Process and mechanism of preparing metallized blast furnace burden from metallurgical dust and sludge.

Metallurgical dust and sludge are solid waste resources with recycling value. In recent years, rotary hearth furnace has become the most important means to treat metallurgical dust and sludge because of its wide range of raw materials and strong treatment capacity. In this study blast furnace ash and converter sludge were selected as the research objects, and high-quality metallized pellets were prepared based on the rotary hearth furnace process. The strength changed of pellets, the reduction process of iron oxides and the removal process of zinc during the roasting of pellets in rotary hearth furnace were studied. To explore the reasonable roasting condition for preparing metallized pellets in rotary hearth furnace. The optimum roasting temperature of the pellets was 1250℃ and the roasting time was 25 min. The compressive strength, metallization rate and dezincification rate of metallized pellets reached 1361N, 97.44% and 95.67%, respectively. The efficient resource utilization of various metallurgical dust and sludge is realized.

An outlier detection-based method for artifact removal of few-channel EEGs.

Objective.The electroencephalogram (EEG) is one of the most important brain-imaging tools. The few-channel EEG is more suitable and affordable for practical use as a wearable device. Removing artifacts from collected EEGs is a prerequisite for accurately interpreting brain function and state. Previous studies proposed methods combining signal decomposition with the blind source separation (BSS) algorithms, but most of them used threshold-based criteria for artifact rejection, resulting in a lack of effectiveness in removing specific artifacts and the excessive suppression of brain activities. In this study, we proposed an outlier detection-based method for artifact removal under the few-channel condition.Approach. The underlying components (sources) were extracted using the decomposition-BSS schema. Based on our assumptions that in the feature space, the artifact-related components are dispersed, while the components related to brain activities are closely distributed, the artifact-related components were identified and rejected using one-class support vector machine. The assumptions were validated by visualizing the distribution of clusters of components.Main results. In quantitative analyses with semisimulated data, the proposed method outperformed the threshold-based methods for various artifacts, including muscle artifact, ocular artifact, and power line noise. With a real dataset and an event-related potential dataset, the proposed method demonstrated good performance in real-life situations.Significance. This study provided a fully data-driven and adaptive method for removing various artifacts in a single process without excessive suppression of brain activities.

Kinetics of Reduction in Stages of Pellets Prepared from the Bayan Obo Iron Ore Concentrate.

To explore the reduction swelling process of pellets prepared from the Bayan Obo iron ore concentrate, based on the iron oxide reduction theory of pellets, the reduction of pellets prepared from the Bayan Obo iron ore concentrate was analyzed by thermogravimetric experiments and kinetic calculations in three stages. The reason for the abnormal swelling of pellets prepared from the Bayan Obo iron ore concentrate was analyzed from the perspective of kinetics. The research results showed that carbon deposition occurred in the first stage of reduction. The second stage of reduction was controlled by an interfacial chemical reaction, and the activation energy of the reaction was 117.99 kJ/mol. The reaction energy barrier was higher and the reaction rate was slower, and therefore, the reduction swelling rate of pellets was lower at this stage. The third stage of reduction was controlled by internal diffusion, and the reaction activation energy was 15.9 kJ/mol. The reduction reaction of pellets occurs violently, and the reduction swelling behavior was remarkable at this stage.

Enhanced transmembrane electron transfer in Shewanella oneidensis MR-1 using gold nanoparticles for high-performance microbial fuel cells.

Low efficiency of extracellular electron transfer (EET) is a major bottleneck in developing high-performance microbial fuel cells (MFCs). Herein, we construct Shewanella oneidensis MR-1@Au for the bioanode of MFCs. Through performance recovery experiments of mutants, we proved that abundant Au nanoparticles not only tightly covered the bacteria surface, but were also distributed in the periplasm and cytoplasm, and even embedded in the outer and inner membranes of the cell. These Au nanoparticles could act as electron conduits to enable highly efficient electron transfer between S. oneidensis MR-1 and electrodes. Strikingly, the maximum power density of the S. oneidensis MR-1@Au bioanode reached up to 3749 mW m-2, which was 17.4 times higher than that with the native bacteria, reaching the highest performance yet reported in MFCs using Au or Au-based nanocomposites as the anode. This work elucidates the role of Au nanoparticles in promoting transmembrane and extracellular electron transfer from the perspective of molecular biology and electrochemistry, while alleviating bottlenecks in MFC performances.

Research on the Ash Melting Characteristics of Blended Coal Based on DFT Calculations.

Low-ash-melting-point bituminous coal and high-ash-melting-point anthracite coal are mixed and burned in different proportions. The ash melting characteristics of blended coal were determined experimentally. At the same time, the ash samples of bituminous coal, anthracite, and blended coal were analyzed by X-ray diffraction (XRD), and the ash melting characteristic improvement mechanism of blended coal was analyzed by quantum chemical calculations. The results show that when high-ash-melting-point anthracite is added, the ash melting characteristics of blended coal are improved, and the deformation temperature, softening temperature, hemispheric temperature, and flow temperature of the blended coal are significantly increased. The melting point of blended coal ash with a bituminous coal ratio of less than 50% can meet the requirements of blast furnace injection. The reason for the improved melting characteristics of the blended coal ash is that mullite in anthracite ash reacts with gehlenite in bituminous coal ash during the combustion process to produce anorthite.