous control over particle size and morphology, constituent materials, and internal interfaces. Fenton et al. have developed a strategy that mimics chemical retrosynthesis, starting with simple nanoparticle synthons—in this case, Cu 1.8 S nanoparticles, nanorods, and nanosheets. Various types of interfaces and junctions can be introduced, for example, by cation substitution. This intervention breaks the symmetry of the synthons and assembles them into higher-order structures. The nanostructures can thus be formed with asymmetric, patchy, porous, or sculpted regions. Science , this issue p. 513 Three simple nanoparticle synthons are transformed into a wide variety of higher-order derivatives. Complex heterostructured nanoparticles with precisely defined materials and interfaces are important for many applications. However, rationally incorporating such features into nanoparticles with rigorous morphology control remains a synthetic bottleneck. We define a modular divergent synthesis strategy that progressively transforms simple nanoparticle synthons into increasingly sophisticated products. We introduce a series of tunable interfaces into zero-, one-, and two-dimensional copper sulfide nanoparticles using cation exchange reactions. Subsequent manipulation of these intraparticle frameworks yielded a library of 47 distinct heterostructured metal sulfide derivatives, including particles that contain asymmetric, patchy, porous, and sculpted nanoarchitectures. This generalizable mix-and-match strategy provides predictable retrosynthetic pathways to complex nanoparticle features that are otherwise inaccessible.

SoilGrids produces maps of soil properties for the entire globe at medium spatial resolution (250 m cell size) using state-of-the-art machine learning methods to generate the necessary models. It takes as inputs soil observations from about 240 000 locations worldwide and over 400 global environmental covariates describing vegetation, terrain morphology, climate, geology and hydrology. The aim of this work was the production of global maps of soil properties, with cross-validation, hyper-parameter selection and quantification of spatially explicit uncertainty, as implemented in the SoilGrids version 2.0 product incorporating state-of-the-art practices and adapting them for global digital soil mapping with legacy data. The paper presents the evaluation of the global predictions produced for soil organic carbon content, total nitrogen, coarse fragments, pH (water), cation exchange capacity, bulk density and texture fractions at six standard depths (up to 200 cm). The quantitative evaluation showed metrics in line with previous global, continental and large-region studies. The qualitative evaluation showed that coarse-scale patterns are well reproduced. The spatial uncertainty at global scale highlighted the need for more soil observations, especially in high-latitude regions.

Aim Experimental nitrogen (N) addition (fertilization) studies are commonly used to quantify the impacts of increased N inputs on plant biodiversity. However, given that plant community responses can vary considerably among individual studies, there is a clear need to synthesize and generalize findings with meta‐analytical approaches. Our goal was to quantify changes in species richness and abundance in plant communities in response to N addition across different environmental contexts, while controlling for different experimental designs. Location Global. Time period Data range: 1985–2016; Publication years: 1990–2018. Major taxa studied Plants. Methods We performed a meta‐analysis of 115 experiments reported in 85 studies assessing the effects of N addition on terrestrial natural and semi‐natural plant communities. We quantified local‐scale changes in plant biodiversity in relationship to N addition using four metrics: species richness (SR), individual species abundance (IA), mean species abundance (MSA) and geometric mean abundance (GMA). Results For all metrics, greater amounts of annual N addition resulted in larger declines in plant diversity. Additionally, MSA decreased more steeply with N that was applied in reduced (NH4+) rather than oxidized (NO3-) form. Loss of SR with increasing amounts of N was found to be larger in warmer sites. Furthermore, greater losses of SR were found in sites with longer experimental durations, smaller plot sizes and lower soil cation exchange capacity. Finally, reductions in the abundance of individual species were larger for N‐sensitive plant life‐form types (legumes and non‐vascular plants). Main conclusions N enrichment decreases both SR and abundance of plants in N‐addition experiments, but the magnitude of the response differs among biodiversity metrics and with the environmental and experimental context. This underlines the importance of integrating multiple dimensions of biodiversity and relevant modifying factors into assessments of biodiversity responses to global environmental change.

Integrating multiple materials in arbitrary arrangements within nanoparticles is a prerequisite for advancing many applications. Strategies to synthesize heterostructured nanoparticles are emerging, but they are limited in complexity, scope, and scalability. We introduce two design guidelines, based on interfacial reactivity and crystal structure relations, that enable the rational synthesis of a heterostructured nanorod megalibrary. We define synthetically feasible pathways to 65,520 distinct multicomponent metal sulfide nanorods having as many as 6 materials, 8 segments, and 11 internal interfaces by applying up to seven sequential cation-exchange reactions to copper sulfide nanorod precursors. We experimentally observe 113 individual heterostructured nanorods and demonstrate the scalable production of three samples. Previously unimaginable complexity in heterostructured nanorods is now routinely achievable with simple benchtop chemistry and standard laboratory glassware.

Physical and chemical stabilisation mechanisms are now known to play a critical role in controlling carbon (C) storage in mineral soils, leading to suggestions that climate warming-induced C losses may be lower than previously predicted. By analysing > 9,000 soil profiles, here we show that, overall, C storage declines strongly with mean annual temperature. However, the reduction in C storage with temperature was more than three times greater in coarse-textured soils, with limited capacities for stabilising organic matter, than in fine-textured soils with greater stabilisation capacities. This pattern was observed independently in cool and warm regions, and after accounting for potentially confounding factors (plant productivity, precipitation, aridity, cation exchange capacity, and pH). The results could not, however, be represented by an established Earth system model (ESM). We conclude that warming will promote substantial soil C losses, but ESMs may not be predicting these losses accurately or which stocks are most vulnerable. The extent to which temperature controls soil carbon storage remains highly uncertain. Here, the authors show that, globally, soil carbon stocks decline strongly with temperature, but the effect is much greater in coarse-textured soils with limited organic matter stabilisation capacities, than in fine-textured soils.

This paper describes the technical development and accuracy assessment of the most recent and improved version of the SoilGrids system at 250m resolution (June 2016 update). SoilGrids provides global predictions for standard numeric soil properties (organic carbon, bulk density, Cation Exchange Capacity (CEC), pH, soil texture fractions and coarse fragments) at seven standard depths (0, 5, 15, 30, 60, 100 and 200 cm), in addition to predictions of depth to bedrock and distribution of soil classes based on the World Reference Base (WRB) and USDA classification systems (ca. 280 raster layers in total). Predictions were based on ca. 150,000 soil profiles used for training and a stack of 158 remote sensing-based soil covariates (primarily derived from MODIS land products, SRTM DEM derivatives, climatic images and global landform and lithology maps), which were used to fit an ensemble of machine learning methods-random forest and gradient boosting and/or multinomial logistic regression-as implemented in the R packages ranger, xgboost, nnet and caret. The results of 10-fold cross-validation show that the ensemble models explain between 56% (coarse fragments) and 83% (pH) of variation with an overall average of 61%. Improvements in the relative accuracy considering the amount of variation explained, in comparison to the previous version of SoilGrids at 1 km spatial resolution, range from 60 to 230%. Improvements can be attributed to: (1) the use of machine learning instead of linear regression, (2) to considerable investments in preparing finer resolution covariate layers and (3) to insertion of additional soil profiles. Further development of SoilGrids could include refinement of methods to incorporate input uncertainties and derivation of posterior probability distributions (per pixel), and further automation of spatial modeling so that soil maps can be generated for potentially hundreds of soil variables. Another area of future research is the development of methods for multiscale merging of SoilGrids predictions with local and/or national gridded soil products (e.g. up to 50 m spatial resolution) so that increasingly more accurate, complete and consistent global soil information can be produced. SoilGrids are available under the Open Data Base License.

The integration of luminescence and chirality in easy-scalable metal-organic frameworks gives rise to the development of advanced luminescent sensors. To date, the synthesis of chiral metal-organic frameworks is poorly predictable and their chirality primarily originates from components that constitute the frameworks. By contrast, the introduction of chirality into the pores of metal-organic frameworks has not been explored to the best of our knowledge. Here, we demonstrate that chirality can be introduced into an anionic Zn-based metal-organic framework via simple cation exchange, yielding dual luminescent centers comprised of the ligand and Tb 3+ ions, accompanied by a chiral center in the pores. This bifunctional material shows enantioselectivity luminescent sensing for a mixture of stereoisomers, demonstrated for Cinchonine and Cinchonidine epimers and amino alcohol enantiomers, from which the quantitative determination of the stereoisomeric excess has been obtained. This study paves a pathway for the design of multifunctional metal-organic framework systems as a useful method for rapid sensing of chiral molecules. Metal-organic frameworks with luminescence and chirality are promising for luminescent sensors for chiral molecules. Here, the authors use cation exchange to introduce chirality in multifunctional metal-organic framework systems for rapid enantioselective luminescent sensing.

Salt pollution and human-accelerated weathering are shifting the chemical composition of major ions in fresh water and increasing salinization and alkalinization across North America. We propose a concept, the freshwater salinization syndrome, which links salinization and alkalinization processes. This syndrome manifests as concurrent trends in specific conductance, pH, alkalinity, and base cations. Although individual trends can vary in strength, changes in salinization and alkalinization have affected 37% and 90%, respectively, of the drainage area of the contiguous United States over the past century. Across 232 United States Geological Survey (USGS) monitoring sites, 66% of stream and river sites showed a statistical increase in pH, which often began decades before acid rain regulations. The syndrome is most prominent in the densely populated eastern and midwestern United States, where salinity and alkalinity have increased most rapidly. The syndrome is caused by salt pollution (e.g., road deicers, irrigation runoff, sewage, potash), accelerated weathering and soil cation exchange, mining and resource extraction, and the presence of easily weathered minerals used in agriculture (lime) and urbanization (concrete). Increasing salts with strong bases and carbonates elevate acid neutralizing capacity and pH, and increasing sodium from salt pollution eventually displaces base cations on soil exchange sites, which further increases pH and alkalinization. Symptoms of the syndrome can include: infrastructure corrosion, contaminant mobilization, and variations in coastal ocean acidification caused by increasingly alkaline river inputs. Unless regulated and managed, the freshwater salinization syndrome can have significant impacts on ecosystem services such as safe drinking water, contaminant retention, and biodiversity.

Perovskite photovoltaics are gaining increasing common ground to partner with or compete with silicon photovoltaics to reduce cost of solar energy. However, a cost-effective waste management for toxic lead (Pb), which might determine the fate of this technology, has not been developed yet. Here, we report an end-of-life material management for perovskite solar modules to recycle toxic lead and valuable transparent conductors to protect the environment and create dramatic economic benefits from recycled materials. Lead is separated from decommissioned modules by weakly acidic cation exchange resin, which could be released as soluble Pb(NO 3 ) 2 followed by precipitation as PbI 2 for reuse, with a recycling efficiency of 99.2%. Thermal delamination disassembles the encapsulated modules with intact transparent conductors and cover glasses. The refabricated devices based on recycled lead iodide and recycled transparent conductors show comparable performance as devices based on fresh raw materials. Cost analysis shows this recycling technology is economically attractive. Perovskite photovoltaics has become more competitive against silicon counterpart in reducing cost of solar energy, yet the management of toxic lead hampers it application. Here, the authors propose a cost-effective environmental-friendly approach to recycle lead and transparent conductors.

Bipolar membrane electrolyzers present an attractive scenario for concurrently optimizing the pH environment required for paired electrode reactions. However, the practicalization of bipolar membranes for water electrolysis has been hindered by their sluggish water dissociation kinetics, poor mass transport, and insufficient interface durability. This study starts with numerical simulations and discloses the limiting factors of monopolar membrane layer engineering. On this foundation, we tailor flexible bipolar membranes (10 ∼ 40 µm) comprising anion and cation exchange layers with an identical poly(terphenyl alkylene) polymeric skeleton. Rapid mass transfer properties and high compatibility of the monopolar membrane layers endow the bipolar membrane with appreciable water dissociation efficiency and long-term stability. Incorporating the bipolar membrane into a flow-cell electrolyzer enables an ampere-level pure water electrolysis with a total voltage of 2.68 V at 1000 mA cm –2 , increasing the energy efficiency to twice that of the state-of-the-art commercial BPM. Furthermore, the bipolar membrane realizes a durability of 1000 h at high current densities of 300 ∼ 500 mA cm –2 with negligible performance decay. Bipolar membrane electrolyzers hold promise for water electrolysis but are limited by poor water dissociation and interface stability. Here, the authors report poly(terphenyl alkylene)-scaffold bipolar membranes that enhance water dissociation efficiency and enable durable pure water electrolysis.