Cu1-Fe Dual Sites for Superior Neutral Ammonia Electrosynthesis from Nitrate.

The electrochemical nitrate reduction reaction (NO3RR) is able to convert nitrate (NO3 -) into reusable ammonia (NH3), offering a green treatment and resource utilization strategy of nitrate wastewater and ammonia synthesis. The conversion of NO3 - to NH3 undergoes water dissociation to generate active hydrogen atoms and nitrogen-containing intermediates hydrogenation tandemly. The two relay processes compete for the same active sites, especially under pH-neutral condition, resulting in the suboptimal efficiency and selectivity in the electrosynthesis of NH3 from NO3 -. Herein, we constructed a Cu1-Fe dual-site catalyst by anchoring Cu single atoms on amorphous iron oxide shell of nanoscale zero-valent iron (nZVI) for the electrochemical NO3RR, achieving an impressive NO3 - removal efficiency of 94.8 % and NH3 selectivity of 99.2 % under neutral pH and nitrate concentration of 50 mg L-1 NO3 --N conditions, greatly surpassing the performance of nZVI counterpart. This superior performance can be attributed to the synergistic effect of enhanced NO3 - adsorption on Fe sites and strengthened water activation on single-atom Cu sites, decreasing the energy barrier for the rate-determining step of *NO-to-*NOH. This work develops a novel strategy of fabricating dual-site catalysts to enhance the electrosynthesis of NH3 from NO3 -, and presents an environmentally sustainable approach for neutral nitrate wastewater treatment.

Oxalate-Promoted SO2 Uptake and Oxidation on Iron Minerals: Implications for Secondary Sulfate Aerosol Formation.

Mineral dust serves as a significant source of sulfate aerosols by mediating heterogeneous sulfur dioxide (SO2) oxidation in the atmosphere. Given that a considerable proportion of small organic acids are deposited onto mineral dust via long-range transportation, understanding their impact on atmospheric SO2 transformation and sulfate formation is of great importance. This study investigates the effect of oxalate on heterogeneous SO2 uptake and oxidation phenomenon by in situ FTIR, theoretical calculation, and continuous stream experiments, exploiting hematite (Fe2O3) as an environmental indicator. The results highlight the critical role of naturally deposited oxalate in mononuclear monodentate coordinating surface Fe atoms of Fe2O3 that enhances the activation of O2 for oxidizing SO2 into sulfate. Meanwhile, oxalate increases the hygroscopicity of Fe2O3, facilitating H2O dissociation into reactive hydroxyl groups and further augmenting the SO2 uptake capacity of Fe2O3. More importantly, other conventional iron minerals, such as goethite and magnetite, as well as authentic iron-containing mineral dust, exhibit similar oxalate-promoted sulfate accumulation behaviors. Our findings suggest that oxalate-assisted SO2 oxidation on iron minerals is one of the important contributors to secondary sulfate aerosols, especially during the nighttime with high relative humidity.

A Salient Object Detection Method Based on Boundary Enhancement.

Visual saliency refers to the human's ability to quickly focus on important parts of their visual field, which is a crucial aspect of image processing, particularly in fields like medical imaging and robotics. Understanding and simulating this mechanism is crucial for solving complex visual problems. In this paper, we propose a salient object detection method based on boundary enhancement, which is applicable to both 2D and 3D sensors data. To address the problem of large-scale variation of salient objects, our method introduces a multi-level feature aggregation module that enhances the expressive ability of fixed-resolution features by utilizing adjacent features to complement each other. Additionally, we propose a multi-scale information extraction module to capture local contextual information at different scales for back-propagated level-by-level features, which allows for better measurement of the composition of the feature map after back-fusion. To tackle the low confidence issue of boundary pixels, we also introduce a boundary extraction module to extract the boundary information of salient regions. This information is then fused with salient target information to further refine the saliency prediction results. During the training process, our method uses a mixed loss function to constrain the model training from two levels: pixels and images. The experimental results demonstrate that our salient target detection method based on boundary enhancement shows good detection effects on targets of different scales, multi-targets, linear targets, and targets in complex scenes. We compare our method with the best method in four conventional datasets and achieve an average improvement of 6.2% on the mean absolute error (MAE) indicators. Overall, our approach shows promise for improving the accuracy and efficiency of salient object detection in a variety of settings, including those involving 2D/3D semantic analysis and reconstruction/inpainting of image/video/point cloud data.

Triangle Cl-Ag1 -Cl Sites for Superior Photocatalytic Molecular Oxygen Activation and NO Oxidation of BiOCl.

BiOCl photocatalysis shows great promise for molecular oxygen activation and NO oxidation, but its selective transformation of NO to immobilized nitrate without toxic NO2 emission is still a great challenge, because of uncontrollable reaction intermediates and pathways. In this study, we demonstrate that the introduction of triangle Cl-Ag1 -Cl sites on a Cl-terminated, (001) facet-exposed BiOCl can selectively promote one-electron activation of reactant molecular oxygen to intermediate superoxide radicals (⋅O2 - ), and also shift the adsorption configuration of product NO3 - from the weak monodentate binding mode to a strong bidentate mode to avoid unfavorable photolysis. By simultaneously tuning intermediates and products, the Cl-Ag1 -Cl-landen BiOCl achieved >90 % NO conversion to favorable NO3 - of high selectivity (>97 %) in 10 min under visible light, with the undesired NO2 concentration below 20 ppb. Both the activity and the selectivity of Cl-Ag1 -Cl sites surpass those of BiOCl surface sites (38 % NO conversion, 67 % NO3 - selectivity) or control O-Ag1 -O sites on a benchmark photocatalyst P25 (67 % NO conversion and 87 % NO3 - selectivity). This study develops new single-atom sites for the performance enhancement of semiconductor photocatalysts, and also provides a facile pathway to manipulate the reactive oxygen species production for efficient pollutant removal.

Locally Asymmetric BiOBr for Efficient Exciton Dissociation and Selective O2 Activation toward Oxidative Coupling of Amines.

Two-dimensional (2D) layered photocatalysts with highly ordered out-of-plane symmetry usually display robust excitonic effects, thus being ineffective in driving catalytic reactions that necessitate unchained charge carriers. Herein, taking 2D BiOBr as a prototype model, we implement a superficial asymmetric [Br-Bi-O-Bi] stacking in the out-of-plane direction by selectively stripping off the top-layer Br of BiOBr. This local asymmetry disrupts the diagnostic confinement configuration of BiOBr to urge energetic exciton dissociation into charge carriers and further contributes to the emergence of a surface dipole field that powers the subsequent separation of transient electron-hole pairs. Distinct from the symmetric BiOBr, which activates O2 into 1O2 via an exciton-mediated energy transfer, surface asymmetric BiOBr favors selective O2 activation into ·O2- for a broad range of amine-to-imine conversions. Our work here not only presents a paradigm for asymmetric photocatalyst design but also expands the toolkit available for regulating exciton behaviors in semiconductor photocatalytic systems.

Identification of Cancer Hallmarks Based on the Gene Co-expression Networks of Seven Cancers.

Identifying the hallmarks of cancer is essential for cancer research, and the genes involved in cancer hallmarks are likely to be cancer drivers. However, there is no appropriate method in the current literature for identifying genetic cancer hallmarks, especially considering the interrelationships among the genes. Here, we hypothesized that "dense clusters" (or "communities") in the gene co-expression networks of cancer patients may represent functional units regarding cancer formation and progression, and the communities present in the co-expression networks of multiple types of cancer may be cancer hallmarks. Consequently, we mined the conserved communities in the gene co-expression networks of seven cancers in order to identify candidate hallmarks. Functional annotation of the communities showed that they were mainly related to immune response, the cell cycle and the biological processes that maintain basic cellular functions. Survival analysis using the genes involved in the conserved communities verified that two of these hallmarks could predict the survival risks of cancer patients in multiple types of cancer. Furthermore, the genes involved in these hallmarks, one of which was related to the cell cycle, could be useful in screening for cancer drugs.