Solid Electrolyte Interphase Recombination on Graphene Nanoribbons for Lithium Anode.

The practical application of lithium metal batteries is hindered by the lithium dendrite issue, which is seriously affected by the composition and structure of the solid electrolyte interphase (SEI). Modifying the SEI can regulate lithium dendrite formation and growth. Here, we experimentally realize a Li protective layer of LiTFSI-ether electrolyte induced a natural SEI grafted on graphene nanoribbons (SEI@GNRs) via their in situ reactions. The experimental results and theoretical calculations uncover that the 3D structure of SEI@GNRs can reduce the local current density and Li+ flux. The natural SEI in SEI@GNRs, especially the rich inorganic species of LiF, Li3N, and Li2S, decreases the Li+ nucleation overpotential, makes Li+ ion deposition and nucleation uniform, and isolates electron transport. Their synergetic effect suppresses Li dendrite formation and growth, increasing the electrochemical performance of lithium metal batteries. The design strategy is beneficial for the development of lithium metal batteries.

Uniting Young's modulus and the flexibility of solid-state electrolytes for high-performance Li-batteries at room temperature.

The use of solid-state composite electrolytes is a promising strategy to advance all-solid-state batteries. Great efforts have been devoted to improving the ionic conductivity of electrolytes, while little attention has been paid to studying the effect of their mechanical properties on electrochemical performance. The Young's modulus and flexibility are two important and contrary mechanical properties co-existing in electrolytes. Their effect on the electrochemical performance of all-solid-state batteries is important. Here, we study the effect of Young's modulus and flexibility based on a designed sandwich-structured solid-state composite electrolyte (SSCE) with high ionic conductivity (4.57 × 10-4 S cm-1 at 25 °C). In the SSCE, the middle layer with 9 : 1 : 0.5 mass ratio of Li6.4La3Zr1.4Ta0.6O12, poly(vinylidene fluoride-co-hexafluoropropylene) and bis(trifluoromethane)sulfonimide lithium is sandwiched by two outer layers with a 0.1 : 1 : 0.5 mass ratio among them, which can effectively suppress lithium dendrites and have intimate contact with the electrodes, leading to Li|SSCE|LiFePO4 with promising rate performance (155.5 mA h g-1 at 0.05 C and 124.4 mA h g-1 at 1 C) and excellent cycling stability with 98.8% capacity retention after 450 cycles at 25 °C. This work demonstrates that all-solid-state batteries have greatly enhanced electrochemical performance by uniting Young's modulus and flexibility via SSCEs, and provides a feasible strategy for the development of all-solid-state batteries.

Prediction of composting maturity and identification of critical parameters for green waste compost using machine learning.

Ensuring the maturity of green waste compost is crucial to composting processes and quality control of compost products. However, accurate prediction of green waste compost maturity remains a challenge, as there are limited computational methods available. This study aimed to address this issue by employing four machine learning models to predict two indicators of green waste compost maturity: seed germination index (GI) and T value. The four models were compared, and the Extra Trees algorithm exhibited the highest prediction accuracy with R2 values of 0.928 for GI and 0.957 for T value. To identify the interactions between critical parameters and compost maturity, The Pearson correlation matrix and Shapley Additive exPlanations (SHAP) analysis were conducted. Furthermore, the accuracy of the models was validated through compost validation experiments. These findings highlight the potential of applying machine learning algorithms to predict green waste compost maturity and optimise process regulation.

Unconventional Bilateral Compressive Strained Ni-Ir Interface Synergistically Accelerates Alkaline Hydrogen Oxidation.

The alkaline hydrogen oxidation reaction (HOR) involves the coupling of adsorbed hydrogen (Had) and hydroxyl (OHad) species and is thus orders of magnitude slower than that in acid media. According to the Sabatier principle, developing electrocatalysts with appropriate binding energy for both intermediates is vital to accelerating the HOR though it is still challenging. Herein, we propose an unconventional bilateral compressive strained Ni-Ir interface (Ni-Ir(BCS)) as efficient synergistic HOR sites. Density functional theory (DFT) simulations reveal that the bilateral compressive strain effect leads to the appropriate adsorption for both Had and OHad, enabling their coupling thermodynamically spontaneous and kinetically preferential. Such Ni-Ir(BCS) is experimentally achieved by embedding sub-nanometer Ir clusters in graphene-loaded high-density Ni nanocrystals (Ni-Ir(BCS)/G). As predicted, it exhibits a HOR mass activity of 7.95 and 2.88 times those of commercial Ir/C and Pt/C together with much enhanced CO tolerance, respectively, ranking among the most active state-of-the-art HOR catalysts. These results provide new insights into the rational design of advanced electrocatalysts involving coordinated adsorption and activation of multiple reactants.

The accumulation and toxicity of ZIF-8 nanoparticles in Corbicula fluminea.

Metal-organic frameworks (MOFs) are promising new materials that have been intensively studied and possibly applied to various environmental remediation. However, little is known about the fate and risk of MOFs to living organisms in the water environment. Here, the toxic effects of ZIF-8 nanoparticles (NPs) on benthic organisms were confirmed by sub-chronic toxicity experiments (7 and 14 days) using Corbicula fluminea as the model organism. With exposure doses ranging from 0 to 50 mg/L, ZIF-8 NPs induced oxidative stress behaviors similar to the hormesis effect in the tissues of C. fluminea. The oxidative stress induced by ZIF-8 NPs and the released Zn2+ was the crucial cause of the toxic effects. Besides, we also found that the ZIF-8 NPs and dissolved Zn2+ may result in different mechanisms of toxicity and accumulation depending on the dosages. The Zn2+ release rate of ZIF-8 NPs was high at low dosages, leading to a higher proportion of Zn2+ taken up by C. fluminea than the particulate ZIF-8. Conversely, at high dosages, C. fluminea mainly ingested the ZIF-8 NPs and resulted in increased mortality. The results have important implications for understanding the fate and biological effects of ZIF-8 in natural aquatic environments.

Tensor Multi-Clustering Parallel Intelligent Computing Method Based on Tensor Chain Decomposition.

Adaptable methods for representing higher-order data with various features and high dimensionality have been demanded by the increasing usage of multi-sensor technologies and the emergence of large data sets. Arrays of multi-dimensional data, known as tensors, can be found in a variety of applications. Standard data that depicts things from a single point of view lacks the semantic richness, utility, and complexity of multi-dimensional data. Research into multi-clustering has taken off since traditional clustering methods are unable to handle large datasets. There are three main kinds of multi-clustering algorithms: Self-weighted Multiview Clustering (SwMC), Latent Multi-view Subspace Clustering (LMSC), and Multi-view Subspace Clustering with Intactness-Aware Similarity (MSC IAS) that are explored in this paper. To evaluate their performance, we do in-depth tests on seven real-world datasets. The three most important metrics Accuracy (ACC), normalized mutual information (NMI), and purity are grouped. Furthermore, traditional Principal Component Analysis (PCA) cannot uncover hidden components within multi-dimensional data. For this purpose, tensor decomposition algorithms have been presented that are flexible in terms of constraint selection and extract more broad latent components. In this examination, we also go through the various tensor decomposition methods, with an emphasis on the issues that classical PCA is designed to solve. Various tensor models are also tested for dimensionality reduction and supervised learning applications in the experiments presented here.

Insights into aqueous reduction of Cr(VI) by biochar and its iron-modified counterpart in the presence of organic acids.

Chromium (Cr) pollution in water has become an environmental and social problem because of the highly toxic nature of Cr(VI). Biochar has been widely used in Cr-containing wastewater treatment due to its adsorption advantage and intrinsic electron-donating ability. In this paper, Cr(VI) was taken as the target pollutant, and corn-straw derived biochar (BC) and its iron-modified counterpart (BC-Fe) were taken as the main adsorbents. The effects of fulvic acid (FA) and lactic acid (LA) on the adsorption efficiency of BC and BC-Fe in aqueous solution were discussed, and the internal reaction mechanism was revealed by SEM, FTIR, XPS, and Zeta potential analysis. The results showed that the BC-Fe pyrolyzed at 600 °C (i.e., BC-Fe600) had good magnetic property and adsorption effect across a wide pH range (pH 3-9) (the maximum removal efficiency was 96%). At the same time, LA had a concentration-dependent promoting effect on Cr(VI) adsorption in the BC600. However, the addition of FA and LA both inhibited the adsorption of Cr(VI) by BC-Fe600 at pH = 5 and 7, with LA showing a more inhibiting effect on Cr(VI) removal (decreased by 16.09% at pH 5) than FA (decreased by 2.09% at pH 5). The addition of FA and LA caused the surface potential of BC-Fe600 to drop, resulting in an increasing electrostatic repulsion between Cr(VI) and the material. However, LA increased the reduction of Cr(VI) on BC-Fe600, possibly through the combined effects of the electron-donating ability of LA and the photolysis of Fe(III)-lactate complexes.

Removal of Cr(VI) by polyaniline embedded polyvinyl alcohol/sodium alginate beads - Extension from water treatment to soil remediation.

Efficient nano-scale chromium (Cr) remediating agents used in the water industry may find their application in soil difficult because of the strong aggregation effect. In this study, a millimeter-sized PANI/PVA/SA composite (PPS) was synthesized by embedding polyaniline (PANI) into polyvinyl alcohol (PVA)/sodium alginate (SA) gel beads. Additionally, the PPS was used to recover hexavalent chromium (Cr(VI)) contaminated water and soil to study the remediation impacts and mechanism. Results showed that the PPS was an irregular sphere with a pore size of 24.24 nm and exhibited strong adsorption capacity (83.1 mg/g) for removing Cr(VI) in water. The Cr(VI) adsorption by PPS could be well described with the pseudo-second-order kinetics and the Redlich-Peterson isotherm model, indicating that the chemical reactions were the controlling step in the Cr(VI) adsorption process. PPS also exhibited excellent physicochemical properties (< 13 mg/L TOC release) and reusability (efficiency of 95.25% after four runs) for Cr(VI) removal. Soil incubation results showed that the 5% PPS (5PPS) treatment could efficiently remove 24.17% of total Cr and 52.47% of Cr(VI) in the contaminated soil after 30 days. Meanwhile, the water-soluble and the leaching Cr contents were decreased by 43.37% and 61.78% in the 5PPS group, respectively. Elemental speciation by XPS revealed that Cr(VI) removal from solution and soil proceeded mainly by electrostatic attraction, reduction, and complexation/chelation. The study implied that PPS could be a useful amendment to remediate both the Cr(VI)-contaminated water and soil.