Recovery of Valuable Metals from Nickel Smelting Slag Based on Reduction and Sulfurization Modification

Nickel smelting slag contains valuable metals including nickel and copper. Failure to recycle these metals wastes resources, and disposal of nickel slag in stockpiles results in environmental pollution. Nickel slag recycling is important, and metals can be recovered from slag by flotation. However, considering the complex forms in which valuable metals occur in nickel slag, high yields are difficult to achieve by direct flotation. In this study, nickel slag was modified by reduction and sulfurization to render it more amenable to metal recovery through flotation. The mechanism was assessed based on thermodynamics and elements’ phase distributions. Thermodynamic analyses indicated the feasibility of nickel slag modification by reduction–sulfurization smelting. The results of chemical phase analysis show that the forms in which valuable metals occur in nickel slag can be modified by reduction–sulfurization, and the proportion of metals existing in sulfide and free metal states in nickel slag can be increased. Compared with the direct flotation of raw slag, the recovery of nickel and copper from top-blowing slag increased by 23.03% and 14.63%, respectively. The recoveries of nickel and copper from settling slag increased by 49.68% and 43.65%, respectively.

An optimal technological scheme for flotation concentration of gold-copper-arsenic ores of the Taror deposit (Republic of Tajikistan)

This article investigates the effect of material size on the efficiency of flotation concentration of gold-copperarsenic ores of the Taror deposit (Republic of Tajikistan) and studies the dependence of gold recovery on the duration of the process with the purpose of developing an alternative technological scheme for processing this ore type. According to X-ray phase analysis, Taror ore samples consist of rock-forming minerals by 92%. Ore mineralization is represented by sulphide minerals, mainly arsenopyrite, chalcopyrite and pyrite, in the total amount of 8%. Ore-forming elements include iron, sulphur, arsenic and copper with the mass fraction of 6.02%, 3.26%, 1.52% and 0.82%, respectively. Gold and silver are contained in the ore in the amount of 7.35 g/t and 20.28 g/t, respectively. The oxidation state of the ore calculated by iron comprises 51.3%. According to this indicator, this ore type can be distinguished as mixed, close to the primary type. According to the conducted chemical phase analysis of gold, this ore type belongs to the category of refractory ores. Flotation concentration experiments showed that grinding the original ore to a size of 95%–71 microns increases the recovery of gold in the concentrate by 10%, compared to grinding to a particle size of 80%–71 microns. The effect of the flotation process duration on gold recovery was also studied. To achieve the maximum gold recovery in the flotation concentrate, the duration of the main flotation and control flotation should be taken equal to 14 and 12 minutes, respectively. As a result of the experiments, a relatively simple technological solution was proposed for flotation concentration of the Taror ore, which includes the main, control and cleaning stages of flotation.

Mechanism of Li2S formation and dissolution in Lithium-Sulphur batteries

Insufficient understanding of the mechanism that reversibly converts sulphur into lithium sulphide (Li2S) via soluble polysulphides (PS) hampers the realization of high performance lithium-sulphur cells. Typically Li2S formation is explained by direct electroreduction of a PS to Li2S; however, this is not consistent with the size of the insulating Li2S deposits. Here, we use in situ small and wide angle X-ray scattering (SAXS/WAXS) to track the growth and dissolution of crystalline and amorphous deposits from atomic to sub-micron scales during charge and discharge. Stochastic modelling based on the SAXS data allows quantification of the chemical phase evolution during discharge and charge. We show that Li2S deposits predominantly via disproportionation of transient, solid Li2S2 to form primary Li2S crystallites and solid Li2S4 particles. We further demonstrate that this process happens in reverse during charge. These findings show that the discharge capacity and rate capability in Li-S battery cathodes are therefore limited by mass transport through the increasingly tortuous network of Li2S / Li2S4 / carbon pores rather than electron transport through a passivating surface film.

Sulfidizing Behavior of Complex Lead-Silver Ore: A Flotation Study

In this study, we investigate a low-grade oxidized lead ore containing noble metal silver, with complex mineralogy. The sulfurization behaviors of different types of lead-silver minerals at different pH values were analyzed using the chemical phase analysis method. The interactions between different types of lead-silver minerals and different types of collectors were investigated. An effective laboratory process was developed, and closed-circuit tests were carried out at industrial sites. We found that the order of difficulty for sulfidizing various lead minerals and silver minerals was (PbFe6(OH)12SO4)4 < PbCO3 < PbSO4 < Pb5(P/As/VO4)3Cl; Ag2AsS2 < AgCl < natural-Ag. Aerophine 3418A had the best selectivity and capture capacity of the silver minerals. In the laboratory, the total recovery of lead and silver was 65.16% and 87.81%, respectively. In industrial closed-circuit testing, flotation alone was used, which produced a total lead recovery yield of 67.71%, and a total silver recovery yield of 87.64%.

Compósito de resíduos de mineração com cimento e cal para materiais de construção sustentáveis

<p> <span class="fontstyle0">Sustainable alternatives have been developed with the use of waste in construction, among which we can highlight mining waste due to its large amount generated and environmental impact caused. This work consists in the joint application of scheelite residue and stone powder with lime and cement addition, producing cylindrical specimens, to evaluate possible uses in constructive materials. After chemical and physical characterization, the percentage of each residue was determined through the analysis of packing between the particles, which resulted in a formulation of 50% of each residue with the addition of cement and / or lime in the contents of 6% and 12%. Essays for simple compressive strength (SCS), water absorption (WA) and chemical phase analysis by scanning electron microscopy (SEM) and X-ray diffraction (XRD) were evaluated at determined cure times. The SCS essays results of formulations with residues and cement reached values above 1 MPa and WA essays results with value below 20%, according to the Brazilian technical standards. Cement phases were observed in SEM and XRD analysis. The results obtained from mixing the waste with the cement are promising for the manufacture of cement building materials.</span> <br /><br /></p>

Giving Attention to Generative VAE Models for De Novo Molecular Design

<div> <div> <div> <p>We explore the impact of adding attention to generative VAE models for molecular design. Four model types are compared: a simple recurrent VAE (RNN), a recurrent VAE with an added attention layer (RNNAttn), a transformer VAE (TransVAE) and the previous state-of-the-art (MosesVAE). The models are assessed based on their effect on the organization of the latent space (i.e. latent memory) and their ability to generate samples that are valid and novel. Additionally, the Shannon information entropy is used to measure the complexity of the latent memory in an information bottleneck theoretical framework and we define a novel metric to assess the extent to which models explore chemical phase space. All three models are trained on millions of molecules from either the ZINC or PubChem datasets. We find that both RNNAttn and TransVAE models perform substantially better when tasked with accurately reconstructing input SMILES strings than the MosesVAE or RNN models, particularly for larger molecules up to ~700 Da. The TransVAE learns a complex “molecular grammar” that includes detailed molecular substructures and high-level structural and atomic relationships. The RNNAttn models learn the most efficient compression of the input data while still maintaining good performance. The complexity of the compressed representation learned by each model type increases in the order of MosesVAE < RNNAttn < RNN < TransVAE. We find that there is an unavoidable tradeoff between model exploration and validity that is a function of the complexity of the latent memory. However, novel sampling schemes may be used that optimize this tradeoff and allow us to utilize the information-dense representations learned by the transformer in spite of their complexity. </p> </div> </div> </div>

Giving Attention to Generative VAE Models for De Novo Molecular Design

<div> <div> <div> <p>We explore the impact of adding attention to generative VAE models for molecular design. Four model types are compared: a simple recurrent VAE (RNN), a recurrent VAE with an added attention layer (RNNAttn), a transformer VAE (TransVAE) and the previous state-of-the-art (MosesVAE). The models are assessed based on their effect on the organization of the latent space (i.e. latent memory) and their ability to generate samples that are valid and novel. Additionally, the Shannon information entropy is used to measure the complexity of the latent memory in an information bottleneck theoretical framework and we define a novel metric to assess the extent to which models explore chemical phase space. All three models are trained on millions of molecules from either the ZINC or PubChem datasets. We find that both RNNAttn and TransVAE models perform substantially better when tasked with accurately reconstructing input SMILES strings than the MosesVAE or RNN models, particularly for larger molecules up to ~700 Da. The TransVAE learns a complex “molecular grammar” that includes detailed molecular substructures and high-level structural and atomic relationships. The RNNAttn models learn the most efficient compression of the input data while still maintaining good performance. The complexity of the compressed representation learned by each model type increases in the order of MosesVAE < RNNAttn < RNN < TransVAE. We find that there is an unavoidable tradeoff between model exploration and validity that is a function of the complexity of the latent memory. However, novel sampling schemes may be used that optimize this tradeoff and allow us to utilize the information-dense representations learned by the transformer in spite of their complexity. </p> </div> </div> </div>

Memory seeds enable high structural phase purity in 2D perovskite films for high-efficiency devices

Two-dimensional (2D) perovskites are a class of halide perovskites offering a pathway for realizing efficient and durable optoelectronic devices. However, the broad chemical phase space and lack of understanding of film formation have led to quasi-2D perovskite films with polydispersity in perovskite layer thicknesses, which have hindered devices performance and stability. Here, we demonstrate a scalable approach involving dissolution of single-phase crystalline powders with homogeneous perovskite layer thickness in desired solvents, to fabricate 2D perovskite thin-films with high phase purity. In-situ characterizations reveal the presence of sub-micron-sized seeds in solution that preserve the memory of the dissolved single-crystals and dictate the nucleation and growth of grains with identical thickness of the perovskite layers in thin-films. Photovoltaic devices fabricated with such films, yields an efficiency of 17.1% and 1.20V open-circuit voltage, while preserving 97.5% of their peak-performance after 800 hours under illumination without any external thermal management.