Activities and Ionic Distributions in Cobalt Silicate Melts

Smith, I. B.; Masson, C. R.

doi:10.1139/v71-115

Cited by 18 publications

(8 citation statements)

References 8 publications

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“…Since the melts contain primarily polymers, f P 1, the value of the average polymer chain length, m, can be obtained from the known quantities a MO and , and is expressed in Eq. [19]: [20] , [19] The relationship between m and m for the polymer mixture [19] is given as [20] where m is a very small constant for the weak interactions between the arsenic anions and silicates and is dependent on the average polymer chain length, m.…”

Section: B Arsenate Capacity For Acidic Meltsmentioning

confidence: 99%

Arsenate capacities of copper smelting slags

Reddy

Font

2003

Metall Mater Trans B

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The arsenate capacity model, based on the Reddy-Blander model, was developed for copper smelting slags. The arsenate capacities of FeO-SiO 2 , CaO-SiO 2 , MgO-SiO 2 , FeO-FeO 1.5 -CuO 0.5 -MgO-SiO 2 , and FeO-FeO 1.5 -CuO 0.5 -CaO-MgO-SiO 2 slags in equilibrium with different grades of copper mattes (21 to 79 wt pct Cu) at 1573 K were studied. The calculated arsenate capacities using the RB model in copper slags a priori is in very good agreement with the available experimental data. The results show that the calculated arsenate capacities for these slags are found to be directly related to two independent experimental quantities: the equilibrium constant K of the arsenate forming reaction 3 / 2 MO (1) ϩ As (1) ϩ 5/4O 2 (g) ϭ M 3/2 AsO 4 (l, s), and the activity of the base metal oxides in the binary MO-SiO 2 slags. Furthermore, this arsenate capacity model can be used for a priori prediction of arsenic behavior in a wide range of slag and matte composition, temperature, and p SO2 in copper smelting conditions. Such predictions are very useful in understanding the behavior of arsenic in the current and eventually future nonferrous metal processes.

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Section: B Arsenate Capacity For Acidic Meltsmentioning

confidence: 99%

Arsenate capacities of copper smelting slags

Reddy

Font

2003

Metall Mater Trans B

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“…Activities of CoO in CoO -SiO 2 melts were studied by Smith and Masson [30] by equilibration with 80 %Pt -20 %Rh alloy under controlled oxygen partial pressures at 1450 and 1550 8C, followed by analysis of the CoO and Co contents of the quenched oxide melts and alloys by a conventional gravimetric method and by chemical analysis respectively. From the known activity coefficient of Co in the Pt -Rh alloy, Smith and Masson then calculated the activities of CoO in equilibrated CoO -SiO 2 melts.…”

Section: Coo -Sio 2 Systemmentioning

confidence: 99%

“…Calculated (optimized) activity of CoO (solid standard state) in CoO -SiO 2 melts at 1450 8C and 1500 8C and experimental data[30]. liquid) and (spinel + olivine + cobaltowustite + liquid).…”

mentioning

confidence: 99%

Thermodynamic modeling of the CoO–SiO₂and CoO–FeO–Fe₂O₃–SiO₂systems

Jung

Decterov

Pelton

2007

International Journal of Materials Research

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A complete critical evaluation and thermodynamic modeling of the phase diagrams and thermodynamic properties of oxide phases in the CoO -FeO -Fe 2 O 3 -SiO 2 system at 1 bar total pressure are presented. Optimized equations for the thermodynamic properties of all phases were obtained which reproduce all available thermodynamic and phase equilibrium data within the limits of absolute experimental accuracy from 25 8C to above the liquidus temperatures at all compositions and oxygen partial pressures. The database of the model parameters can be used, along with software for Gibbs energy minimization, to calculate any type of phase diagram section. Unexplored phase diagram sections and activities of CoO, FeO and SiO 2 in this system of industrial importance are predicted from the thermodynamic models with the optimized parameters.

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“…Using polymer-solution theory, we obtain an equation for C S as [6] where f S is the volume fraction of S 2Ϫ monomer sites. For silicate polymeric melts, [20] the value of m can be obtained from the known quantities of a MO and , as shown in Eq [8]: [8] and m P is expressed as [14] [9] Because the melts contain, primarily, polymers at Ͼ 0.5, f P is taken to be equal to 1.…”

Section: A Theoretical Consideration Of R-b Modelmentioning

confidence: 99%

Emerging technologies in extraction and processing of metals

Reddy¹

2003

Metall Mater Trans B

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The growing need to conserve energy and materials and prevent environmental pollution led to an increased demand for better understanding of potential as well as existing processes. In this context, thermodynamic and transport modeling of materials and processes provides a rapid and cost-effective means of conducting and minimizing the complexity of experimental investigations and developing innovative and environmentally friendly metallurgical processes. This presentation concentrates on some fundamentals on new technologies as extractive metallurgy of copper, lead, aluminum, and other nonferrous metals and processing of nanocomposites.The newer routes of copper smelting and modeling of impurities in copper and lead slags and mattes are reviewed. The copper smelting capacity increased by a factor of 10 during the last three decades, the smelting rate increased by a factor of 6, and the process fuel equivalent decreased by a factor of 2. The a priori prediction, with no adjustable parameters, of impurity capacities of S and As in copper slags and S in lead slags, based on the Reddy-Blander model, is reviewed. Excellent agreement between the model-predicted capacities data and laboratory experimental and industrial data was observed. The model is an invaluable tool for optimization of process parameters in the efficient removal of impurities from the nonferrous-metals smelting and refining processes.A new in-situ processing technology for the production of a lightweight alloy matrix with ceramic particle reinforcements such as SiC in aluminum alloy matrix composites by bubbling reactive gas is reviewed. Thermal plasma processing of a nanoscale aluminum alloy matrix with TiC and TiN composites is discussed. The in-situ formed reinforcements are thermodynamically stable, and the composite particles are of uniform size. The optimum process parameters for the production of composite powders by thermal plasma are discussed.A low-temperature aluminum production and refining process using ionic liquids as electrolytes is reviewed. This newly developed aluminum production process has many advantages over the current industrial process, and the energy consumption is closer to the thermodynamic limit of aluminum production. RAMANA G. REDDYThe Extraction and Processing Lecturer Award honors an outstanding scientific leader in the field of nonferrous extractive metallurgy with an invitation to present a Professor Reddy has 20 years of teaching and research experience in the field of chemical and materials engineering. He obtained his Ph.D. degree from the University of Utah. He has conducted projects involving thermodynamics and kinetics of metallurgical reactions; pyrometallurgy, hydrometallurgy, plasma processing of metals, molten salt electrolysis, and waste processing.He has published over 174 research articles in national and international journals and 7 books, including one undergraduate student textbook in thermodynamics. He has presented numerous invited lectures and research presentations in the United States and abr...

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Activities and Ionic Distributions in Cobalt Silicate Melts

Cited by 18 publications

References 8 publications

Arsenate capacities of copper smelting slags

Arsenate capacities of copper smelting slags

Thermodynamic modeling of the CoO–SiO₂and CoO–FeO–Fe₂O₃–SiO₂systems

Emerging technologies in extraction and processing of metals

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Activities and Ionic Distributions in Cobalt Silicate Melts

Cited by 18 publications

References 8 publications

Arsenate capacities of copper smelting slags

Arsenate capacities of copper smelting slags

Thermodynamic modeling of the CoO–SiO2and CoO–FeO–Fe2O3–SiO2systems

Emerging technologies in extraction and processing of metals

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Thermodynamic modeling of the CoO–SiO₂and CoO–FeO–Fe₂O₃–SiO₂systems