A critical review on solvent extraction of rare earths from aqueous solutions

Rare earth elements have unique physicochemical properties that make them essential elements in many high-tech components. Bastnesite (La, Ce)FCO₃, monazite, (Ce, La, Y, Th)PO₄, and xenotime, YPO₄, are the main commercial sources of rare earths. Rare earth minerals are usually beneficiated by flotation or gravity or magnetic processes to produce concentrates that are subsequently leached with aqueous inorganic acids, such as HCl, H₂SO₄, or HNO₃. After filtration or counter current decantation (CCD), solvent extraction is usually used to separate individual rare earths or produce mixed rare earth solutions or compounds. Rare earth producers follow similar principles and schemes when selecting specific solvent extraction routes. The use of cation exchangers, solvation extractants, and anion exchangers, for separating rare earths has been extensively studied. The choice of extractants and aqueous solutions is influenced by both cost considerations and requirements of technical performance. Commercially, D2EHPA, HEHEHP, Versatic 10, TBP, and Aliquat 336 have been widely used in rare earth solvent extraction processes. Up to hundreds of stages of mixers and settlers may be assembled together to achieve the necessary separations. This paper reviews the chemistry of different solvent extractants and typical configurations for rare earth separations.     

一种用于钴、镍分离的全界面接触高效萃取设备

介绍了一种全界面高效萃取分离钴、镍的新设备。利用自主研发的多相流涡轮增压反应器切割混合水相和有机相,使两相物料以微米级形态接触,增大了萃取反应相内接触表面积和反应动力学,克服了机械混合的缺点,使两相分离速度加快,而且不产生第三相,萃取反应级数从传统的9级降为3级,设备投入减少。优化后的镍、钴萃取分离工艺试验结果表明:在萃取剂与硫酸镍溶液体积比为1∶3、萃取剂皂化率50%~55%、反应温度45℃、3级逆流萃取条件下,钴萃取率达99.9%,萃余液中钴离子质量浓度达到要求(1mg/L)。     

Extraction and analysis of multiple time window features associated with muscle fatigue conditions using sEMG signals

In this work, an attempt has been made to differentiate surface electromyography (sEMG) signals under muscle fatigue and non-fatigue conditions with multiple time window (MTW) features. sEMG signals are recorded from biceps brachii muscles of 50 volunteers. Eleven MTW features are extracted from the acquired signals using four window functions, namely rectangular windows, Hamming windows, trapezoidal windows, and Slepian windows. Prominent features are selected using genetic algorithm and information gain based ranking. Four different classification algorithms, namely naïve Bayes, support vector machines, k-nearest neighbour, and linear discriminant analysis, are used for the study. Classifier performances with the MTW features are compared with the currently used time- and frequency-domain features. The results show a reduction in mean and median frequencies of the signals under fatigue. Mean and variance of the features differ by an order of magnitude between the two cases considered. The number of features is reduced by 45% with the genetic algorithm and 36% with information gain based ranking. The k-nearest neighbour algorithm is found to be the most accurate in classifying the features, with a maximum accuracy of 93% with the features selected using information gain ranking.     

陶瓷废料粗骨料混凝土的研究

选取陶瓷废料取代传统的碎石粗骨料进行了混凝土实验,对掺杂了陶瓷废料粗骨料的混凝土的抗压强度、抗拉强度、弯曲强度及弹性模量做了系统研究,并与碎石粗骨料传统混凝土进行了比较,试验结果表明,陶瓷废料粗骨料混凝土的和易性是良好的,并且强度特性与常规混凝土相近。     

谈当代建筑是否能够进入遗产保护行列

以西安钟楼饭店为例,通过对该建筑特征价值、与类似文物建筑的比较,并参考英国遗产评定标准进行评价,得出改革开放30年建设的当代典型建筑是可以进入遗产保护行列的。     

化学分离法分析大型纸浆发电厂废渣中生物质底灰和飞灰成分(英文)

采用三步分离法,其中第一步用水,第二步用乙酸铵,第三步用盐酸,提取纸浆发电厂生物质飞灰和底灰的组分,以评估这些残渣的浸出行为。除了Mo、S、Na以及那些浓度低于检测范围的元素外,在这两种灰份中,对于其他元素这三种浸出剂的浸出能力从弱到强的顺序为:水、乙酸铵和盐酸。采用三步分离法处理的废渣中元素浓度比前期用BCR连续提取法得到的低。     

Feature extraction and classification for detecting the thermal faults in electrical installations

This paper proposed an effort to investigate the suitability of input features and classifier for identifying thermal faults within electrical installations. The features are extracted from the thermal images of electrical equipment and classified using a multilayered perceptron (MLP) artificial neural network and support vector machine (SVM). In the experiments, the classification performances from various input features are evaluated. The commonly used classification performance indices, including sensitivity, specificity, accuracy, area under curve (AUC), receiver operating characteristic (ROC) and F-score are employed to identify the most suitable input feature as well as the best configuration of classifiers. The experimental results demonstrate that the combination of features set T_max, T_delta and DT_bg produce the best input feature for thermal fault detection. In addition, the implementation of SVM using radial basis kernel function (RBF) produces slightly better performance than the MLP artificial neural network.     

Simultaneous Microwave Extraction and Separation of Volatile and Non-Volatile Organic Compounds of Boldo Leaves. From Lab to Industrial Scale

Microwave extraction and separation has been used to increase the concentration of the extract compared to the conventional method with the same solid/liquid ratio, reducing extraction time and separate at the same time Volatile Organic Compounds (VOC) from non-Volatile Organic Compounds (NVOC) of boldo leaves. As preliminary study, a response surface method has been used to optimize the extraction of soluble material and the separation of VOC from the plant in laboratory scale. The results from the statistical analysis revealed that the optimized conditions were: microwave power 200 W, extraction time 56 min and solid liquid ratio of 7.5% of plants in water. Lab scale optimized microwave method is compared to conventional distillation, and requires a power/mass ratio of 0.4 W/g of water engaged. This power/mass ratio is kept in order to upscale from lab to pilot plant.     

The kinetic and thermodynamic analysis of ultrasound-extraction of minerals from aerial parts of white lady's bedstraw (Galium mollugo L.)

The present paper deals with the extraction of some minerals (potassium, calcium and magnesium) from ground, dried aerial parts of white lady's bedstraw (Galium mollugo L.) using an aqueous ethanol solution (50% by volume) at different temperatures (from 23 to 40 °C) in the presence and absence of ultrasound. The main goal was to establish the kinetics and the thermodynamics of the two extraction processes. A phenomenological model involving simultaneous washing and diffusion was proved for both ultrasound-assisted and silent extraction of the minerals. The minerals extraction both in the presence and the absence of ultrasound is endothermic and irreversible since the enthalpy change and the entropy change are positive in the ranges of extraction temperature applied. The Gibbs free energy change for the extraction of minerals is negative, indicating that the process is feasible and spontaneous. The minerals yield increased by a factor of 1.02–1.06 and 1.14–1.27 in the absence and the presence of ultrasound, respectively for every 10 °C rise in temperature.     

Mass Transfer in Molybdenum Extraction from Aqueous Solutions Using Nanoporous Membranes

Modeling of non‐disperse solvent extraction of molybdenum(VI) with PC‐88A as extractant and a nanoporous hollow‐fiber membrane contactor as extractor was performed. Computational fluid dynamics was applied for modeling and simulation of molybdenum extraction. Concentration, pressure, and velocity distributions for molybdenum were determined. The extraction of Mo⁶⁺ was greatly influenced by the flow rate of feed solution. The extraction efficiency was reduced with higher feed flow rate and increased with the molybdenum content in the feed. The pressure drop along the shell side of the membrane extractor was found to be not significant, being one of the advantages of membrane extractors which assist in reducing the operational costs. The proposed simulation method is capable to prognosticate the performance of solvent extraction of molybdenum in membrane extractors.