国外某高磷鲕状赤铁矿直接还原—磁选降磷研究

以国外某高磷鲕状赤铁矿为研究对象进行脱磷研究，该高磷矿铁品位为55.81%，磷含量为0.72%，铁矿物主要为磁铁矿和赤铁矿，48.61%的磷存在于磷酸盐中，47.22%的磷分布于铁矿物中。研究了脱磷剂用量、秸秆炭用量、还原温度以及还原时间对粉末还原铁指标的影响。结果表明：无脱磷剂碳酸钙时，无法获得合格的指标；在碳酸钙用量为25%，秸秆炭用量为12.5%，还原温度1 200 ℃，还原时间为75 min，还原产品两段磨矿两段磁选的条件下，可获得铁品位、铁回收率以及磷含量分别为94.27%、87.34%以及0.077%的粉末还原铁，该产品可作为电炉炼钢的优质原料。不加添加剂时，部分含磷矿物被还原成单质磷进入到金属铁中，故粉末还原铁磷含量较高，当碳酸钙用量为25%时，含磷矿物的还原受到抑制而保留在脉石相中，可实现降磷目的，而还原时间过长时，磷仍在脉石相中，铁颗粒将部分含磷矿物包裹，磨矿难以分离，导致磷含量升高。     

Effect of ultrasonic vibration on thermal and material flow behavior,microstructure and mechanical properties of friction stir welded Al/Cu joints

Al/Cu dissimilar joint has been widely produced by using friction stir welding (FSW), but the weld quality remains limited. A recently developed ultrasonic     

Personality expression and recognition in Chinese language usage

User Modeling and User-Adapted Interaction - Personality plays a pivotal role at work. Many scholars have investigated the association between personality and language usage habits in the English...     

Unsteady free convection of second‐grade nanofluid with a new time‐space fractional heat conduction

The Caputo and Caputo–Fabrizio derivative are applied to study a second‐grade nanofluid over a vertical plate. A comparative analysis is presented to study the unsteady free convection of a second‐grade nanofluid with a new time–space fractional heat conduction. The governing equations with mixed time–space fractional derivatives are non‐dimensionalized and solved numerically, and a comparison between the Caputo and the Caputo–Fabrizio models is made. It is found that the temperature is higher for the Caputo–Fabrizio fractional model than the Caputo model, but the higher velocity only exists near the vertical plate for the Caputo–Fabrizio model than the Caputo model. Moreover, the velocity for the Caputo model will exceed the Caputo–Fabrizio model as y evolves.     

Transformation of the reabsorption characteristics of lignite treated by low and high temperature drying process

Abstract

The reabsorption characteristics of the lignite treated by low and high temperature drying process were addressed in the paper. The information about the moisture form, functional groups, effective water-filled porosities and equilibrium moisture content of the lignite before and after the drying process was investigated using Differential scanning calorimetry (DSC), Fourier transform infrared (FTIR) spectroscopy, nuclear magnetic resonance (NMR) spectroscopy and a self-made reabsorption device, respectively. The results show that the low drying temperature (140, 190, 230?°C, 10?min, N₂) has little impact on the effective water-filled porosities of the resulted samples, whereas it has a great influence on the main oxygen-containing functional groups, which amount firstly decreases and then increases with the drying temperature increasing. In the case of the lignite samples dried under high-temperature (600, 700, 800?°C, 30?s, N₂), the amount of the effective water-filled porosity of the sample decreases and the amount of oxygen-containing functional groups increases as the temperature increasing. The reabsorption capability of the high temperature dried sample is much lower than that of the sample treated under low drying temperature. The reabsorption characteristics of the low-temperature dried samples are affected by the amount of the oxygen-containing functional groups, while the effective water-filled porosity is main factor for the lignite samples derived from high temperature drying process. Moreover, the work gives a good evidence that the high-temperature drying process is an effective choose for lignite upgrading.     

Image Super-Resolution Based on Generative Adversarial Networks: A Brief Review

Single image super resolution (SISR) is an important research content in the field of computer vision and image processing. With the rapid development of deep neural networks, different image super-resolution models have emerged. Compared to some traditional SISR methods, deep learning-based methods can complete the superresolution tasks through a single image. In addition, compared with the SISR methods using traditional convolutional neural networks, SISR based on generative adversarial networks (GAN) has achieved the most advanced visual performance. In this review, we first explore the challenges faced by SISR and introduce some common datasets and evaluation metrics. Then, we review the improved network structures and loss functions of GAN-based perceptual SISR. Subsequently, the advantages and disadvantages of different networks are analyzed by multiple comparative experiments. Finally, we summarize the paper and look forward to the future development trends of GAN-based perceptual SISR.