Glencore (Norway)

importante, sobretudo na regio sudeste.Constatou-se que a forma urbana da doena crescente e necessrio entender seu carter de emergncia.Alm disso, foram observados fatores de risco para o aparecimento de tantos novos casos da doena, como a alta infestao do mosquito transmissor, o deslocamento de pessoas infectadas da rea rural para o meio urbano, favorecendo tambm novos casos de febre amarela urbana, e pessoas susceptveis ao desenvolvimento da doena.Concluso: Por tanto, notou-

Recycling of valuable metals such as nickel is instrumental to meet the need from the dramatic increase in electric vehicle battery production and to improve its sustainability. Nickel required in the battery manufacture can be recovered from the hydrometallurgical industrial process streams by crystallization of nickel sulfate. Here, crystallization of nickel sulfate is studied from an industrial point of view, investigating the effects of temperature, seeding and presence of magnesium on the formation of various solid phases for the evaluation of their potential influence on the process design. Results showed that the precipitating phase was dictated both by seed amount and reaction temperature. Transformation of metastable phases both in suspension and in a dry state was observed over time. Presence of magnesium was shown to promote formation of NiSO4·7H2O in solution and increased its stability in a dry form. In their dry state, nickel sulfate that was formed in the absence of magnesium transformed towards α-NiSO4·6H2O, whereas those precipitated in the presence of high magnesium concentrations transformed towards β-NiSO4·6H2O, indicating that magnesium inhibited the phase transformation towards α-NiSO4·6H2O. Knowledge about various solid phases of varying crystal morphology and stability can be used as input to decisions for the best suited solid product type and how this relates to the initial conditions of the sidestreams.

Battery production for electric vehicles has increased rapidly in the last decade, and the projections show an ever-increasing demand for the next years. This leads to a need for recycling of valuable metals used in batteries, such as nickel, for a sustainable development. Nickel can be recovered from process streams or side streams in hydrometallurgical industry as nickel sulfate by crystallization, in order to obtain high-purity products for applications like battery-grade nickel sulfate. In this work, NiSO4·6H2O was precipitated by cooling crystallization in a temperature-controlled batch reactor, and uptake of Na, Cl, and Mg, impurities commonly found in hydrometallurgical industries, were investigated. Increasing the initial impurity concentrations in the reactor caused increased impurity content in the precipitates, and the highest uptake was provided by Mg. Characterization of final products with X-ray diffraction (XRD) showed that the precipitating polymorph was altered at high impurity concentration. The results of partial dissolution studies indicated that uptake of Cl was negligible, and Na was weakly adsorbed on the crystal surface, while Mg was also incorporated in the bulk of the crystals, possibly explained by the similar properties of Mg and Ni.

Abstract Cooling crystallization was successfully carried out in a batch cooling crystallizer from impure acidic solutions to recover nickel as nickel sulfate salt with three different cooling rates. The compositions of the solutions included impurities of sodium, magnesium, chloride, and sulfuric acid to mimic industrial nickel electrowinning process solutions. The results show that NiSO4·6H2O mainly crystallized, and its solubility and purity decreased with the increase in the mass ratio of chloride to sulfate. Cooling rates did not have a significant influence on crystal purity; however, it did affect the filter cake moisture; lower moisture can be obtained with a lower cooling rate. The sequence of impurity removal efficiency from high to low was Cl > Na > Mg.

Author Summary: In modern process industry it is necessary to find “smart” ways to continuously satisfy customers’ demands, strive for more efficient production and prioritise the focus on safety, health and environment, allowing dedicated companies to obtain a competitive advantage. To achieve individual goals in these areas, companies increasingly implement a so-called business system approach, which ensures systematic, continuous improvement initiatives in all sectors. Most business systems address improvement in process control, since in many cases there is a significant positive economic potential which often only requires minor capital investments. This is also the case for Glencore Nikkelverk, Norway, where it has been decided to transform a former project-based improvement framework into a holistic business system, the Nikkelverk Business System (NBS). One pillar consists of different tools to improve process performance, with the objective to identify critical processes and process stages a.o. and also to ensure that the measurement systems in use can be geared, and validated, to mainly capture process variations, allowing to document valid process improvements. At Nikkelverk there are between 6000 and 7000 measurement points, of which one-third are used for process regulation purposes. It is therefore critically important to be able to monitor and verify that measurement system uncertainty is suitably low—ideally at a level of 10% relative or below compared to the variation of the process being monitored. This will become a key priority. An optimal measurement system should therefore not contribute significantly to the total apparent process variation as revealed by raw process data that are used to track when a process is deviating from steady state or dangerously close to control limits, or gets outside relevant safety limits. Critical processes must be kept under constant monitoring and control to ensure that all improvement attempts work from a solid database. As but two examples, energy and material consumption, can be fine-tuned to a lowest possible level only when both processes themselves and the measurement systems are monitored and controlled properly. This not only contributes to the cost efficiency of the company, but enforces process monitoring and control to take a leading role. We here focus specifically on the relative merits of variographic analysis (Theory of Sampling) and measurement system analysis (Six Sigma) and show how the former can function as a very effective screening for the much more costly latter.

Lead-based anodes are widely used in copper electrowinning (EW). However, lead can induce contamination of the electrolyte during copper EW due to the corrosion of the anode [1]. Furthermore, corrosion while at high current densities will finally lead to the failure of the anode since the overvoltage for oxygen evolution reaction (OER) on lead is still rather high, and the service life of lead-based anodes is quite limited in industrial copper plants [2]. Besides, lead and lead compounds are toxic, which means the use of lead-based anodes is not environmentally friendly. Dimensionally stable anodes (DSAs) with IrO2-Ta2O5 oxides coated on titanium substrates hold excellent electrocatalytic activity and electrochemical stability, and have the most potential to replace lead-based anode in copper EW industry. In this work, different types of commercially available electrode samples with IrO2-Ta2O5 coating were studied. The studies focused on investigating the impact of surface microstructure on electrocatalytic activity. Surface morphology and chemical composition of DSA samples were analyzed using scanning electron microscopy (SEM, Hitachi S-3400N) combined with energy dispersive spectroscopy (EDS). X-ray diffraction (XRD) studies were carried out using Bruker AXS D8Advance with grazing incident angle at 3°. The crystalline structure and phase composition were analyzed by varying the 2θ angle from 10° to 80°. The electrochemical experiments were carried out in aqueous solution with 0.9 M H2SO4 and 1.2 M CuSO4. A Teflon holder giving a 1 cm2 electrode surface area was used. All experiments were conducted at 60 °C. Cyclic voltammetry (CV) measurements were recorded in a range between 0.55 V and 1.35 V vs. SHE with varying sweep rate from 300 mV/s to 1 mV/s. The scan rate for all polarization measurement was 0.5 mV/s. The ohmic (IR) drop during the testing was corrected for by measuring the electrolyte resistance using electrochemical impedance spectroscopy (EIS) at high frequency. Electrocatalytic activity for anodes as a function of composition and preparation method was determined by steady state polarization analysis. The durability of the anodes was investigated by accelerated lifetime tests, which were carried out in 0.9 M H2SO4 solution at the constant current density of 2 A/cm2. In the present work, commercial DSAs were used instead of samples fabricated in the laboratory. This offers not only valuable results for DSAs research but also a consideration for DSAs manufacturers to improve the quality of the DSA. [1] M. Clancy, C. J. Bettles, A. Stuart, N. Birbilis, Corrosion behaviour and catalytic effectiveness of Pb–Ca–Sn, RuO2 –IrO2 /Ti and IrO2 –Ta2O5/Ti anodes for copper electrowinning, Hydrometallurgy 131-132 (2013) 144. [2] G. N. Martelli, R. Ornelas, G. Faita, Deactivation mechanisms of oxygen evolving anodes at high current densities, Electrochim. Acta 39 (1994) 1551.

This paper discusses the topics related to automating parameter, disturbance and state estimation analysis of large-scale complex nonlinear dynamic systems using free programming tools. For large-scale complex systems, before implementing any state estimator, the system should be analyzed for structural observability and the structural observability analysis can be automated using Modelica and Python. As a result of structural observability analysis, the system may be decomposed into subsystems where some of them may be observable --- with respect to parameter, disturbances, and states --- while some may not. The state estimation process is carried out for those observable subsystems and the optimum number of additional measurements are prescribed for unobservable subsystems to make them observable. In this paper, an industrial case study is considered: the copper production process at Glencore Nikkelverk, Kristiansand, Norway. The copper production process is a large-scale complex system. It is shown how to implement various state estimators, in Python, to estimate parameters and disturbances, in addition to states, based on available measurements.