Heavy Metal Pollution in Surface Water of Linglong Gold Mining Area, China

AbstractThe concentrations and distribution patterns of lead, mercury, zinc, copper, chromium, arsenic, cadmium in surface water of Linglong deposit area were discussed. The result shows that the surface water of Linglong mining area is seriously polluted by mercury, zinc and cadmium, which of the concentration are higher than the III class of National Surface Water Quality Standard, and moderately polluted by chromium and arsenic, which of the concentration conforms to the III class national surface water quality standard, and light polluted by lead and copper, which of the concentration conforms to the II class national surface water quality standard. The concentration of heavy metals in the gold deposit areas depends upon the distance from the pollution source and scalar transport in rivulet flows, decreases along the flow direction. The concentration and distribution of heavy metal pollutants in surface water are dominated by the geochemical situation and the pollution source, but seriously affected by mining leachate and chemical wastewater discharge

Automatic Ship Detection of Remote Sensing Images from Google Earth in Complex Scenes Based on Multi-Scale Rotation Dense Feature Pyramid Networks

Ship detection has been playing a significant role in the field of remote sensing for a long time but it is still full of challenges. The main limitations of traditional ship detection methods usually lie in the complexity of application scenarios, the difficulty of intensive object detection and the redundancy of detection region. In order to solve such problems above, we propose a framework called Rotation Dense Feature Pyramid Networks (R-DFPN) which can effectively detect ship in different scenes including ocean and port. Specifically, we put forward the Dense Feature Pyramid Network (DFPN), which is aimed at solving the problem resulted from the narrow width of the ship. Compared with previous multi-scale detectors such as Feature Pyramid Network (FPN), DFPN builds the high-level semantic feature-maps for all scales by means of dense connections, through which enhances the feature propagation and encourages the feature reuse. Additionally, in the case of ship rotation and dense arrangement, we design a rotation anchor strategy to predict the minimum circumscribed rectangle of the object so as to reduce the redundant detection region and improve the recall. Furthermore, we also propose multi-scale ROI Align for the purpose of maintaining the completeness of semantic and spatial information. Experiments based on remote sensing images from Google Earth for ship detection show that our detection method based on R-DFPN representation has a state-of-the-art performance.Comment: 14 pages, 11 figure

Recent research progress on imbibition system of nanoparticle-surfactant dispersions

Nanotechnology has been increasingly applied in the petroleum industry in recent years. In particular, dispersions consisting of nanoparticles and surfactants have been widely investigated. The imbibition system compounded by nanoparticle and surfactant was found to display a high efficiency in enhancing oil recovery. This paper briefly reviews the factors influencing imbibition efficiency. At the same time, the application and mechanism of the imbibition system of nanoparticle-surfactant dispersion in the field of enhanced oil recovery are introduced. Additionally, the limitations and challenges that the imbibition system of nanoparticle-surfactant dispersions may face in enhanced oil recovery applications are put forward. The current work reveals that the imbibition system with nanoparticle-surfactant dispersion is an ideal candidate for enhanced oil recovery in tight and low-permeability reservoirs.Document Type: Invited reviewCited as: Shao, W., Yang, J., Wang, H., Chang, J., Wu, H., Hou, J. Recent research progress on imbibition system of nanoparticle-surfactant dispersions. Capillarity, 2023, 8(2): 34-44. https://doi.org/10.46690/capi.2023.08.0

Functionalized carbophenes as high-capacity versatile gas adsorbents: An ab initio study

This study employs density functional theory (DFT) and density functional tight-binding theory (DFTB) to determine the adsorption properties of carbon dioxide (CO$_2$), methane (CH$_4$), and dihydrogen (H$_2$) in carbophenes functionalized with carboxyl (COOH), amine (NH$_2$), nitro (NO$_2$), and hydroxyl (OH) groups. We demonstrate that carbophenes are promising candidates as adsorbents for these gasses. Carbophenes have larger CO$_2$ and CH$_4$ adsorption energies than other next-generation solid-state capture materials. Yet, the low predicted desorption temperatures mean they can be beneficial as air scrubbers in confined spaces. Functionalized carbophenes have H$_2$ adsorption energies usually observed in metal-containing materials. Further, the predicted desorption temperatures of H$_2$ from carbophenes lie within the DOE Technical Targets for Onboard Hydrogen Storage for Light-Duty Vehicles (DOEHST) operating temperature range. The possibility of tailoring the degree of functionalization in combination with selecting sufficiently open carbophene structures that allow for multiple strong interactions without steric hindrance (crowding) effects, added to the multiplicity of possible functional groups alone or in combination, suggests that these very light materials can be ideal adsorbates for many gases. Tailoring the design to specific adsorption or separation needs would require extensive combinatorial investigations

All-small-molecule organic solar cells with over 14% efficiency by optimizing hierarchical morphologies

The high efficiency all-small-molecule organic solar cells (OSCs) normally require optimized morphology in their bulk heterojunction active layers. Herein, a small-molecule donor is designed and synthesized, and single-crystal structural analyses reveal its explicit molecular planarity and compact intermolecular packing. A promising narrow bandgap small-molecule with absorption edge of more than 930 nm along with our home-designed small molecule is selected as electron acceptors. To the best of our knowledge, the binary all-small-molecule OSCs achieve the highest efficiency of 14.34% by optimizing their hierarchical morphologies, in which the donor or acceptor rich domains with size up to ca. 70 nm, and the donor crystals of tens of nanometers, together with the donor-acceptor blending, are proved coexisting in the hierarchical large domain. All-small-molecule photovoltaic system shows its promising for high performance OSCs, and our study is likely to lead to insights in relations between bulk heterojunction structure and photovoltaic performance.Funding Agencies|Ministry of Science and Technology of ChinaMinistry of Science and Technology, China [2016YFA0200700, 2016YFF0203803]; National Natural Science Foundation of ChinaNational Natural Science Foundation of China [51961135103, 51973043, 21822503, 21534003, 21721002]; Beijing Nova ProgramBeijing Municipal Science &amp; Technology Commission [Z17110001117062]; Youth Innovation Promotion Association; K.C.Wong Education Foundation; Chinese Academy of SciencesChinese Academy of Sciences; Swedish Research Council VRSwedish Research Council [2018-06048, 2018-05484]</p

Comparative Study Reveals Insights of Sheepgrass (Leymus chinensis) Coping With Phosphate-Deprived Stress Condition

Sheepgrass [Leymus chinensis (Trin.) Tzvel] is a valuable forage plant highly significant to the grassland productivity of Euro-Asia steppes. Growth of above-ground tissues of L. chinensis is the major component contributing to the grass yield. Although it is generally known that this species is sensitive to ecosystem disturbance and adverse environments, detailed information of how L. chinensis coping with various nutrient deficiency especially phosphate deprivation (-Pi) is still limited. Here, we investigated impact of Pi-deprivation on shoot growth and biomass accumulation as well as photosynthetic properties of L. chinensis. Growth inhibition of Pi-deprived seedlings was most obvious and reduction of biomass accumulation and net photosynthetic rate (Pn) was 55.3 and 63.3%, respectively, compared to the control plants grown under Pi-repleted condition. Also, we compared these characters with seedlings subjected to low-Pi stress condition. Pi-deprivation caused 18.5 and 12.3% more reduction of biomass and Pn relative to low-Pi-stressed seedlings, respectively. Further analysis of in vivo chlorophyll fluorescence and thylakoid membrane protein complexes using 2D-BN/SDS-PAGE combined with immunoblot detection demonstrated that among the measured photosynthetic parameters, decrease of ATP synthase activity was most pronounced in Pi-deprived plants. Together with less extent of lipid peroxidation of the thylakoid membranes and increased ROS scavenger enzyme activities in the leaves of Pi-deprived seedlings, we suggest that the decreased activity of ATP synthase in their thylakoids is the major cause of the greater reduction of photosynthetic efficiency than that of low-Pi stressed plants, leading to the least shoot growth and biomass production in L. chinensis

Highly Efficient Transfer Hydrogenation of Biomass-Derived Furfural to Furfuryl Alcohol over Mesoporous Zr-Containing Hybrids with 5-Sulfosalicylic Acid as a Ligand

The catalytic transfer hydrogenation of biomass-derived furfural to furfuryl alcohol under mild conditions is an attractive topic in biorefinery. Herein, mesoporous Zr-containing hybrids (Zr-hybrids) with a high surface area (281.9&ndash;291.3 m2/g) and large pore volume (0.49&ndash;0.74 cm3/g) were prepared using the biomass-derived 5-sulfosalicylic acid as a ligand, and they were proven to be highly efficient for the Meerwein&ndash;Ponndorf&ndash;Verley reduction of furfural to furfuryl alcohol at 110 &deg;C, with the highest furfuryl alcohol yield reaching up to 97.8%. Characterizations demonstrated that sulfonic and carboxyl groups in 5-sulfosalicylic acid molecules were coordinated with zirconium ions, making zirconium ions fully dispersed, thus leading to the formation of very fine zirconia particles with the diameter of &lt;2 nm in mesoporous Zr-hybrids. The interaction between the 5-sulfosalicylic acid ligands and zirconium ions endowed mesoporous Zr-hybrids with relatively higher acid strength but lower base strength, which was beneficial for the selective reduction of furfural to furfuryl alcohol. A recycling study was performed over a certain mesoporous Zr-hybrid, namely meso-Zr-SA15, demonstrating that the yield and selectivity of furfuryl alcohol remained almost unchanged during the five consecutive reaction cycles. This study provides an optional method to prepare hybrid catalysts for biomass refining by using biomass-derived feedstock