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Hierarchical Amorphous Vanadium Oxide and Carbon Nanotubes Microspheres with Strong Interface Interaction for Superior Performance Aqueous Zinc-ion Batteries. [Display omitted] Aqueous zinc-ion batteries have attracted more and more attention due to their safety, environmental benignity and high theoretical capacity. However, the lack of appropriate cathode materials with high capacity and long cycle life have become an obstacle to the development of aqueous zinc-ion batteries. Herein, the hierarchical amorphous vanadium oxide and carbon nanotubes (a-V 2 O 5 @CNTs) microspheres with strong interface interaction were successfully prepared by combing facile spray drying technique with annealing treatment. Benefiting from the a-V 2 O 5 amorphous characters, CNTs framework high conductivity and hierarchical microspheres with strong interface interaction, the a-V 2 O 5 @CNTs exhibited abundant active sites, fast reaction kinetics as well as eminent structure stability. As a promising electrode material, the a-V 2 O 5 @CNTs displayed high specific capacity (480 mAh g−1 at 0.5 A g−1), good rate capability and long-term stability under high current density (158 mAh g−1 at 30 A g−1 over 1000 cycles). Meanwhile, the corresponding mechanism was further illustrated through different characterizations. Furthermore, the as-assembled flexible pouch battery based on the a-V 2 O 5 @CNTs delivered outstanding flexibility and feasibility. Hence, this work provides a new idea for developing high performance cathode materials of aqueous zinc-ion batteries. [ABSTRACT FROM AUTHOR]

Semi-arid regions present unique challenges for maintaining aquatic biological integrity due to their complex evolutionary mechanisms. Uncovering the spatial patterns of aquatic biological integrity in these areas is a challenging research task, especially under the compound environmental stress. Our goal is to address this issue with a scientifically rigorous approach. This study aims to explore the spatial analysis and diagnosis method of aquatic biological based on the combination of machine learning and statistical analysis, so as to reveal the spatial differentiation patterns and causes of changes of aquatic biological integrity in semi-arid regions. To this end, we have introduced an innovative approach that combines XGBoost-SHAP and Fuzzy C-means clustering (FCM), we successfully identified and diagnosed the spatial variations of aquatic biological integrity in the Wei River Basin (WRB). The study reveals significant spatial variations in species number, diversity, and aquatic biological integrity of phytoplankton, serving as a testament to the multifaceted responses of biological communities under the intricate tapestry of environmental gradients. Delving into the depths of the XGBoost-SHAP algorithm, we discerned that Annual average Temperature (AT) stands as the pivotal driver steering the spatial divergence of the Phytoplankton Integrity Index (P-IBI), casting a positive influence on P-IBI when AT is below 11.8 °C. The intricate interactions between hydrological variables (VF and RW) and AT, as well as between water quality parameters (WT, NO 3 –N, TP, COD) and AT, collectively sculpt the spatial distribution of P-IBI. The fusion of XGBoost-SHAP with FCM unveils pronounced north-south gradient disparities in aquatic biological integrity across the watershed, segmenting the region into four distinct zones. This establishes scientific boundary conditions for the conservation strategies and management practices of aquatic ecosystems in the region, and its flexibility is applicable to the analysis of spatial heterogeneity in other complex environmental contexts. • XGBoost-SHAP uncovers key drivers in semi-arid aquatic integrity evolution. • Innovative integration of XGBoost-SHAP with FCM maps aquatic spatial patterns. • AT dominates the distribution of aquatic biological integrity. • Distinct north-south trends in aquatic biological integrity of semi-arids revealed. [ABSTRACT FROM AUTHOR]

Z-scheme Bi 25 FeO 40 /BiOCl (BOFC) heterojunction possesses superior tetracyclines removal performance in the photocatalytic peroxymonosulfate oxidation process at low PMS concentrations. [Display omitted] • Z-scheme Bi 25 FeO 40 /BiOCl heterojunction was constructed for tetracyclines removal. • The photocatalytic PMS oxidation process was carried out at 0.08 M PMS. • Bi 25 FeO 40 /BiOCl/PMS/Vis system exhibits low toxicity. Photocatalytic peroxymonosulfate (PMS) oxidation systems demonstrate significant potential and promising prospects through the interconnection of photocatalytic and PMS oxidation for simultaneously achieving efficient pollutant removal and reduction of PMS dosage, which prevents resource wastage and secondary pollution. In this study, a Z-scheme Bi 25 FeO 40 /BiOCl (BOFC) heterojunction was constructed to carry out the photocatalytic PMS oxidation process for tetracyclines (TCs) pollutants at low PMS concentrations (0.08 mM). The photocatalytic PMS oxidation rate of Bi 25 FeO 40 /BiOCl composites for tetracycline hydrochloride (TCH), chlortetracycline (CTC), oxytetracycline (OTC) and doxycycline (DXC) reaches 86.6%, 83.6%, 86.7%, and 88.0% within 120 min. Simultaneously, the BOFC/PMS system under visible light (Vis) equally displayed the practical application prospects for the solo and mixed simulated TCs antibiotics wastewater. Based on the electron spin resonance (ESR) and X-ray photoelectron spectroscopy (XPS) valence band spectrum, a Z-scheme electron migration pathway was proposed to elucidate the mechanism underlying the performance enhancement of BOFC composites. Bi 25 FeO 40 in BOFC composites can serve as active site for activating PMS by the formation of Fe3+/Fe2+ cycle. Toxicity estimation software tool (T.E.S.T.) and mung beans planting experiment demonstrates that BOFC/PMS/Vis system can reduce toxicity of TCs wastewater. Therefore, BOFC/PMS/Vis system achieves efficient examination in different water environments and efficient utilization of PMS, which displays a scientific reference for achieving environmentally-friendly and resource-saving handling processes. [ABSTRACT FROM AUTHOR]

Rapid and accurate testing of wheat flour for illegal additives is important for maintaining food safety. In this study, a combination of NIR spectroscopy and partial least squares regression (PLSR) was used to predict the levels of two illegal additives (talc powder and benzoyl peroxide) in wheat flour. Different critical wavelength selection algorithms (competitive adaptive reweighted sampling, CARS; random frog, RF; Monte Carlo uninformative variable elimination, MCUVE; CARS-RF; CARS-MCUVE) were used to filter key wavelengths. In our study, R2P for talc and benzoyl peroxide in the full-wavelength PLSR model was 0.995 and 0.964, respectively. The CARS-RF and RF were screened for 10 effective wavelengths. In wheat flour containing talc, the R2P and RPD of the model using the CARS-RF were 0.995 and 14.796, respectively. In wheat flour containing benzoyl peroxide, the R2P and RPD of the model using the RF were 0.923 and 3.697, respectively. CARS-RF and RF algorithms had great potential to accurately predict illegal additives. • NIR spectroscopy of wheat flour containing talc and benzoyl peroxide were collected. • Full-wavelength NIR spectroscopy and PLSR were used for modeling. • The 5 key wavelength algorithm was used to screen the key wavelength. • Both CARS-RF and RF algorithms screened out 10 key wavelengths. • CARS-RF and RF algorithms could predict the illegal additives in flour very well. [ABSTRACT FROM AUTHOR]