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Rechargeable sodium-chlorine (Na-Cl2) batteries show high theoretical specific energy density and excellent adaptability for extreme environmental applications. However, the reported cycle life is mostly less than 500 cycles, and the understanding of battery failure mechanisms is quite limited. In this work, we demonstrate that the substantially increased voltage polarization plays a critical role in the battery failure. Typically, the passivation on the porous cathode caused by the deposition of insulated sodium chloride (NaCl) is a crucial factor, significantly influencing the three-phase chlorine (NaCl/Na+, Cl-/Cl2) conversion kinetics. Here, a self-depassivation strategy enabled by iodine anion (I-)-tuned NaCl deposition was implemented to enhance the chlorine reversibility. The nucleation and growth of NaCl crystals are well balanced through strong coordination of the NaI deposition-dissolution process, achieving depassivation on the cathode and improving the reoxidation efficiency of solid NaCl. Consequently, the resultant Na-Cl2 battery delivers a super-long cycle life up to 2000 cycles. An iodine-induced self-depassivation strategy extends Na-Cl2 battery life to 2000 cycles by forming high-reactivity NaCl and lowering the chlorine conversion polarization, which successfully solves a key failure mechanism for superior reversibility. [ABSTRACT FROM AUTHOR]

A novel multi-combined-step-size normalized subband adaptive filtering algorithm is proposed. Different from the traditional combined-step-size method, by employing a variable mixing parameter on each subband, our designed algorithm is able to combine a large step size with a small one more effectively for each subband. The subband mixing parameters are derived from the variance of the noise-free a priori subband error signals. In this design, a noniterative shrinkage strategy is also utilized to estimate the noise-free a priori subband error signals. Moreover, the mean-square and steady-state performances of the proposed algorithm are studied. Simulation results illustrate that the proposed algorithm outperforms other algorithms mentioned in this paper in terms of tracking capability, convergence speed and steady-state error. [ABSTRACT FROM AUTHOR]

Designing Pt-based electrocatalysts with high catalytic activity and CO tolerance is challenging but extremely desirable for alkaline hydrogen oxidation reaction. Herein we report the design of a series of single-atom lanthanide (La, Ce, Pr, Nd, and Lu)-embedded ultrasmall Pt nanoclusters for efficient alkaline hydrogen electro-oxidation catalysis based on vapor filling and spatially confined reduction/growth of metal species. Mechanism studies reveal that oxophilic single-atom lanthanide species in Pt nanoclusters can serve as the Lewis acid site for selective OH- adsorption and regulate the binding strength of intermediates on Pt sites, which promotes the kinetics of hydrogen oxidation and CO oxidation by accelerating the combination of OH− and *H/*CO in kinetics and thermodynamics, endowing the electrocatalyst with up to 14.3-times higher mass activity than commercial Pt/C and enhanced CO tolerance. This work may shed light on the design of metal nanocluster-based electrocatalysts for energy conversion. Exploring enhanced catalysts for alkaline hydrogen oxidation with high catalytic activity and CO tolerance is highly desired yet challenging. Here, the authors report single-atom lanthanide embedded Pt nanoclusters with high activities and durability. [ABSTRACT FROM AUTHOR]

A brand series employs various letters which make such variations in brand names relatively comparable. However, scant attention has been paid to the influence of alphabetic order in a brand series on consumers' preferences(liking). This research aims to investigate the influence of alphabetic order in a brand series on consumers' preferences(liking) based on space–time congruity theory. With 4 experiments, this paper examines how the alphabetic order in a brand series influences consumers' preferences(liking) and uncovers the underlying psychological mechanism that connects alphabetic order in a brand series and consumers' preferences(liking). The findings indicate that a brand series employing a late letter receives more favors than a comparatively early letter. Newness perception mediates the effect of alphabetic order in brands on consumers' preferences(liking). For the products which accord with "new means advantages" (the time value for these products is "new means more advantages and better performances than old"), a brand series employing a late letter receives more favors than a comparatively early letter. However, for the products which accord with "old means advantages" (the time value for these products is "old means more advantages and better performances than new"), this effect is the opposite. The effect of alphabetic order in a brand series on consumers' preferences(liking) is only significant when consumers are in high involvement condition. The paper provides new insight into the influence of alphabetic order in a brand series on consumers' preferences. [ABSTRACT FROM AUTHOR]

Soil is the largest terrestrial reservoir of organic carbon and is central for climate change mitigation and carbon-climate feedbacks. Chemical and physical associations of soil carbon with minerals play a critical role in carbon storage, but the amount and global capacity for storage in this form remain unquantified. Here, we produce spatially-resolved global estimates of mineral-associated organic carbon stocks and carbon-storage capacity by analyzing 1144 globally-distributed soil profiles. We show that current stocks total 899 Pg C to a depth of 1 m in non-permafrost mineral soils. Although this constitutes 66% and 70% of soil carbon in surface and deeper layers, respectively, it is only 42% and 21% of the mineralogical capacity. Regions under agricultural management and deeper soil layers show the largest undersaturation of mineral-associated carbon. Critically, the degree of undersaturation indicates sequestration efficiency over years to decades. We show that, across 103 carbon-accrual measurements spanning management interventions globally, soils furthest from their mineralogical capacity are more effective at accruing carbon; sequestration rates average 3-times higher in soils at one tenth of their capacity compared to soils at one half of their capacity. Our findings provide insights into the world's soils, their capacity to store carbon, and priority regions and actions for soil carbon management. Mineral-organic associations play a key role in soil carbon preservation. Here, Georgiou et al. produce global estimates of mineral-associated soil carbon, providing insight into the world's soils and their capacity to store carbon [ABSTRACT FROM AUTHOR]

Quantifying the upper limit of stable soil carbon storage is essential for guiding policies to increase soil carbon storage. One pool of carbon considered particularly stable across climate zones and soil types is formed when dissolved organic carbon sorbs to minerals. We quantified, for the first time, the potential of mineral soils to sorb additional dissolved organic carbon (DOC) for six soil orders. We compiled 402 laboratory sorption experiments to estimate the additional DOC sorption potential, that is the potential of excess DOC sorption in addition to the existing background level already sorbed in each soil sample. We estimated this potential using gridded climate and soil geochemical variables within a machine learning model. We find that mid- and low-latitude soils and subsoils have a greater capacity to store DOC by sorption compared to high-latitude soils and topsoils. The global additional DOC sorption potential for six soil orders is estimated to be 107 ± 13 Pg C to 1 m depth. If this potential was realized, it would represent a 7% increase in the existing total carbon stock. [ABSTRACT FROM AUTHOR]

Soil organic carbon (SOC) can be defined by measurable chemical and physical pools, such as mineral-associated carbon, carbon physically entrapped in aggregates, dissolved carbon, and fragments of plant detritus. Yet, most soil models use conceptual rather than measurable SOC pools. What would the traditional pool-based soil model look like if it were built today, reflecting the latest understanding of biological, chemical, and physical transformations in soils? We propose a conceptual model-the Millennial model-that defines pools as measurable entities. First, we discuss relevant pool definitions conceptually and in terms of the measurements that can be used to quantify pool size, formation, and destabilization. Then, we develop a numerical model following the Millennial model conceptual framework to evaluate against the Century model, a widely-used standard for estimating SOC stocks across space and through time. The Millennial model predicts qualitatively similar changes in total SOC in response to single factor perturbations when compared to Century, but different responses to multiple factor perturbations. We review important conceptual and behavioral differences between the Millennial and Century modeling approaches, and the field and lab measurements needed to constrain parameter values. We propose the Millennial model as a simple but comprehensive framework to model SOC pools and guide measurements for further model development. [ABSTRACT FROM AUTHOR]

Purpose: Little is known about the biogeochemical properties of millennia-old soil organic matter (SOM) in boreal forest paleosols and whether these properties contribute to the persistence of several millennia-old SOM. In this study, we assessed the physicochemical properties of a well-drained paleosol and looked for links between these properties and the mineralizable carbon (C) fraction. Materials and methods: We studied a well-drained paleosol located under a typical forest podzol in Northern Sweden, in which up to 7-kyr-old SOM was preserved according to C dating. We assessed the elemental compositions of the outermost 2-μm and 10-nm soil particle surfaces by using energy-dispersive X-ray scanning electron microscopy and X-ray photoelectron spectroscopy, respectively. We also conducted a 5-week laboratory incubation of samples from both the paleosol and the podzol to quantify their mineralizable C fractions and analyzed the thermal stability of soil samples before and after incubation by using temperature-programmed desorption coupled with mass spectrometry techniques. Results and discussion: Proxies for weathering (i.e., total mineral surface area and Al/Si and Fe/Si ratios of particle surfaces) suggested that the paleosol was at the same weathering stage as the contemporary forming podzol. Mineral soil particle surfaces of both the paleosol and podzol were dominated by aliphatic and ether/alcohol C functional groups. The incubation and thermal analysis showed that the mineralizable C fraction of the paleosol was smaller than that of the podzol, and losses of thermally labile SOM due to microbial degradation during the incubations were only detected in the mineral free O horizon of the podzol. Moreover, the mineralizable C fraction of the sampled podzol-paleosol sequence was correlated to the proportion of ether/alcohol C functional groups at the outermost 10-nm soil particle surfaces. Conclusions: Based on the links between microbial decomposition and the chemistry of soil particle surfaces and the thermal stability difference between organic and mineral soils induced by microbial decomposition, we conclude that the intrinsic chemical properties of SOM and its chemical surroundings is important for SOM preservation over a millennia timescale in the studied soil. [ABSTRACT FROM AUTHOR]

Organic carbon (C) associated with fine soil particles (<20 μm) is relatively stable and accounts for a large proportion of total soil organic C (SOC). The soil C saturation concept proposes a maximal amount of SOC that can be stabilized in the fine soil fraction, and the soil C saturation deficit (i.e., the difference between current SOC and the maximal amount) is presumed to affect the capacity, magnitude, and rate of SOC storage. In this study, we argue that predictions using current models underestimate maximal organic C stabilization of fine soil particles due to fundamental limitations of using least-squares linear regression. The objective was to improve predictions of maximal organic C stabilization by using two alternative approaches; one mechanistic, based on organic C loadings, and one statistical, based on boundary line analysis. We collected 342 data points on the organic C content of fine soil particles, fine particle mass proportions in bulk soil, dominant soil mineral types, and land use types from 32 studies. Predictions of maximal organic C stabilization using linear regression models are questionable because of the use of data from soils that may not be saturated in SOC and because of the nature of regression itself, resulting in a high proportion of presumed over-saturated samples. Predictions of maximal organic C stabilization using the organic C loading approach fit the data for soils dominated by 2:1 minerals well, but not soils dominated by 1:1 minerals; suggesting that the use of a single value for specific surface area, and therefore a single organic C loading, to represent a large dataset is problematic. In boundary line analysis, only data representing soils having reached the maximal amount (upper tenth percentile) were used. The boundary line analysis estimate of maximal organic C stabilization (78 ± 4 g C kg fraction) was more than double the estimate by the linear regression approach (33 ± 1 g C kg fraction). These results show that linear regression models do not adequately predict maximal organic C stabilization. Soil properties associated with soil mineralogy, such as specific surface area and organic C loading, should be incorporated to generate more mechanistic models for predicting soil C saturation, but in their absence, statistical models should represent the upper envelope rather than the average value. [ABSTRACT FROM AUTHOR]