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Photocatalytic processes are efficient methods to solve water contamination problems, especially considering dyeing wastewater disposal. However, high-efficiency photocatalysts are usually very expensive and have the risk of heavy metal pollution. Recently, an iron oxides@hydrothermal carbonation carbon (HTCC) heterogeneous catalyst was prepared by our group through co-hydrothermal treatment of carbohydrates and zinc extraction tailings of converter dust. Herein, the catalytic performance of the iron oxides@HTCC was verified by a non-biodegradable dye, methylene blue (MB), and the catalytic mechanism was deduced from theoretical simulations and spectroscopic measurements. The iron oxides@HTCC showed an excellent synergy between photocatalysis and Fenton-like reactions. Under visible-light illumination, the iron oxides@HTCC could be excited to generate electrons and holes, reacting with H2O2 to produce
The catalytic effect of FeCoNiCrMo high entropy alloy nanosheets on the hydrogen storage performance of magnesium hydride (MgH2) was investigated for the first time in this paper. Experimental results demonstrated that 9wt% FeCoNiCrMo doped MgH2 started to dehydrogenate at 200°C and discharged up to 5.89wt% hydrogen within 60 min at 325°C. The fully dehydrogenated composite could absorb 3.23wt% hydrogen in 50 min at a temperature as low as 100°C. The calculated de/hydrogenation activation energy values decreased by 44.21%/55.22% compared with MgH2, respectively. Moreover, the composite’s hydrogen capacity dropped only 0.28wt% after 20 cycles, demonstrating remarkable cycling stability. The microstructure analysis verified that the five elements, Fe, Co, Ni, Cr, and Mo, remained stable in the form of high entropy alloy during the cycling process, and synergistically serving as a catalytic union to boost the de/hydrogenation reactions of MgH2. Besides, the FeCoNiCrMo nanosheets had close contact with MgH2, providing numerous non-homogeneous activation sites and diffusion channels for the rapid transfer of hydrogen, thus obtaining a superior catalytic effect.
Tensile and shear fractures are significant mechanisms for rock failure. Understanding the fractures that occur in rock can reveal rock failure mechanisms. Scanning electron microscopy (SEM) has been widely used to analyze tensile and shear fractures of rock on a mesoscopic scale. To quantify tensile and shear fractures, this study proposed an innovative method composed of SEM images and deep learning techniques to identify tensile and shear fractures in red sandstone. First, direct tensile and preset angle shear tests were performed for red sandstone to produce representative tensile and shear fracture surfaces, which were then observed by SEM. Second, these obtained SEM images were applied to develop deep learning models (AlexNet, VGG13, and SqueezeNet). Model evaluation showed that VGG13 was the best model, with a testing accuracy of 0.985. Third, the features of tensile and shear fractures of red sandstone learned by VGG13 were analyzed by the integrated gradient algorithm. VGG13 was then implemented to identify the distribution and proportion of tensile and shear fractures on the failure surfaces of rock fragments caused by uniaxial compression and Brazilian splitting tests. Results demonstrated the model feasibility and suggested that the proposed method can reveal rock failure mechanisms.
The anisotropy of the structure and properties caused by the strong epitaxial growth of grains during laser powder bed fusion (L-PBF) significantly affects the mechanical performance of Inconel 718 alloy components such as turbine disks. The defects (lack-of-fusion, LoF) in components processed via L-PBF are detrimental to the strength of the alloy. The purpose of this study is to investigate the effect of laser scanning parameters on the epitaxial grain growth and LoF formation in order to obtain the parameter space in which the microstructure is refined and LoF defect is suppressed. The temperature field of the molten pool and the epitaxial grain growth are simulated using a multiscale model combining the finite element method with the phase-field method. The LoF model is proposed to predict the formation of LoF defects resulting from insufficient melting during L-PBF. Defect mitigation and grain-structure control during L-PBF can be realized simultaneously in the model. The simulation shows the input laser energy density for the as-deposited structure with fine grains and without LoF defects varied from 55.0–62.5 J·mm–3 when the interlayer rotation angle was 0o–90o. The optimized process parameters (laser power of 280 W, scanning speed of 1160 mm·s–1, and rotation angle of 67o) were computationally screened. In these conditions, the average grain size was 7.0 μm, and the ultimate tensile strength and yield strength at room temperature were (1111 ± 3) MPa and (820 ± 7) MPa, respectively, which is 8.8% and 10.5% higher than those of reported. The results indicating the proposed multiscale computational approach for predicting grain growth and LoF defects could allow simultaneous grain-structure control and defect mitigation during L-PBF.
Galena (PbS) and chalcopyrite (CuFeS2) are sulfide minerals that exhibit good floatability characteristics. Thus, efficiently separating them via common flotation is challenging. Herein, a new method of surface sulfuric acid corrosion in conjunction with flotation separation was proposed, and the efficient separation of galena and chalcopyrite was successfully realized. Contact angle test results showed a substantial decrease in surface contact angle and a selective inhibition of surface floatability for corroded galena. Meanwhile, the contact angle and floatability of corroded chalcopyrite remained almost unaffected. Scanning electron microscope results confirmed that sulfuric acid corrosion led to the formation of a dense oxide layer on the galena surface, whereas the chalcopyrite surface remained unaltered. X-ray photoelectron spectroscopy results showed that the chemical state of S2− on the surface of corroded galena was oxidized to
Anion exchange membrane (AEM) electrolysis is a promising membrane-based green hydrogen production technology. However, AEM electrolysis still remains in its infancy, and the performance of AEM electrolyzers is far behind that of well-developed alkaline and proton exchange membrane electrolyzers. Therefore, breaking through the technical barriers of AEM electrolyzers is critical. On the basis of the analysis of the electrochemical performance tested in a single cell, electrochemical impedance spectroscopy, and the number of active sites, we evaluated the main technical factors that affect AEM electrolyzers. These factors included catalyst layer manufacturing (e.g., catalyst, carbon black, and anionic ionomer) loadings, membrane electrode assembly, and testing conditions (e.g., the KOH concentration in the electrolyte, electrolyte feeding mode, and operating temperature). The underlying mechanisms of the effects of these factors on AEM electrolyzer performance were also revealed. The irreversible voltage loss in the AEM electrolyzer was concluded to be mainly associated with the kinetics of the electrode reaction and the transport of electrons, ions, and gas-phase products involved in electrolysis. Based on the study results, the performance and stability of AEM electrolyzers were significantly improved.
Solidification structure is a key aspect for understanding the mechanical performance of metal alloys, wherein composition and casting parameters considerably influence solidification and determine the unique microstructure of the alloys. By following the principle of free energy minimization, the phase-field method eliminates the need for tracking the solid/liquid phase interface and has greatly accelerated the research and development efforts geared toward optimizing metal solidification microstructures. The recent progress in the application of phase-field simulation to investigate the effect of alloy composition and casting process parameters on the solidification structure of metals is summarized in this review. The effects of several typical elements and process parameters, including carbon, boron, silicon, cooling rate, pulling speed, scanning speed, anisotropy, and gravity, on the solidification structure are discussed. The present work also addresses the future prospects of phase-field simulation and aims to facilitate the widespread applications of phase-field approaches in the simulation of microstructures during solidification.
Electric arc furnace dust (EAFD) is a hazardous waste but can also be a potential secondary resource for valuable metals, such as Zn and Fe. Given the increased awareness of carbon emission reduction, energy conservation, and environmental protection, hydrometallurgical technologies for the detoxification and resource use of EAFD have been developing rapidly. This work summarizes the generation mechanisms, compositions, and characteristics of EAFD and presents a critical review of various hydrometallurgical treatment methods for EAFD, e.g., acid leaching, alkaline leaching, salt leaching, and pretreatment–enhanced leaching methods. Simultaneously, the phase transformation mechanisms of zinc-containing components in acid and alkali solutions and pretreatment processes are expounded. Finally, two novel combined methods, i.e., oxygen pressure sulfuric acid leaching combined with composite catalyst preparation, and synergistic roasting of EAFD and municipal solid waste incineration fly ash combined with alkaline leaching, are proposed, which can provide future development directions to completely recycling EAFD by recovering valuable metals and using zinc residue.