Inorganic Polymeric Materials Based on Natural Silicate and Aluminosilicate Raw Materials

The prospects of implementing the mechanochemical activation method of volcanic silicate and aluminosilicate rocks - perlites, tuffs, pumice, etc. are being considered for the production of a wide range of building materials using energy-conserving technologies. The thermodynamic and kinetic parameters of interaction in the systems of aluminosilicate – NaOH have been presented, indicating low-temperature sintering of volcanic rocks with sodium hydroxide. According to the degree of activity, the rocks have the following order: perlites, tuffs, obsidian, microcline. Kinetic parameters are presented: concentration, temperature, conversion degree, reaction rate constant, time of complete reaction and product layer thickness.

Selective Scandium (Sc) Extraction from Bauxite Residue (Red Mud) Obtained by Alkali Fusion-Leaching Method

Bauxite residue, known as “red mud,” is a potential raw material for extracting rare-earth elements (REEs). The main REEs (Sc, Y, La, Ce, Nd, Nb, and Sm) from the raw bauxite are concentrated in RM after the Bayer leaching process. The earlier worldwide studies were focused on the scandium (Sc) extraction from RM by concentrated acids to enhance the extraction degree. This leads to the dissolution of major oxides (Fe2O3 and Al2O3) from RM. This article studies the possibility of selective Sc extraction from alkali fusion red mud (RMF) by diluted nitric acid (HNO3) leaching at pH ≥ 2 to prevent co-dissolution of Fe2O3. RMF samples were analyzed by X-ray fluorescence spectrometry (XRF), X-ray diffraction (XRD), electron probe microanalysis (EPMA), and inductively coupled plasma mass spectrometry (ICP-MS). It was revealed that Sc concentration in RMF can reach up to 140–150 mg kg−1. Sc extraction was 71.2% at RMF leaching by HNO3 at pH 2 and 80 °C during 90 min. The leaching solution contained 8 mg L−1 Sc and a high amount of other REEs in the presence of relatively low concentrations of impurity elements such as Fe, Al, Ti, Ca, etc. The kinetic analysis of experimental data by the shrinking core model showed that Sc leaching process is limited by the interfacial diffusion and the diffusion through the product layer. The apparent activation energy (Ea) was 19.5 kJ/mol. The linear dependence of Sc extraction on magnesium (Mg) extraction was revealed. According to EPMA of RMF, Sc is associated with iron minerals rather than Mg. This allows us to conclude that Mg acts as a leaching agent for the extraction of Sc presented in the RMF in an ion-exchangeable phase.

Spin Freezing and Its Impact on Pore Size, Tortuosity and Solid State

Spin freeze-drying, as a part of a continuous freeze-drying technology, is associated with a much higher drying rate and a higher level of process control in comparison with batch freeze-drying. However, the impact of the spin freezing rate on the dried product layer characteristics is not well understood at present. This research focuses on the relation between spin-freezing and pore size, pore shape, dried product mass transfer resistance and solid state of the dried product layer. This was thoroughly investigated via high-resolution X-ray micro-computed tomography (µCT), scanning electron microscopy (SEM), thermal imaging and solid state X-ray diffraction (XRD). It was concluded that slow spin-freezing rates resulted in the formation of highly tortuous structures with a high dried-product mass-transfer resistance, while fast spin-freezing rates resulted in lamellar structures with a low tortuosity and low dried-product mass-transfer resistance.

Hydrothermal Treatment of Arsenopyrite Particles with CuSO4 Solution

The nature of the hydrothermal reaction between arsenopyrite particles (FeAsS) and copper sulfate solution (CuSO4) was investigated in this study. The effects of temperature (443–523 K), CuSO4 (0.08–0.96 mol/L) and H2SO4 (0.05–0.6 mol/L) concentrations, reaction time (1–120 min), stirring speed (40–100 rpm) and particle size (10–100 μm) on the FeAsS conversion were studied. The FeAsS conversion was significant at >503 K, and it is suggested that the reaction is characterized by the formation of a thin layer of metallic copper (Cu0) and elemental sulfur (S0) around the unreacted FeAsS core. The shrinking core model (SCM) was applied for describing the process kinetics, and the rate of the overall reaction was found to be controlled by product layer diffusion, while the overall process was divided into two stages: (Stage 1: mixed chemical reaction/product layer diffusion-controlled) interaction of FeAsS with CuSO4 on the mineral’s surface with the formation of Cu1+ and Fe2+ sulfates, arsenous acid, S0, and subsequent diffusion of the reagent (Cu2+) and products (As3+ and Fe2+) through the gradually forming layer of Cu0 and molten S0; (Stage 2: product layer diffusion-controlled) the subsequent interaction of CuSO4 with FeAsS resulted in the formation of a denser and less porous Cu0 and S0 layer, which complicates the countercurrent diffusion of Cu2+, Cu1+, and Fe2+ across the layer to the unreacted FeAsS core. The reaction orders with respect to CuSO4 and H2SO4 were calculated as 0.41 and −0.45 for Stage 1 and 0.35 and −0.5 for Stage 2. The apparent activation energies of 91.67 and 56.69 kJ/mol were obtained for Stages 1 and 2, respectively.

Laser Additively Manufactured Iron-Based Biocomposite: Microstructure, Degradation, and In Vitro Cell Behavior

A too slow degradation of iron (Fe) limits its orthopedic application. In this study, calcium chloride (CaCl2) was incorporated into a Fe-based biocomposite fabricated by laser additive manufacturing, with an aim to accelerate the degradation. It was found that CaCl2 with strong water absorptivity improved the hydrophilicity of the Fe matrix and thereby promoted the invasion of corrosive solution. On the other hand, CaCl2 could rapidly dissolve once contacting the solution and release massive chloride ion. Interestingly, the local high concentration of chloride ion effectively destroyed the corrosion product layer due to its strong erosion ability. As a result, the corrosion product layer covered on the Fe/CaCl2 matrix exhibited an extremely porous structure, thus exhibiting a significantly reduced corrosion resistance. Besides, in vivo cell testing proved that the Fe/CaCl2 biocomposite also showed favorable cytocompatibility.

Corrosion behavior of HRB400 and HRB400M steel bars in concrete under DC interference

The influence of direct current interference on the corrosion behavior of HRB400 and HRB400M steel bars in simulated concrete solution was studied using methods such as weight loss experiment, electrochemical experiment, surface technology and product analysis. The research results showed that with the increase of DC interference voltage, the corrosion rates of HRB400 and HRB400M steel bars would increase. The corrosion resistance of HRB400M steel bars was better than HRB400 steel bars under the experimental conditions. In addition, direct current interference could cause damage to the corrosion product layer on the surface of HRB400 steel bars and HRB400M steel bars. And the corrosion form and corrosion product types of HRB400 and HRB400M steel bars would be affected by direct current interference. The main corrosion products of HRB400 steel bars included γ-FeOOH and Fe2O3 when it was not interfered by DC. When DC interference was applied, the main corrosion products included Fe3O4 and Fe2O3. The corrosion products on the surface of HRB400M steel bars were mainly Fe3O4 and Fe2O3, and the types of products increased to form Cr2O3 and MnFe2O4.

Selective Scandium (Sc) Extraction from Bauxite Residue (Red Mud) Obtained by Alkali Fusion-Leaching Method

One of the potential sources of rare-earth elements (REEs) is the solid waste from alumina industry - bauxite residue, known as “red mud” (RM). The main REEs from the raw bauxite are concentrated in RM after the Bayer leaching process. The earlier worldwide studies were focused on the scandium (Sc) extraction from RM by concentrated acids to enhance the extraction degree. This leads to the dissolution of major oxides (Fe2O3 and Al2O3) from RM. This article studies the possibility of selective Sc extraction from alkali fusion red mud (RMF) by diluted nitric acid (HNO3) leaching at pH ≥ 2 to prevent co-dissolution of Fe2O3. RMF samples have been analyzed by X-ray fluorescence spectrometry (XRF), X-ray diffraction (XRD), electron probe microanalysis (EPMA), and inductively coupled plasma mass spectrometry (ICP-MS). Sc extraction has been found to be 71.2 % at RMF leaching by HNO3 at pH=2 and at 80 °C during 90 min. The kinetic analysis of experimental data by the shrinking core model has shown that Sc leaching process is limited by the interfacial diffusion and the diffusion through the product layer. The apparent activation energy (Ea) was 19.5 kJ/mol. We have established that according to EPMA of RMF, Sc is associated with iron minerals; it could act as the product layer. The linear dependence of Sc extraction of magnesium (Mg) extraction has been revealed. This fact indicates that Mg can act as a leaching agent of Sc presented in RMF by ion-exchangeable phase.

A Novel Integrated Network with LightGBM for Click-Through Rate Prediction

Click-through Rate (CTR) prediction has become one of the core tasks of the recommendation system and its online advertising with the development of e-commerce. In the CTR prediction field, different features extraction schemes are used to mine the user click behavior to achieve the maximum CTR, which helps the advertisers maximize their profits. At present, achievements have been made in CTR prediction based on Deep Neural Network (DNN), but insufficiently, DNN can only learn high-order features combination. In this paper, Product & Cross supported Stacking Network with LightGBM (PCSNL) is proposed for CTR prediction to solve such problems. Firstly, the L 1 and L 2 regularizations are imposed on Light Gradient Boosting Machine (LightGBM) to prevent overfitting. Secondly, the method of vector-wise feature interactions is added to product layer in product network to learn second-order feature combinations. Lastly, feature information is fully learned through the cross network, product network and stacking network in PCSNL. The online ads CTR prediction datasets released by Huawei and Avazu on the Kaggle platform are involved for experiments. It is shown that the PCSN model and PCSNL have better performance than the traditional CTR prediction models and deep learning models.

Properties and Kinetics of Selective Zinc Leaching with Choline Chloride and Urea

A choline chloride-urea (ChCl-urea) deep eutectic solvent (DES) was used to experimentally investigate the secondary recovery of zinc from zinc-bearing dust sludge via a leaching process. The effects of varying the liquid–solid ratio, leaching temperature, stirring speed, and leaching time on the zinc leaching efficiency were determined, and the optimum values of these parameters were found to be 15:1, 90 °C, 400 rpm, and 600 min, respectively, at which a leaching efficiency of 86.87% was achieved. XRF and EDS analyses confirmed that the zinc content in the sludge decreased noticeably after leaching, while those of other elements did not, indicating the selective and efficient leaching of zinc. A study of the leaching kinetics showed that the reaction conforms to the nuclear shrinkage model without solid product layer formation, and the calculated apparent activation energy is 22.16 kJ/mol.