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The transfer of photosynthetically produced organic carbon from surface to mesopelagic waters draws carbon dioxide from the atmosphere1. However, current observation-based estimates disagree on the strength of this biological carbon pump (BCP)2. Earth system models (ESMs) also exhibit a large spread of BCP estimates, indicating limited representations of the known carbon export pathways3. Here we use several decades of hydrographic observations to produce a top-down estimate of the strength of the BCP with an inverse biogeochemical model that implicitly accounts for all known export pathways. Our estimate of total organic carbon (TOC) export at 73.4 m (model euphotic zone depth) is 15.00 ± 1.12 Pg C year-1, with only two-thirds reaching 100 m depth owing to rapid remineralization of organic matter in the upper water column. Partitioned by sequestration time below the euphotic zone, τ, the globally integrated organic carbon production rate with τ > 3 months is 11.09 ± 1.02 Pg C year-1, dropping to 8.25 ± 0.30 Pg C year-1 for τ > 1 year, with 81% contributed by the non-advective-diffusive vertical flux owing to sinking particles and vertically migrating zooplankton. Nevertheless, export of organic carbon by mixing and other fluid transport of dissolved matter and suspended particles remains regionally important for meeting the respiratory carbon demand. Furthermore, the temperature dependence of the sequestration efficiency inferred from our inversion suggests that future global warming may intensify the recycling of organic matter in the upper ocean, potentially weakening the BCP.

C58H42CdN10O6, triclinic, P1‾$P\overline{1}$ (no. 2), a = 9.689(3) Å, b = 10.930(3) Å, c = 23.321(6) Å, α = 80.838(5)°, β = 84.261(5)°, γ = 79.189(5)°, V = 2388.7(12) Å3, Z = 2, Rgt(F) = 0.0592, wRref(F2) = 0.1561, T = 293 K.

C42H27MnN5O9·2H2O, triclinic, P1‾$P\overline{1}$ (no. 2), a = 12.4250(8) Å, b = 12.7259(8) Å, c = 14.2946(9) Å, α = 64.102(2)°, β = 79.774(2)°, γ = 62.453(2)°, V = 1801.9(2) Å3, Z = 2, Rgt(F) = 0.0344, wRref(F2) = 0.0951, T = 150 K.

C28H21Cl2MnN5O4, triclinic, P1‾ $P\overline{1}$ (no. 2), a = 8.9699(9) Å, b = 9.1185(9) Å, c = 17.6902(17) Å, α = 103.776(1)°, β = 92.407(1)°, γ = 99.761(1)°, V = 1379.8(2) Å3, Z = 2, R gt(F) = 0.0388, wR ref(F 2) = 0.0920, T = 296 K.

C22H28N2O2, monoclinic, P21/n (no. 14), a = 6.463(3) Å, b = 14.889(6) Å, c = 10.282(4) Å, β = 95.105(5)°, V = 985.5(7) Å3, Z = 2, Rgt(F) = 0.0425, wRref(F2) = 0.1206, T = 296 (2) K.

Surface ocean phosphate is commonly below the standard analytical detection limits, leading to an incomplete picture of the global variation and biogeochemical role of phosphate. A global compilation of phosphate measured using high-sensitivity methods revealed several previously unrecognized low-phosphate areas and clear regional differences. Both observational climatologies and Earth system models (ESMs) systematically overestimated surface phosphate. Furthermore, ESMs misrepresented the relationships between phosphate, phytoplankton biomass, and primary productivity. Atmospheric iron input and nitrogen fixation are known important controls on surface phosphate, but model simulations showed that differences in the iron-to-macronutrient ratio in the vertical nutrient supply and surface lateral transport are additional drivers of phosphate concentrations. Our study demonstrates the importance of accurately quantifying nutrients for understanding the regulation of ocean ecosystems and biogeochemistry now and under future climate conditions.

Electrocatalytic CO2 reduction to multi-carbon products is a promising approach for achieving carbon-neutral economies. However, the energy efficiency of these processes remains low, particularly at high current densities. Herein, we demonstrate that the low energy efficiencies are, in part, sometimes significantly, attributed to the high concentration overpotential resulting from the instability (i.e., flooding) of catalyst-layer during electrolysis. To tackle this challenge, we develop copper/gallium bimetallic catalysts with reduced activation energies for the formation of multi-carbon products. Consequently, the reduced activation overpotential allows us to achieve practical-relevant current densities for CO2 reduction at low cathodic potentials, ensuring good stability of the catalyst-layer and thereby minimizing the undesired concentration overpotential. The optimized bimetallic catalyst achieves over 50% cathodic energy efficiency for multi-carbon production at a high current density of over 1.0 A cm − 2 . Furthermore, we achieve current densities exceeding 2.0 A cm − 2 in a zero-gap membrane-electrode-assembly reactor, with a full-cell energy efficiency surpassing 30%. Electroreduction of CO2 to fuels and chemicals is promising but hindered by its low energy efficiency. Here, the authors develop Cu/Ga bimetallic catalysts with reduced activation energies to mitigate the high concentration overpotential, thereby achieving high energy efficiency for CO2 reduction. [ABSTRACT FROM AUTHOR]

The recent progress in chemical synthetic methodologies has facilitated the fabrication of discrete plasmonic nanoparticles exhibiting chiral characteristics on their surface. In comparison to conventional gold nanorods (NRs), such structures possess strong plasmonic circular dichroism response, making them highly suitable for various applications involving circularly polarized light. Although the intrinsic and extrinsic chirality of chiral nanostructures produced by the assembly with chiral ligands have been explored both experimentally and theoretically, the investigation into the influencing factors of the intrinsic and extrinsic chirality of discrete chiral Au NRs (dc-Au NRs) has been relatively limited. Herein, we conducted a comprehensive investigation using full-wave electromagnetic simulations to explore the influence of various structural parameters (such as helical depth, width, and numbers of the helical pitches) on the intrinsic and extrinsic chirality of dc-Au NRs. Additionally, we examined the chiral surface plasmon resonance coupling and the corresponding chiral near-field by studying the cross-like assembly of dc-Au NR dimers. These findings serve as valuable guidance for future experimental and theoretical research on chiral plasmonic nanostructures and their applications involving circularly polarized light. [ABSTRACT FROM AUTHOR]

This paper proposes a new hybrid model for classifying stress states using EEG signals, combining multi-domain transfer entropy (TrEn) with a two-dimensional PCANet (2D-PCANet) approach. The aim is to create an automated system for identifying stress levels, which is crucial for early intervention and mental health management. A major challenge in this field lies in extracting meaningful emotional information from the complex patterns observed in EEG. Our model addresses this by initially applying independent component analysis (ICA) to purify the EEG signals, enhancing the clarity for further analysis. We then leverage the adaptability of the fractional Fourier transform (FrFT) to represent the EEG data in time, frequency, and time–frequency domains. This multi-domain representation allows for a more nuanced understanding of the brain's activity in response to stress. The subsequent stage involves the deployment of a two-layer 2D-PCANet network designed to autonomously distill EEG features associated with stress. These features are then classified by a support vector machine (SVM) to determine the stress state. Moreover, stress induction and data acquisition experiments are designed. We employed two distinct tasks known to trigger stress responses. Other stress-inducing elements that enhance the stress response were included in the experimental design, such as time limits and performance feedback. The EEG data collected from 15 participants were retained. The proposed algorithm achieves an average accuracy of over 92% on this self-collected dataset, enabling stress state detection under different task-induced conditions. [ABSTRACT FROM AUTHOR]

We examine climate change impacts on net primary production (NPP) and export production (sinking particulate flux; EP) with simulations from nine Earth system models (ESMs) performed in the framework of the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Global NPP and EP are reduced by the end of the century for the intense warming scenario of Representative Concentration Pathway (RCP) 8.5. Relative to the 1990s, NPP in the 2090s is reduced by 2-16 % and EP by 7-18 %. The models with the largest increases in stratification (and largest relative declines in NPP and EP) also show the largest positive biases in stratification for the contemporary period, suggesting overestimation of climate change impacts on NPP and EP. All of the CMIP5 models show an increase in stratification in response to surface-ocean warming and freshening, which is accompanied by decreases in surface nutrients, NPP and EP. There is considerable variability across the models in the magnitudes of NPP, EP, surface nutrient concentrations and their perturbations by climate change. The negative response of NPP and EP to increasing stratification reflects primarily a bottom-up control, as upward nutrient flux declines at the global scale. Models with dynamic phytoplankton community structure show larger declines in EP than in NPP. This pattern is driven by phytoplankton community composition shifts, with reductions in productivity by large phytoplankton as smaller phytoplankton (which export less efficiently) are favored under the increasing nutrient stress. Thus, the projections of the NPP response to climate change are critically dependent on the simulated phytoplankton community structure, the efficiency of the biological pump and the resulting levels of regenerated production, which vary widely across the models. Community structure is represented simply in the CMIP5 models, and should be expanded to better capture the spatial patterns and climate-driven changes in export efficiency.