Jiwei Hu

This study investigated the pollution characteristics of heavy metals (Ni, Cu, Zn, As, Cd, Hg, Pb) in the sediments of the Hongfeng Reservoir in Guizhou. The fuzzy comprehensive evaluation method was used to evaluate the pollution level of heavy metals in the study area. The toxicity risk index method determined the biological harmful toxicity of heavy metals and the principal component analysis method determined the source of pollution of the heavy metals. The results show that the pollution level of heavy metals in the study area ranges from no pollution to strong pollution, and Ni and Zn have strong biological toxicity. According to the principal component analysis, domestic and industrial sewage and agricultural activities are the main pollution sources of Cu, Ni and Zn. The pollution sources of Cd, Pb and As are mainly the discharge of pollutants around the reservoir, industrial activities and human activities.

To study the spatial distribution characteristics of soil organic carbon (SOC) coupled with rocky desertification, 1212 soil samples from 152 soil profiles were sampled from different karst landforms, including karst low hills/virgin forest (KLH) in Libo County, a karst peak-cluster depression (KPCD) in Xingyi County, a karst canyon (KC) in Guanling County, a karst plateau basin (KPB) in Puding County and a karst trough valley (KTV) in Yinjiang County. The spatial distribution characteristics of the responses of SOC, SOC density (SOCD), rocky desertification and soil bulk density (SBD) to different influencing factors were analyzed. The relationships among SOC, SOCD, rocky desertification and SBD were analyzed using Pearson correlation analysis. The SOC storage capacity was characterized by using SOCD, and then the SOC storage capacity in different evolution stages of karst landforms was assessed. The SOC contents of KLH, KPCD, KC, KPB and KTV ranged from 6.16 to 38.20 g·kg⁻¹, 7.42 to 27.08 g·kg⁻¹, 6.28 to 35.17 g·kg⁻¹, 4.62 to 23.79 g·kg⁻¹ and 5.24 to 37.85 g·kg⁻¹, respectively, and their average SOCD values (0–100 cm) were 7.37, 10.79, 7.06, 8.51 and 7.84 kg·m⁻², respectively. The karst landforms as ordered by SOC storage capacity were KPCD > KPB > KLH > KTV > KC. The SOC content was negatively correlated with the SBD; light rocky desertification may lead to SOC accumulation. The rocky desertification degree and SBD were closely associated with slope position and gradient. Rocky desertification first increased, then decreased from mountain foot to summit, and increased with increasing slope gradient. However, the SBD decreased from mountain foot to summit and with increasing slope gradient. The SOC contents on the northern aspect of the mountains were generally higher than the other aspects. In summary, rock outcrops controlled the SOC contents in the studied regions. The slope position, gradient and aspect influenced the composition and distribution of vegetation, which influenced the evolution of rocky desertification. Therefore, these factors indirectly affected the SOC content. Additionally, the SOCD decreased with increasing rocky desertification. During the different evolution stages of karst landforms, the SOC storage capacity first decreases, then increases.

Advanced oxidation (e.g., fenton-like reagent oxidation and ozone oxidation) is a highly important technology that uses strong oxidizing free radicals to degrade organic pollutants and mineralize them. The fenton-like reactions have the characteristics of low cost, simple operation, thorough reaction and no secondary pollution. Fenton-like reagents refer to a strong oxidation system composed of transition metal ions (e.g., Fe³⁺, Mn²⁺ and Ag⁺) and oxidants (hydrogen peroxide, potassium persulfate, sodium persulfate, etc). Graphene and carbon nanotube possess a distinctive mechanical strength, flexibility, electrical and thermal conductivity and a very large specific surface area, which can work as an excellent carrier to disperse the catalyst and prevent its agglomeration. Fullerene can synergize with iron-based materials to promote the reaction of hydroxyl groups with organic pollutants and enhance the catalytic effect. Fenton-like catalysts influence the catalytic behavior by inducing electron transfer under strong interactions with the support. Due to the short lifespan of free radicals, the treatment effect is usually enhanced with the assistance of external conditions (ultraviolet and electric fields) to expand the application of fenton-like catalysts in water treatment. There are mainly light-fenton, electro-fenton and photoelectric-fenton methods. Fenton-like catalysts can be prepared by hydrothermal method, impregnation and coordination-precipitation approaches. The structures and properties of the catalysts are characterized by a variety of techniques, such as high-resolution transmission electron microscopy, high-angle annular dark-field scanning transmission electron microscopy and X-ray absorption near-edge structure spectroscopy. In this paper, we review the mechanisms, preparation methods, characterizations and applications status of fenton-like reagents in industrial wastewater treatment, and summarize the recycling of these catalysts and describe prospects for their future research directions.

The recent application of computer vision to disassembly and remanufacturing has pushed forward this field significantly. In disassembling the laptop, we find that the existing positioning screw methods such as hough transform and template matching were not suitable for black laptops, so we propose a new method to solve this problem. We use RCF network to locate the screw hole contour, and make two improvements according to the characteristics of small screw hole size: 1. A feature integration module is added to RCF network to increase multi-scale features.2. A modulating factor is added to the loss function to enhance the attention to the indistinguishable pixels. Our approach has shown good results on black laptops and has higher ODS and OIS than the original RCF network and the existing method.

Extensive use of fossil fuels can lead to energy depletion and serious environmental pollution. Therefore, it is necessary to solve these problems by developing clean energy. Graphene materials own the advantages of high electrocatalytic activity, high conductivity, excellent mechanical strength, strong flexibility, large specific surface area and light weight, thus giving the potential to store electric charge, ions or hydrogen. Graphene-based nanocomposites have become new research hotspots in the field of energy storage and conversion, such as in fuel cells, lithium-ion batteries, solar cells and thermoelectric conversion. Graphene as a catalyst carrier of hydrogen fuel cells has been further modified to obtain higher and more uniform metal dispersion, hence improving the electrocatalyst activity. Moreover, it can complement the network of electroactive materials to buffer the change of electrode volume and prevent the breakage and aggregation of electrode materials, and graphene oxide is also used as a cheap and sustainable proton exchange membrane. In lithium-ion batteries, substituting heteroatoms for carbon atoms in graphene composite electrodes can produce defects on the graphitized surface which have a good reversible specific capacity and increased energy and power densities. In solar cells, the performance of the interface and junction is enhanced by using a few layers of graphene-based composites and more electron-hole pairs are collected; therefore, the conversion efficiency is increased. Graphene has a high Seebeck coefficient, and therefore, it is a potential thermoelectric material. In this paper, we review the latest progress in the synthesis, characterization, evaluation and properties of graphene-based composites and their practical applications in fuel cells, lithium-ion batteries, solar cells and thermoelectric conversion.

Karst landforms are widely distributed in Guizhou Province, and the karst terrain is complex. To investigate the spatial distribution characteristics of soil organic carbon (SOC) in topsoil in different karst landforms, a total of 920 samples were taken from different karst landforms. The study areas, Puding, Xingyi, Guanling, Libo and Yinjiang in Guizhou Province, represent the karst plateau (KP), karst peak-cluster depression (KPCD), karst canyon (KC), karst virgin forest (KVF) and karst trough valley (KTV) landforms, respectively. The characteristics of the SOC contents in areas with different vegetation, land use and soil types under different karst landforms were analyzed. The dimensionality of the factors was reduced via principal component analysis, the relationships among SOC content and different factors were subjected to redundancy analysis, and the effects of the main impact factors on SOC were discussed. The results showed that there was a large discrepancy in the SOC contents in the topsoil layers among different types of karst landforms, the changes in the SOC content in the topsoil layer were highly variable, and the discrepancy in the upper soil layer was higher than that in the lower soil layer. The SOC contents in the 0–50 cm topsoil layers in different karst landforms were between 7.76 and 38.29 g·kg⁻¹, the SOC content gradually decreased with increasing soil depth, and the descending order of the SOC contents in different karst landforms was KTV > KVF > KC > KPCD > KP.

Mesoporous Mn-doped Fe nanoparticle-modified reduced graphene oxide (Mn-doped Fe/rGO) was prepared through a one-step co-precipitation method, which was then used to eliminate ethyl violet (EV) in wastewater. The prepared Mn-doped Fe/rGO was characterized by X-ray diffraction, X-ray photoelectron spectroscopy, Raman spectroscopy, high-resolution transmission electron microscopy, scanning electron microscopy, energy dispersive spectroscopy, N₂-sorption, small angle X-ray diffraction and superconducting quantum interference device. The Brunauer–Emmett–Teller specific surface area of Mn-doped Fe/rGO composites was 104.088 m²/g. The EV elimination by Mn-doped Fe/rGO was modeled and optimized by artificial intelligence (AI) models (i.e., radial basis function network, random forest, artificial neural network genetic algorithm (ANN-GA) and particle swarm optimization). Among these AI models, ANN-GA is considered as the best model for predicting the removal efficiency of EV by Mn-doped Fe/rGO. The evaluation of variables shows that dosage gives the maximum importance to Mn-doped Fe/rGO removal of EV. The experimental data were fitted to kinetics and adsorption isotherm models. The results indicated that the process of EV removal by Mn-doped Fe/rGO obeyed the pseudo-second-order kinetics model and Langmuir isotherm, and the maximum adsorption capacity was 1000.00 mg/g. This study provides a possibility for synthesis of Mn-doped Fe/rGO by co-precipitation as an excellent material for EV removal from the aqueous phase.