Evaluación de SAFT-VR Mie y SAFT-γ Mie en la modelación de sistemas basados en aminas.
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Date
2025
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Publisher
Universidad de Concepción
Abstract
El aumento de emisiones de gases de efecto invernadero, específ
icamente el dióxido de carbono (CO2), surgen propuestas conjuntas como el Protocolo de Kioto y el Acuerdo de París y el desafío de alcanzar cero emisiones netas para 2050 establecido por la ONU. Este trabajo se enfoca en la descripción de sistemas basados en aminas, dada la elevada madurez tecnológica de esta solución para la absorción de CO2. Reconociendo los altos requerimientos energéticos del proceso, se presenta el desafío de desarrollar nuevas aminas más eficientes. La escasez de datos experimentales de sistemas de CO2 con aminas acuosas impulsa el uso de modelado con capacidad predictiva. Por ello, este trabajo desarrolló la modelación de soluciones acuosas de aminas mediante ecuaciones de estado de base molecular, capaces de describir el comportamiento físico y químico de interacción a través de una asociación física. Estas ecuaciones, agrupadas bajo el acrónimo SAFT (Statistical Associating Fluid Theory), son específicamente las versiones de tercera generación SAFT-γ Mie y SAFT-VR Mie.
El objetivo de esta investigación fue comparar cuantitativamente la capacidad descriptiva de ambos modelos para el equilibrio líquido-vapor en sistemas formados por soluciones acuosas de aminas, mediante la parametrización de compuestos puros y mezclas binarias. En la metodología, se desarrolló la parametrización para SAFT-VR Mie mediante datos experimentales y la
construcción de las moléculas para SAFT-γ Mie. Para ello, se utilizó la herramienta SGTPy un código en lenguaje Python que incluye la codificación de ambas ecuaciones, posteriormente se realizó una comparación cuantitativa de ambos métodos a través de la desviación de los resultados en equilibrios de fase con datos experimentales extraídos de la literatura y la base de
datos DIPPR.
Se concluye que la parametrización de compuestos mediante BOTTLE SAFT se reveló como un buen punto inicial, aunque la descripción de mezclas depende de una adecuada caracterización de sitios de asociación, rango (rAB c ) y energía de asociación (ϵAB), sugiriendo un beneficio en el ajuste simultáneo de compuestos puros y mezclas. Al comparar las ecuaciones de estado, SAFT-VR Mie presenta una mejor descripción de los compuestos puros y mezclas binarias, aunque no se logra una descripción adecuada del sistema ternario. Por otro lado, SAFT-γ Mie, aunque capaz de capturar cualitativamente la gran mayoría de sistemas, presentó una mayor desviación cuantitativa. Para su aplicación futura en el estudio de nuevos solventes, es necesaria una revisión y generación de nuevas interacciones entre grupos funcionales SAFT-γ Mie, con un enfoque más amplio que considere mezclas y compuestos con múltiples grupos amino.
The increase in greenhouse gas emissions, specifically carbon dioxide (CO2), has led to joint initiatives such as the Kyoto Protocol and the Paris Agreement, as well as the challenge of achieving net-zero emissions by 2050 set by the United Nations. This work focuses on the description of amine-based systems, given the high technological maturity of this solution for CO2 absorption. Recognizing the high energy requirements of the process, the development of more efficient amines arises as a major challenge. The scarcity of experimental data on CO2 systems with aqueous amines motivates the use of predictive modeling. Therefore, this work developed the modeling of aqueous amine solutions using molecular-based equations of state, capable of describing physical and chemical interactions through physical association. These equations, grouped under the acronym SAFT (Statistical Associating Fluid Theory), specifically refer to the third-generation versions SAFT-γ Mie and SAFT-VR Mie. The objective of this research was to quantitatively compare the descriptive capability of both models for vapor-liquid equilibrium in systems composed of aqueous amine solutions, through the parametrization of pure compounds and binary mixtures. The methodology involved parametrizing SAFT-VR Mie using experimental data and constructing the molecular models for SAFT-γ Mie. For this purpose, the SGTPy tool was used, a Python-based code that implements both equations. A quantitative comparison was then performed based on the deviation of phase equilibrium predictions from experimental data extracted from the literature and the DIPPR database. It is concluded that the parametrization of compounds using BOTTLE SAFT proved to be a good starting point; however, the description of mixtures depends on proper characterization of association sites, range (rAB c ), and association energy (ϵAB), suggesting a benefit from simultaneous fitting of pure compounds and mixtures. When comparing the equations of state, SAFT-VR Mie provides a better description of pure compounds and binary mixtures, although it does not adequately describe the ternary system. On the other hand, SAFT-γ Mie, while capable of qualitatively capturing most systems, showed greater quantitative deviations. For future applications in the study of new solvents, it is necessary to review and generate new SAFT-γ Mie functional group interactions, with a broader approach that considers mixtures and compounds with multiple amino groups.
The increase in greenhouse gas emissions, specifically carbon dioxide (CO2), has led to joint initiatives such as the Kyoto Protocol and the Paris Agreement, as well as the challenge of achieving net-zero emissions by 2050 set by the United Nations. This work focuses on the description of amine-based systems, given the high technological maturity of this solution for CO2 absorption. Recognizing the high energy requirements of the process, the development of more efficient amines arises as a major challenge. The scarcity of experimental data on CO2 systems with aqueous amines motivates the use of predictive modeling. Therefore, this work developed the modeling of aqueous amine solutions using molecular-based equations of state, capable of describing physical and chemical interactions through physical association. These equations, grouped under the acronym SAFT (Statistical Associating Fluid Theory), specifically refer to the third-generation versions SAFT-γ Mie and SAFT-VR Mie. The objective of this research was to quantitatively compare the descriptive capability of both models for vapor-liquid equilibrium in systems composed of aqueous amine solutions, through the parametrization of pure compounds and binary mixtures. The methodology involved parametrizing SAFT-VR Mie using experimental data and constructing the molecular models for SAFT-γ Mie. For this purpose, the SGTPy tool was used, a Python-based code that implements both equations. A quantitative comparison was then performed based on the deviation of phase equilibrium predictions from experimental data extracted from the literature and the DIPPR database. It is concluded that the parametrization of compounds using BOTTLE SAFT proved to be a good starting point; however, the description of mixtures depends on proper characterization of association sites, range (rAB c ), and association energy (ϵAB), suggesting a benefit from simultaneous fitting of pure compounds and mixtures. When comparing the equations of state, SAFT-VR Mie provides a better description of pure compounds and binary mixtures, although it does not adequately describe the ternary system. On the other hand, SAFT-γ Mie, while capable of qualitatively capturing most systems, showed greater quantitative deviations. For future applications in the study of new solvents, it is necessary to review and generate new SAFT-γ Mie functional group interactions, with a broader approach that considers mixtures and compounds with multiple amino groups.
Description
Tesis presentada para optar al título de Ingeniero/a Civil Químico/a.
Keywords
Aminas, Equilibrio vapor-líquido, Dióxido de carbono, Soluciones (Minería)