Activation of Ni Particles into Single Ni–N Atoms for Efficient Electrochemical Reduction of CO2

Electrochemical reduction of carbon dioxide (CO₂) to fuels and value‐added industrial chemicals is a promising strategy for keeping a healthy balance between energy supply and net carbon emissions. Here, the facile transformation of residual Ni particle catalysts in carbon nanotubes into thermally stable single Ni atoms with a possible NiN₃ moiety is reported, surrounded with a porous N‐doped carbon sheath through a one‐step nanoconfined pyrolysis strategy. These structural changes are confirmed by X‐ray absorption fine structure analysis and density functional theory (DFT) calculations. The dispersed Ni single atoms facilitate highly efficient electrocatalytic CO₂ reduction at low overpotentials to yield CO, providing a CO faradaic efficiency exceeding 90%, turnover frequency approaching 12 000 h^?1, and metal mass activity reaching about 10 600 mA mg^?1, outperforming current state‐of‐the‐art single atom catalysts for CO₂ reduction to CO. DFT calculations suggest that the Ni@N₃ (pyrrolic) site favors *COOH formation with lower free energy than Ni@N₄, in addition to exothermic CO desorption, hence enhancing electrocatalytic CO₂ conversion. This finding provides a simple, scalable, and promising route for the preparation of low‐cost, abundant, and highly active single atom catalysts, benefiting future practical CO₂ electrolysis.     

Accelerating Atomic Catalyst Discovery by Theoretical Calculations‐Machine Learning Strategy

Atomic catalysts (AC) are emerging as a highly attractive research topic, especially in sustainable energy fields. Lack of a full picture of the hydrogen evolution reaction (HER) impedes the future development of potential electrocatalysts. In this work, the systematic investigation of the HER process in graphdyine (GDY) based AC is presented in terms of the adsorption energies, adsorption trend, electronic structures, reaction pathway, and active sites. This comprehensive work innovatively reveals GDY based AC for HER covering all the transition metals (TM) and lanthanide (Ln) metals, enabling the screening of potential catalysts. The density functional theory (DFT) calculations carefully explore the HER performance beyond the comparison of sole H adsorption. Therefore, the screened catalysts candidates not only match with experimental results but also provide significant references for novel catalysts. Moreover, the machine learning (ML) technique bag‐tree approach is innovatively utilized based on the fuzzy model for data separation and converse prediction of the HER performance, which indicates a similar result to the theoretical calculations. From two independent theoretical perspectives (DFT and ML), this work proposes pivotal guidelines for experimental catalyst design and synthesis. The proposed advanced research strategy shows great potential as a general approach in other energy‐related areas.     

Phosphorus alleviation of nitrogen‐suppressed methane sink in global grasslands

Grassland ecosystems account for more than 10% of the global CH₄ sink in soils. A 4‐year field experiment found that addition of P alone did not affect CH₄ uptake and experimental addition of N alone significantly suppressed CH₄ uptake, whereas concurrent N and P additions suppressed CH₄ uptake to a lesser degree. A meta‐analysis including 382 data points in global grasslands corroborated these findings. Global extrapolation with an empirical modelling approach estimated that contemporary N addition suppresses CH₄ sink in global grassland by 11.4% and concurrent N and P deposition alleviates this suppression to 5.8%. The P alleviation of N‐suppressed CH₄ sink is primarily attributed to substrate competition, defined as the competition between ammonium and CH₄ for the methane mono‐oxygenase enzyme. The N and P impacts on CH₄ uptake indicate that projected increases in N and P depositions might substantially affect CH₄ uptake and alter the global CH₄ cycle.     

Evolution of specialized microbial cooperation in dynamic fluids

Here, we study the evolution of specialization using realistic computer simulations of bacteria that secrete two public goods in a dynamic fluid. Through this first‐principles approach, we find physical factors such as diffusion, flow patterns and decay rates are as influential as fitness economics in governing the evolution of community structure, to the extent that when mechanical factors are taken into account, (a) generalist communities can resist becoming specialists despite the invasion fitness of specialization; (b) generalist and specialists can both resist cheaters despite the invasion fitness of free‐riding; and (c) multiple community structures can coexist despite the opposing force of competitive exclusion. Our results emphasize the role of spatial assortment and physical forces on niche partitioning and the evolution of diverse community structures.     

Plant respiration: Controlled by photosynthesis or biomass?

Two simplifying hypotheses have been proposed for whole‐plant respiration. One links respiration to photosynthesis; the other to biomass. Using a first‐principles carbon balance model with a prescribed live woody biomass turnover, applied at a forest research site where multidecadal measurements are available for comparison, we show that if turnover is fast the accumulation of respiring biomass is low and respiration depends primarily on photosynthesis; while if turnover is slow the accumulation of respiring biomass is high and respiration depends primarily on biomass. But the first scenario is inconsistent with evidence for substantial carry‐over of fixed carbon between years, while the second implies far too great an increase in respiration during stand development—leading to depleted carbohydrate reserves and an unrealistically high mortality risk. These two mutually incompatible hypotheses are thus both incorrect. Respiration is not linearly related either to photosynthesis or to biomass, but it is more strongly controlled by recent photosynthates (and reserve availability) than by total biomass.     

Human exploitation shapes productivity–biomass relationships on coral reefs

Coral reef fisheries support the livelihoods of millions of people in tropical countries, despite large‐scale depletion of fish biomass. While human adaptability can help to explain the resistance of fisheries to biomass depletion, compensatory ecological mechanisms may also be involved. If this is the case, high productivity should coexist with low biomass under relatively high exploitation. Here we integrate large spatial scale empirical data analysis and a theory‐driven modelling approach to unveil the effects of human exploitation on reef fish productivity–biomass relationships. We show that differences in how productivity and biomass respond to overexploitation can decouple their relationship. As size‐selective exploitation depletes fish biomass, it triggers increased production per unit biomass, averting immediate productivity collapse in both the modelling and the empirical systems. This ‘buffering productivity’ exposes the danger of assuming resource production–biomass equivalence, but may help to explain why some biomass‐depleted fish assemblages still provide ecosystem goods under continued global fishing exploitation.     

Range edges in heterogeneous landscapes: Integrating geographic scale and climate complexity into range dynamics

The impacts of climate change have re‐energized interest in understanding the role of climate in setting species geographic range edges. Despite the strong focus on species' distributions in ecology and evolution, defining a species range edge is theoretically and empirically difficult. The challenge of determining a range edge and its relationship to climate is in part driven by the nested nature of geography and the multidimensionality of climate, which together generate complex patterns of both climate and biotic distributions across landscapes. Because range‐limiting processes occur in both geographic and climate space, the relationship between these two spaces plays a critical role in setting range limits. With both conceptual and empirical support, we argue that three factors—climate heterogeneity, collinearity among climate variables, and spatial scale—interact to shape the spatial structure of range edges along climate gradients, and we discuss several ways that these factors influence the stability of species range edges with a changing climate. We demonstrate that geographic and climate edges are often not concordant across species ranges. Furthermore, high climate heterogeneity and low climate collinearity across landscapes increase the spectrum of possible relationships between geographic and climatic space, suggesting that geographic range edges and climatic niche limits correspond less frequently than we may expect. More empirical explorations of how the complexity of real landscapes shapes the ecological and evolutionary processes that determine species range edges will advance the development of range limit theory and its applications to biodiversity conservation in the context of changing climate.     

Traits mediate drought effects on wood carbon fluxes

CO₂ fluxes from wood decomposition represent an important source of carbon from forest ecosystems to the atmosphere, which are determined by both wood traits and climate influencing the metabolic rates of decomposers. Previous studies have quantified the effects of moisture and temperature on wood decomposition, but these effects were not separated from the potential influence of wood traits. Indeed, it is not well understood how traits and climate interact to influence wood CO₂ fluxes. Here, we examined the responses of CO₂ fluxes from dead wood with different traits (angiosperm and gymnosperm) to 0%, 35%, and 70% rainfall reduction across seasonal temperature gradients. Our results showed that drought significantly decreased wood CO₂ fluxes, but its effects varied with both taxonomical group and drought intensity. Drought‐induced reduction in wood CO₂ fluxes was larger in angiosperms than gymnosperms for the 35% rainfall reduction treatment, but there was no significant difference between these groups for the 70% reduction treatment. This is because wood nitrogen density and carbon quality were significantly higher in angiosperms than gymnosperms, yielding a higher moisture sensitivity of wood decomposition. These findings were demonstrated by a significant positive interaction effect between wood nitrogen and moisture on CO₂ fluxes in a structural equation model. Additionally, we ascertained that a constant temperature sensitivity of CO₂ fluxes was independent of wood traits and consistent with previous estimates for extracellular enzyme kinetics. Our results highlight the key role of wood traits in regulating drought responses of wood carbon fluxes. Given that both climate and forest management might extensively modify taxonomic compositions in the future, it is critical for carbon cycle models to account for such interactions between wood traits and climate in driving dynamics of wood decomposition.     

Development and validation of an experimental and theoretical method for the chiral discrimination of dinotefuran

Dinotefuran is a low-cost agrochemical considered a highly toxic product. In this sense, there is a need for its constant environmental, biological, and food control, aiming to ensure its use to humans as well as to preserve biodiversity and ecosystems. In the present work, we developed an experimental and theoretical method for dinotefuran chiral discrimination. According to the main results, the dinotefuran enantioselective separation was efficiently optimized by high-performance liquid chromatography evaluating the influence of different percentage compositions in the mobile phase to improve the resolution of the peaks in the chromatogram. The novelty of this work was the proposition of a reduced molecular model for the chiral selector amylose-Tris-(3,5-dimethylphenylcarbamate) polysaccharide that was able to adequately describe at the molecular level its interaction with the dinotefuran enantiomers. Besides, the thermodynamic and structural parameters obtained via density functional theory calculations pointed out the chiral discrimination as well as the enantiomeric elution order of the analyte studied, confirming the experimental data, thus validating our proposed method. Finally, hydrogen bonds and repulsive interactions played a key role in the discrimination between the diastereomeric complexes, and consequently, for the dinotefuran enantioselective separation.