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Two-dimensional conjugated coordination polymers exhibit remarkable charge transport properties, with copper-based benzenehexathiol (Cu-BHT) being a rare superconductor. However, the atomic structure of Cu-BHT has remained unresolved, hindering a deeper understanding of the superconductivity in such materials. Here, we show the synthesis of single crystals of Cu 3 BHT with high crystallinity, revealing a quasi-two-dimensional kagome structure with non-van der Waals interlayer Cu-S covalent bonds. These crystals exhibit intrinsic metallic behavior, with conductivity reaching 10 3  S/cm at 300 K and 10 4  S/cm at 2 K. Notably, superconductivity in Cu 3 BHT crystals is observed at 0.25 K, attributed to enhanced electron-electron interactions and electron-phonon coupling in the non-van der Waals structure. The discovery of this clear correlation between atomic-level crystal structure and electrical properties provides a crucial foundation for advancing superconductor coordination polymers, with potential to revolutionize future quantum devices., (© 2024. The Author(s).)

Dendrobium, a highly effective traditional Chinese medicinal herb, exhibits significant variations in efficacy and price among different varieties. Therefore, achieving an efficient classification of Dendrobium is crucial. However, most of the existing identification methods for Dendrobium make it difficult to simultaneously achieve both non-destructiveness and high efficiency, making it challenging to truly meet the needs of industrial production. In this study, we combined Laser-Induced Breakdown Spectroscopy (LIBS) with multivariate models to classify 10 varieties of Dendrobium. LIBS spectral data for each Dendrobium variety were collected from three circular medicinal blocks. During the data analysis phase, multivariate models to classify different Dendrobium varieties first preprocess the LIBS spectral data using Gaussian filtering and stacked correlation coefficient feature selection. Subsequently, the constructed fusion model is utilized for classification. The results demonstrate that the classification accuracy of 10 Dendrobium varieties reached 100%. Compared to Support Vector Machine (SVM), Random Forest (RF), and K-Nearest Neighbors (KNN), our method improved classification accuracy by 14%, 20%, and 20%, respectively. Additionally, it outperforms three models (SVM, RF, and KNN) with added Principal Component Analysis (PCA) by 10%, 10%, and 17%. This fully validates the excellent performance of our classification method. Finally, visualization analysis of the entire research process based on t-distributed Stochastic Neighbor Embedding (t-SNE) technology further enhances the interpretability of the model. This study, by combining LIBS and machine learning technologies, achieves efficient classification of Dendrobium, providing a feasible solution for the identification of Dendrobium and even traditional Chinese medicinal herbs.

Laser-Induced Breakdown Spectroscopy (LIBS) instruments are increasingly recognized as valuable tools for detecting trace metal elements due to their simplicity, rapid detection, and ability to perform simultaneous multi-element analysis. Traditional LIBS modeling often relies on empirical or machine learning-based feature band selection to establish quantitative models. In this study, we introduce a novel approach-simultaneous multi-element quantitative analysis based on the entire spectrum, which enhances model establishment efficiency and leverages the advantages of LIBS. By logarithmically processing the spectra and quantifying the cognitive uncertainty of the model, we achieved remarkable predictive performance (R 2 ) for trace elements Mn, Mo, Cr, and Cu (0.9876, 0.9879, 0.9891, and 0.9841, respectively) in stainless steel. Our multi-element model shares features and parameters during the learning process, effectively mitigating the impact of matrix effects and self-absorption. Additionally, we introduce a cognitive error term to quantify the cognitive uncertainty of the model. The results suggest that our approach has significant potential in the quantitative analysis of trace elements, providing a reliable data processing method for efficient and accurate multi-task analysis in LIBS. This methodology holds promising applications in the field of LIBS quantitative analysis., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The issue of water pollution has emerged as a formidable challenge, prompting a pressing need for solutions. The utilization of metal nanoparticles with surface plasmon resonance and semiconductor composite photocatalysts is regarded as a highly effective approach to solve this problem. g-C 3 N 4 is an effective catalyst for the degradation of organic pollutants. Its photocatalytic performance is usually enhanced by the use of the noble metal Au Ag. However, the high cost of these materials limits their application. In this study, we present the synthesis of Al NPs/g-C 3 N 4 nanocomposites using the bridging effect of ligands. The characterized of transmission electron microscopy (TEM), X-ray diffractometer (XRD) and ultraviolet-visible spectroscopy (UV-Vis) proved that Al NPs/g-C 3 N 4 with a wider light absorption range were successfully synthesized. The effects of ligands, (glutathione (GSH), glutamic acid (GAG), and cysteine (CYS)), Al diameter (40 to 200 nm) and the ratio of Al to g-C 3 N 4 (1:1 to 5:1) on the photocatalytic degradation of methylene blue (MB) by Al NPs/g-C 3 N 4 were also evaluated. The results showed that the optimum degradation efficiency of Al NPs/g-C 3 N 4 for MB at 5 mg/L reached 100% within 60 min, which was 11 times higher than that of pure g-C 3 N 4 . The principal analysis of Al enhancing the photocatalytic performance of g-C 3 N 4 was studied through transient photocurrent spectroscopy (TPC), electrochemical impedance spectroscopy (EIS), and steady-state transient fluorescence spectroscopy (PL). The results confirmed that hot carriers generated by localized surface plasmon resonance (LSPR) of Al nanoparticles increase the carrier concentration. In addition, the Schottky barrier generated by Al and g-C 3 N 4 could also improve the carrier separation rate and increase the carrier lifetime. This work is expected to solve the problem of organic wastewater treatment and lay the foundation for subsequent research on photocatalysis., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Hexavalent chromium (Cr(VI)) is a pollutant with high migration ability, and the destiny of Cr(VI) is highly correlated with ferrihydrite (Fh). Montmorillonite (Mt) is a clay mineral abundantly presents in nature. Although Cr(VI) adsorption on montmorillonite or ferrihydrite has been studied, Cr(VI) behaviors during the Fh-Cr-Mt coprecipitates transformation still remain unknown. In this study, calcium montmorillonite (Ca-Mt) or sodium montmorillonite (Na-Mt) was coprecipitated with ferrihydrite and Cr(VI). Effect of Ca-Mt (or Na-Mt) incorporation on coprecipitates transformation and Cr(VI) behaviors during aging were investigated. The results showed that Ca-Mt or Na-Mt incorporation inhibited the transformation of ferrihydrite in Fh-Cr-Ca-Mt or Fh-Cr-Na-Mt at the initial pH of 5.0, 7.0 and 9.0. During aging, two kinds of Mt were supposed to interact with Fh to form the FeOSi and FeOAl bonds, and thus the formation of hematite and goethite were limited. By testing the Cr(VI) distribution in each phase of coprecipitates during transformation, delay on Cr(VI) migration and redistribution could be found in systems added with montmorillonite, and Cr(VI) was retained in coprecipitates to a greater extent compared with the systems without montmorillonite addition. The results of this study contribute to increasing our knowledge about the role of clay minerals on the coprecipitates transformation when they coexist at different pH values. It is also significant for the heavy metals polluted sites repairing., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

TiO 2 is a catalyst that can effectively degrade organic pollutants with the following advantages, low cost, simplicity, and pollution-free nature. In recent years, the non-noble plasmonic metal Al has effectively improved the photocatalytic performance of TiO 2 . However, the current reports are limited to the photocatalytic performance of Al/TiO 2 on the substrate, which requires expensive large-scale vacuum equipment. In this study, monodispersed Al particles were proposed to enhance the photocatalysis of TiO 2 . The localized surface plasmon resonance (LSPR) effect of Al is proven by finite difference time domain method (FDTF) simulation. Then, Al/TiO 2 composites were prepared by combining monodispersed Al and TiO 2 . The influence of ligand (glutathione (GSH), glutamic acid (GAG), or 3-mercaptopropane acid (MPA)), Al size (40 to 300 nm), and the ratio of Al to TiO 2 (0.5:1 to 10:1) on the photocatalytic degradation of methylene blue (MB) by Al/TiO 2 were discussed. The obtained results showed that the Al/TiO 2 composite which were prepared with 200 nm Al particles, GSH as the ligand bridge, and an Al:TiO 2 ratio of 1:1 had the best MB degradation effect. It can degrade 97.7% of 10 mg/L MB in 100 min. The reaction rate of the Al/TiO 2 composite with the optimal photocatalytic performance is k=3.36×10 -2 min -1 , which is 10 times that of P25 TiO 2 . In addition, Al/TiO 2 has a good photocatalytic effect on rhodamine B (RhB) and crystal violet (CV). Therefore, Al/TiO 2 composites with the advantage of high efficiency are a type of potential photocatalytic material that can be used for the photocatalytic treatment of organic pollutants in water., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

In this study, the mixing mechanism and phase transition process of different metals during the sintering of tailings bricks with four different metal oxides (CuO, PbO, ZnO, and CdO) at temperatures ranging from 700 to 1100 °C for 2 h were investigated. The properties of the sintered product was characterized and analyzed, and the results showed that the main crystalline phases are quartz, cristobalite, hematite, and mullite while the metal oxides are ascribed to copper ferrite spinel (CuFe 2 O 4 ), gahnite (ZnAl 2 O 4 ), zinc ferrite spinel (ZnFe 2 O 4 ), lead feldspar (PbAl 2 Si 2 O 8 ), and cadmium feldspar (CdAl 2 Si 2 O 8 ). Further analysis indicates that the heavy metals were transited into spinel or silicate structures with favorable efficiency. This indicates a good heavy-metal fixation effect from the structural change after the sintering process. Finally, the leaching experiments of the sintered samples suggest that the metal leaching decreased to a low and stable value when the sintering temperature was higher than 950 °C, which meets the China standard (GB 5085.3-2007). The above results indicate that the sintering process facilitates the combination of Cu, Zn, Pb and Cd offering an effective and safe method for the application of materials that contain tailings., (Copyright © 2019 Elsevier Ltd. All rights reserved.)