Computational Thermodynamics Software Research Articles

Thermodynamic Modeling of Solid Flux Interactions with Molten Aluminum

Oxide and dross formation during aluminum melt processing results in a considerable amount of loss of metallic aluminum. The total melt loss generated during melt processing can be greatly reduced by efficient use of flux, particularly for melting aluminum scrap or secondary alloys. Effective use of cover fluxes can significantly reduce dross generation by creating a barrier between the metallic aluminum and the atmosphere. The amount of metallic aluminum trapped within the dross layer can also be reduced by up to 50% using drossing fluxes. However, reducing the industrial average melt loss has remained difficult. To evaluate flux ingredients used in the casting industry, computational thermodynamic software ThermoCalc was used to calculate the driving force for reactions between twenty-one flux ingredients and eighteen common alloying and impurity elements in foundry alloys. The thermodynamic calculations, combined with other properties, were used to provide a desirable list of cover and drossing ingredients, which are being experimentally validated.

Development of a computational thermodynamics EERZ model for the improvement of hot rolled light steel profiles steel refining

Light steel profiles are steels with medium C, Mn and Si contents. In these steels internal cleanness is important for mechanical properties and surface quality, both during hot rolling and during the coating of the final product. Production costs of these steels are defined by the total heat time, from charging the Electric Arc Furnace (EAF) to starting continuous casting. Ladle furnace (LF) processing has a large influence on heat time and costs related to deoxidation, meeting composition requirements with a high yield of oxidizing alloying additions and proper rinsing to promote homogenization and cleanness. Thermodynamics and kinetics control how slag and steel oxidation levels evolve, as well as the evolution of the non-metallic inclusion population since at this stage primary oxides are the main inclusions. A model based on solid thermodynamic and kinetics fundamentals would be extremely useful for the producer of these steels, so that the evolution of the heat in the ladle furnace could be properly understood and, afterward, improve. In this work, we present the development of an “Effective Equilibrium Reaction Zone” (EERZ) for the LF processing of these steels, using a well-established thermodynamic database for metal and slags and a module of commercial computational thermodynamic software. We aim at demonstrating that these easily accessible and useable tools can be very effective to help in industrial process development. Thus, based on three selected industrial heats we adjust the kinetic parameters to describe the processes occurring for tapping from the EAF to releasing the heat for continuous casting. Volumetric mass transfer coefficients, heat transfer coefficients and other less critical variables are adjusted based on these heats and the model is then tested in seven further heats of the same steel grade. Results indicate that it is possible to achieve a good fit of the model to the industrial process and this helps identifying critical process variables to optimize the process schedule of these steels. Furthermore, we identify possible current limitations of the modeling strategy as suggested in the preliminary steps for the development of a EERZ model that may be coupled for on-line use, the support LF operators.

“2 1/2[formula omitted]” generation Calphad databases: Extrapolating heat capacities of elements and compounds to 0K

The extrapolation of thermodynamic properties below the room temperature is still, in practical terms, an unsolved issue. The majority of the already established Calphad databases are based on the 2nd generation Calphad models, which are available only at (T>298.15K), there exist a few assessments relying on 3rd generation Calphad models that include more physical descriptions of heat capacity and extend the range of applicability down to 0K. To combine these slowly developing assessments with huge number of existing assessments, a compatible solution that can bridge the gap between 0K and 298.15K in an efficient and fully automated process is needed.Here, an automated modelling approach is proposed, that can be used to produce a reliable thermodynamic descriptions for a wide range of pure elements and compounds. The heat capacity and entropy values at room temperature are the only inputs required. Two fitting parameters are derived, which are, depending on the values of CP and S at 298.15K, either the Debye temperature and its low-temperature dependence or the Debye temperature and a CP contribution changing linearly with temperature. The results are produced as a simple polynomial expression that can be universally utilized in different computational thermodynamic software. Moreover, they are more accurate when compared with experimental or ab-initio results than solutions that rely on pure Einstein or pure Debye models. The applicability is shown on a huge dataset of solid compounds from the material classes of elements, metallic compounds, oxides, semiconductors and salts, thus covering all material classes relevant in Calphad assessments.

Estimation of Iron Ore Pellet Softening in a Blast Furnace with Computational Thermodynamics

In blast furnaces it is desirable for the burden to hold a lumpy packed structure at as high a temperature as possible. The computational thermodynamic software FactSage (version 7.2, Thermfact/CRCT, Montreal, Canada and GTT-Technologies, Aachen, Germany) was used here to study the softening behavior of blast furnace pellets. The effects of the main slag-forming components (SiO2, MgO, CaO and Al2O3) on liquid formation were estimated by altering the chemical composition of a commercial acid pellet. The phase equilibria for five-component FeO-SiO2-CaO-MgO-Al2O3 systems with constant contents for three slag-forming components were computed case by case and the results were used to estimate the formation of liquid phases. The main findings of this work suggested several practical means for the postponement of liquid formation at higher temperatures: (1) reducing the SiO2 content; (2) increasing the MgO content; (3) reducing the Al2O3 content; and (4) choosing suitable CaO contents for the pellets. Additionally, the olivine phase (mainly the fayalitic type) and its dissolution into the slag determined the amount of the first-formed slag, which formed quickly after the onset of softening. This had an important effect on the acid pellets, in which the amount of the first-formed slag varied between 10 and 40 wt.%, depending on the pellets’ SiO2 content.

Slurry Erosion Behavior of Cast 25 Cr Austenitic-Ferritic Steel with Niobium Addition for Subsea Pipelines

Austenitic-ferritic steel, as suggested by its name, has an equal fraction of austenite and ferrite phases, also known as duplex stainless steels (DSS), are one of the highly used materials for subsea pipelines applications. The presence of slurries is inevitable in subsea pipelines. This technical work elucidates the slurry erosive wear behavior of duplex stainless steel and the impact of the addition of niobium (Nb) on the phenomena. Vacuum induction melting was used to produce duplex stainless steel, and its Nb added casts. The aim of the work is to compare both castings' for erosive wear behavior using a slurry jet erosion tester. Computational thermodynamic software Thermo-calc was used to investigate the presence of numerous phases in the system. X-ray diffraction (XRD) has confirmed the formation of niobium carbide in the steel, indicated by Thermo-calc. The effect of slurry velocity (30, 40, and 50 m/s) and impingement angle of slurry (30°, 45°, and 90°) on wear characteristics of these castings were analyzed using volume loss measurements, optical profilometry, and scanning electron microscopy (SEM). The erosion rate of both the materials increased with increasing velocity, whereas erosion was more at shallow angles of impact and increased significantly at the slurry jet's normal incidence. Refinement of austenitic grains in the ferritic pool hints at an increase in heterogeneous nucleation in Nb-doped samples; at the same time, the samples have shown increased hardness and superior erosion resistance against the slurry jet impact.

Use of computational thermodynamics software to determine the influence of CaO, FeO and SiO2 on hot metal dephosphorization efficiency

The properties of the mixtures used in hot metal dephosphorization, such as solid and liquid fraction phases, CaO and FeO activity and viscosity, are determinant for the process efficiency. The influence of these properties on hot metal dephosphorization were studied for CaO–FeO–SiO2 mixtures. The experiments were carried out at 1400 °C, in MgO-C crucibles, where the mixtures were added to the hot metal. Metal samples were taken at different times to measure the variation of phosphorus (P) content over time. The initial mixtures and final slags properties were determined by computational thermodynamics software FactSage 7.2. A parameter named Dephosphorization Factor (FDeP), that measures the efficiency of the initial mixtures and final slag, in hot metal dephosphorization was used. It was found that the FDeP presents a high correlation (R2) with the dephosphorization efficiency and can be used to predict which slag will be the most efficient.

Computational Thermodynamic Calculations: FactSage from CALPHAD Thermodynamic Database to Virtual Process Simulation

The CALPHAD-type computational thermodynamic databases have been developed since 1970. Several commercial computational thermodynamic software equipped with comprehensive and accurate thermodynamic databases and fast Gibbs energy minimization routine are widely used in the design of new materials and the optimization of materials processing. In this study, the FactSage software, which is the most frequently accessed software in high temperature materials processing, is briefly overviewed. The current databases and on-going directions of the thermodynamic database development are discussed. Application examples of FactSage thermodynamics databases to steel processing from the iron ore sintering process to the final metallic coating process are presented. Lastly, the most recent and future application of the FactSage thermodynamic databases to virtual steelmaking process simulations for the so-called industry 4.0 (smart factory) is highlighted.

Analysis of the influence of adding CaF2 and Na2O to steel desulfurizing mixtures using computational thermodynamics

Steel desulfurization mixtures of the CaO-Al2O3 system are the most industrially used. These mixtures require an amount of solid CaO to keep them always saturated in CaO. The aim of this paper is to study the influence of adding CaF2 and Na2O on the desulfurization efficiency of CaO-Al2O3 system mixtures. Desulfurizing steel mixtures capable of producing steels with sulfur content of less than 0.0020% were formulated. Desulfurizing mixtures based on CaO-Al2O3-flux were prepared with fluxes CaF2 and Na2O. All mixtures presented 95% of liquid phase and 5% of solid CaO, which, according to the literature, are the most efficient slags of this system. The equilibrium conditions were simulated using the composition of the mixtures and the steel by means of computational thermodynamic software. In these simulations, the activities of the slag components, the percentage of solids and liquids, the slag viscosity, and the equilibrium sulfur content were determined. The experimental tests were carried out in an induction furnace at 1600 °C. In addition, data on sulfide capacity (Cs), sulfur partition (Ls) and optical basicity (ʌ) of the initial mixtures, were calculated. The results of the simulations show that all mixtures have thermodynamic potential to reach the target of sulfur content set for this work. The mixtures with CaF2 proved to be the most efficient. However, it is possible to obtain sulfur contents of 0.0020% using mixtures without CaF2.

Horizontally Solidified Al–3 wt%Cu–(0.5 wt%Mg) Alloys: Tailoring Thermal Parameters, Microstructure, Microhardness, and Corrosion Behavior

In the present experimental investigation, Al–3 wt%Cu and Al–3 wt%Cu–0.5 wt%Mg alloys castings are produced by a horizontal solidification technique with a view to examining the interrelationship among growth rate (GR), cooling rate (CR), secondary dendrite arm spacing (λ2), Vickers microhardness (HV), and corrosion behavior in a 0.5 M NaCl solution. The intermetallic phases of the as-solidified microstructures, that is, θ-Al2Cu, S–Al2CuMg, and ω-Al7Cu2Fe, are subjected to a comprehensive characterization by using calculations provided by computational thermodynamics software, optical microscopy, and scanning electron microscopy/energy-dispersive spectroscopy. Moreover, electrochemical impedance spectroscopy and potentiodynamic polarization tests have been applied to analyze the corrosion performance of samples of both alloys castings. Hall–Petch-type equations are proposed to represent the HV dependence on λ2. It is shown that the addition of Mg to the Al–Cu alloy has led to a considerable increase in HV; however, the Al–Cu binary alloy is shown to have lower corrosion current density (icorr) as well as higher polarization resistance as compared to the corresponding results of the Al–Cu–Mg ternary alloy.

Evaluating the hot metal dephosphorization efficiency of different synthetic slags using phosphorus partition ratio, phosphate capacity and computational thermodynamics

Abstract Phosphate capability (CP) and phosphorus partition ratio (LP) are usually used to evaluate the thermodynamic efficiency of dephosphorization slags with different compositions in hot metal pretreatment. However, these parameters are only useful in equilibrium conditions, and they are not accurate when they are used to evaluate slag efficiency in industrial processes. The current study evaluated the hot metal dephosphorization efficiency of different synthetic slags in experimental tests at 1400oC. This evaluation was made by using CP and LP, and by the computational thermodynamic software FactSage 6.4. This software allows to calculate the amount of liquid and solid present in the slag, which directly affects kinetic reactions. Therefore, even the computational thermodynamic software calculations are from considering the equilibrium, which in these cases can be used to explain the kinetic behavior of the processes. The obtained results allow concluding that CP and LP are valid, but only when they are used for equilibrium calculations; and that they should not be used to measure slag efficiency in industrial processes. A parameter named Dephosphorization Factor (FDeP) was developed based on data determined by computational thermodynamics. It was developed to be related to the dephosphorization efficiency. The results obtained in the current study allow to conclude that the initial synthetic slags, which presented higher CaO activity value, higher liquid quantity and FeO activity, will be the most efficient ones. And allow to conclude too, that the higher the factor, the greater the slag dephosphorization efficiency.

Synthesis and Comparative Study on Intergranular Corrosion Characteristics of Stabilized 5A Grade Cast Duplex Stainless Steel

Abstract In this paper, stabilization using zirconium and niobium was investigated to reduce the effect of intergranular corrosion (IGC) in 5A grade cast duplex stainless steel. Computational thermodynamic software was used to determine the various heat treatment temperatures according to phase precipitation. Resistance to IGC was investigated by oxalic acid etch test and double-loop electrochemical potentiokinetic reactivation (DL-EPR) technique. The surface of the specimens was observed using optical microscopy, scanning electron microscopy, energy dispersive spectroscopy, and X-ray diffractometry to evaluate the presence of various intermetallic phases prone to IGC. Oxalic acid etch test response has indicated the susceptibility, whereas the DL-EPR test has provided the degree of sensitization. The results revealed that zirconium-stabilized samples are more susceptible to IGC compared to the niobium samples. Earlier formation of niobium compounds led to the reduction of intergranular attack in the niobium-stabilized samples.

Evaluation of thermophysical properties of Al–Sn–Si alloys based on computational thermodynamics and validation by numerical and experimental simulation of solidification

Modelling of manufacturing processes of multicomponent Al-based alloys products, such as casting, requires thermophysical properties that are rarely found in the literature. It is extremely important to use reliable values of such properties, as they can influence critically on simulated output results. In the present study, a numerical routine is developed and connected in real runtime execution to a computational thermodynamic software with a view to permitting thermophysical properties such as: latent heats; specific heats; temperatures and heats of transformation; phase fractions and composition and density of Al–Sn–Si alloys as a function of temperature, to be determined. A numerical solidification model is used to run solidification simulations of ternary Al-based alloys using the appropriate calculated thermophysical properties. Directional solidification experiments are carried out with two Al–Sn–Si alloys compositions to provide experimental cooling rates profiles along the length of the castings, which are compared with numerical simulations in order to validate the calculated thermophysical data. For both cases a good agreement can be observed, indicating the relevance of applicability of the proposed approach.

Application of computational thermodynamics to the determination of thermophysical properties as a function of temperature for multicomponent Al-based alloys

Despite the technological importance of Al–Si–Cu alloys in manufacturing processes involving heat transfer, such as welding, casting and heat treatment, thermophysical properties of this system of alloys are very scarce in the literature. In this paper, a model connected to a computational thermodynamics software is proposed permitting density and specific heats as a function of temperature and enthalpy of transformations to be numerically determined. The model is pre-validated against experimental density as a function of temperature for liquid and solid phases of A319 and 7075 alloys found in the literature and validated against experimental density values for the solid phase of an Al-6wt%Cu-1wt%Si alloy determined in the present study. In both cases the numerical predictions are in good agreement with the experimental results. Specific heat and temperatures and heats of transformation are also numerically determined for this ternary Al-based alloy.

Analysis of pig iron desulfurization with mixtures from the CaO-Fluorspar and CaO-Sodalite system with the use of computational thermodynamics

This work aims at the use of computational thermodynamics in the study of desulfurization of pig iron through CaO-Fluorspar and CaO-Sodalite mixtures. Experiments were performed with the addition of different mixtures from these systems in molten pig iron at a temperature of 1,400ºC. The test results were analyzed and compared with those obtained by the computational thermodynamics software program THERMOCALC. Through this software, were calculated the equilibrium sulfur content in the metal, solid phases, and the amount of liquid in each desulfurizing mixture used in the process at a temperature of 1,400ºC. The computational thermodynamics proved to be an effective tool in predicting the desulfurization capacity of the mixtures.

Estimating Viscosities in Iron and Steelmaking Slags in the CaO-Al2O3-MgO-SiO2-(TiO2) System with Basis on a Thermodynamic Model

Slags are critical components in several iron and steelmaking processes. In steelmaking, different slags with various properties are used in the different processing steps from melting and refining to continuous casting. Thermodynamic properties, viscosity and surface tension are among the most important properties considered in the design of slag compositions for steel processing. A brief literature review of the approaches at modeling viscosities shows that viscosity correlations with chemical composition, basicity (both chemical and optical), and more recently with slag constitution have been attempted with different degrees of success. In this work, a model based on the Riboud viscosity model combined with the thermodynamic Kappor-Frohberg-Gaye cell model is described and presented as a potential alternative to obtaining slag viscosity estimates directly from computational thermodynamics software. The first results of the adjustment and application of the model to the CaO-Al2O3-MgO-SiO2 system are presented. The quality of the adjustment is discussed as well as its current limitations. Future steps in the model development involve its extension to include FeO, TiO2, and CaF2.

Understanding stainless steelmaking through computational thermodynamics: Part 3 – AOD converting

The major issue in stainless steelmaking is the difficulty of oxidising carbon from molten steel without also oxidising large proportions of expensive chromium. This can, however, be achieved by reducing the partial pressure of the gaseous product of carbon oxidation, carbon monoxide, by dilution with argon. Modern stainless steelmaking is dominated by duplex processes which prepare a high carbon melt in an electric arc furnace, and then decarburise it in an argon–oxygen decarburisation (AOD) converter. In this work, the thermodynamic basis of preferential carbon oxidation by dilution of oxygen with argon is discussed, together with a review of AOD practice. The AOD process was simulated using computational thermodynamics software to illustrate the way in which it can achieve very low carbon levels in the molten steel bath without excessive co-oxidation of chromium. The slag reduction stage using ferrosilicon additions was also modelled and shown to be able to recover almost all oxidised chromium from the slag, limited only by the accompanying increase in the silicon content of the steel. The models, although simple and easy to develop, correctly predicted all trends in output variables as input parameters were changed and often matched plant data very well. The models provide a valuable learning tool for those interested in pyrometallurgical processing in general, and stainless steelmaking in particular.

The application of computational thermodynamics and a numerical model for the determination of surface tension and Gibbs–Thomson coefficient of aluminum based alloys

In this paper, a solution for Butler's formulation is presented permitting the surface tension and the Gibbs–Thomson coefficient of Al-based binary alloys to be determined. The importance of Gibbs–Thomson coefficient for binary alloys is related to the reliability of predictions furnished by predictive cellular and dendritic growth models and of numerical computations of solidification thermal variables, which will be strongly dependent on the thermophysical properties assumed for the calculations. A numerical model based on Powell hybrid algorithm and a finite difference Jacobian approximation was coupled to a specific interface of a computational thermodynamics software in order to assess the excess Gibbs energy of the liquid phase, permitting the surface tension and Gibbs–Thomson coefficient for Al–Fe, Al–Ni, Al–Cu and Al–Si hypoeutectic alloys to be calculated. The computed results are presented as a function of the alloy composition.

Selection of thermodynamic data for a novel carbothermic smelting process for aluminum

For the carbothermic production of aluminum, thermodynamic data are required for the condensed compounds and gas phase involved in the Al2O3-C or Al2O3-Al4C3 systems. The data for Al2O3(s, l), Al4C3(s), CO(g), C(s, g), Al(s, l, g), Al2O(g) and AlO(g) in different databases is in accord. For a novel carbothermic aluminum smelting process, currently in development, the published JANAF Thermochemical Tables were selected for calculations. However, the JANAF Tables do not include data for oxycarbides. Thus a literature review was conducted. Data from different sources was collated and found to be in accord for Al4O4C over the 1,600–2,200 K temperature range. These data, together with the data from JANAF Tables, agree very well with the experimental results obtained during the carbothermic process. However, a commercially available computational thermodynamic software package called HSC provides results which contradict the experimental results obtained, while its thermodynamics data is also significantly different from other data available in the literature.

Understanding stainless steelmaking through computational thermodynamics Part 2 – VOD converting

The central issue in stainless steelmaking is the difficulty of oxidising carbon from molten steel without also oxidising large proportions of expensive chromium. This can, however, be achieved by reducing the partial pressure of the gaseous product of carbon oxidation, carbon monoxide. Modern stainless steelmaking is dominated by duplex processes, which prepare a high carbon melt in an electrical arc furnace and then decarburise the melt in a converter, such as a 'vacuum oxygen decarburisation' converter in which oxygen is blown onto the melt in an evacuated chamber. In this work, the thermodynamic basis of preferential carbon oxidation at low total pressures is discussed, together with a review of VOD practice. VOD steelmaking is then simulated using computational thermodynamics software to illustrate the process principles. It was predicted that CrO is the dominant chromium oxide species in slag and that solid CrO1·5 will be formed during oxygen blowing. Carbon contents as low as 0·001 wt-% are possible, but not achieved due to mass transfer rate limitations. Silicon is a very effective reductant for chromium oxides and also reduces some of the MnO in slag. The recovery of chromium from the slag is very high, but limited by the increasing proportion of added silicon, which dissolves into the steel bath.

Integrated modelling of thermal cycles, austenite formation, grain growth and decomposition in the heat affected zone of carbon steel

The microstructure evolution in the heat affected zone (HAZ) of 1005 low carbon steel during gas tungsten arc welding (GTAW) was quantitatively investigated using a combination of several numerical models. In particular, the α ferrite→γ austenite phase transformation during heating was studied using a Johnson–Mehl–Avrami (JMA) analysis, the γ grain growth was calculated using a Monte Carlo simulation, and the γ→α transformation during cooling was examined using an austenite decomposition model. In addition, the phase equilibria of the 1005 steel were calculated using computational thermodynamics software, Thermo-Calc, while the necessary temperature v. time data for all the microstructure models were obtained from a thermofluid model. These models were then used to calculate the extent of austenitisation with time during heating, the γ grain growth, and the volume fractions of various microconstituents of the final microstructure in the HAZ. It was found that a considerable amount of superheat was required for the initiation and completion of the α→γ transformation under the heating rates typical of arc welding. Significant γ grain growth was found to take place in the HAZ, particularly in the vicinity of the fusion zone (FZ) boundary, where the computed maximum γ grain size was about eight times greater than that of the base metal. The predicted final microstructure in the HAZ was predominantly allotriomorphic and Widmanstatten ferrites, which was consistent with the post-weld metallographic measurements. Overall, the computed microstructure evolution in the HAZ using the multiphenomena models was consistent with the available experimental data. The results reported here indicate that it is now possible to develop a quantitative model of complex weld microstructure evolution with the recent advances in transport phenomena and phase transformation models.