Resumen

LAZZUS, J.A.  y  RIVERA, M.. Gas-solid phase equilibrium of biosubstances by two biological algorithms. Rev. mex. fis. [online]. 2013, vol.59, n.6, pp.577-583. ISSN 0035-001X.

Particle swarm optimization (PSO) and genetic algorithm (GA) are applied to the gas-solid phase equilibrium of biosubstances and to estimate their sublimation pressures (P^s). Four binary systems of supercritical carbon dioxide + biosubstances are considered in this study. The Peng-Robinson equation-of-state with the Wong-Sandler mixing rules, are used as a thermodynamic model to evaluate the fugacity coefficients in the classical solubility equation, and the van Laar model was incorporated to evaluate the excess Gibbs free energy included in the mixing rules. Then, the P^s is calculated from regression analysis of solubility data (y). P^s is usually small for most solid biosubstances and in many cases available experimental techniques cannot be used to obtain accurate values. Therefore, estimation methods must be used to obtain these data. PSO and GA are used for minimize the difference between calculated and experimental solubility. Comparing PSO with GA, it is shown that the results of PSO are better than that of GA, and provide a preferable method to estimate y and P^s of any biosubstances with high accuracy.

Palabras llave : Sublimation pressure; biosubstances; gas-solid equilibrium; equation of state; genetic algorithm; particle swarm optimization.

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