Abstract
The technological inspection of the electrolyte composition in aluminum production is performed using calibration X-ray quantitative phase analysis (QPA). For this purpose, the use of QPA by the Rietveld method, which does not require the creation of multiphase reference samples and is able to take into account the actual structure of the phases in the samples, could be promising. However, its limitations are in its low automation and in the problem of setting the correct initial values of profile and structural parameters. A possible solution to this problem is the application of the genetic algorithm we proposed earlier for finding suitable initial parameter values individually for each sample. However, the genetic algorithm also needs tuning. A self-configuring genetic algorithm that does not require tuning and provides a fully automatic analysis of the electrolyte composition by the Rietveld method was proposed, and successful testing results were presented.
Highlights
Aluminum is normally produced by the electrolysis of alumina in molten fluorides at a temperature of around 950 ◦ C
We provide a self-configuring genetic algorithm, which works without a preliminary adjustment and performs the fully automated analysis of aluminum electrolyte composition by the Rietveld method
One of the possible approaches to tackle this problem is the application of genetic algorithms (GAs) for the choice of an initial approximation of sample parameters, for the evolutionary selection of perspective parameters, and for their automated refinement with Rietveld’s least squares method (LSM)
Summary
Aluminum is normally produced by the electrolysis of alumina in molten fluorides at a temperature of around 950 ◦ C. The main component of the molten electrolyte is cryolite (Na3 AlF6 ), whilst aluminum fluoride, calcium fluoride, and sometimes magnesium fluoride and potassium fluoride are added to improve the cryolite’s technological properties. The composition of the electrolyte in the baths continuously changes and shifts from the optimum. The maintenance of an optimal bath composition is a vital element in electrolysis technology. An integral characteristic of the bath composition is the cryolite ratio (CR)—the ratio of molar concentrations of sodium fluoride and aluminum fluoride (1): CR = C(NaF, mol.
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