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Diseño Computacional de Sistemas Eutécticos Naturales Profundos Utilizando COSMO-RS para Aplicaciones de Control de
Akshat S Mallya1, Priyanka Yadav1, Stephanie Zakhia1
1Department of Mechanical Engineering, University of Minnesota Twin Cities, Minneapolis, Minnesota 55414, United States.
ACS sustainable chemistry & engineering
|January 26, 2026
Resumen
Este estudio presenta un método computacional para predecir Sistemas Eutécticos Naturales Profundos (NADES) para el control de hielo. Los NADES optimizados reducen significativamente la formación de hielo y las entalpías de fusión, ofreciendo una alternativa más ecológica a los métodos tradicionales.
Área de la Ciencia:
- Química Verde
- Química Computacional
- Ciencia de Materiales
Sus antecedentes:
- Los Sistemas Eutécticos Naturales Profundos (NADES) ofrecen alternativas sostenibles y de baja toxicidad en química.
- El desarrollo actual de NADES se basa en métodos empíricos, lo que requiere optimización para aplicaciones específicas como el control de hielo.
Objetivo del estudio:
- Desarrollar una metodología in silico para la preselección y predicción de composiciones eutécticas de NADES.
- Optimizar NADES para aplicaciones efectivas de control de hielo.
Principales métodos:
- Se utilizó el modelo de detección similar al conductor para disolventes reales (COSMOS-RS) para predecir coeficientes de actividad y diagramas de fase binarios.
- Se empleó calorimetría diferencial de barrido (DSC) y espectroscopía Raman a baja temperatura para la validación experimental.
- Se analizaron descriptores de química cuántica para identificar nuevos parámetros de preselección.
Principales resultados:
- Las composiciones eutécticas predichas de NADES mostraron entalpías de fusión significativamente reducidas (>70%) y formación de cristales de hielo (>50%) en comparación con el agua pura.
- La caracterización experimental confirmó el potencial anticongelante de NADES seleccionados de aminoácidos-alcoholes de azúcar (AA-SA) y azúcares-alcoholes de azúcar (SU-SA).
- Identificaron momentos de enlace de hidrógeno como un posible nuevo descriptor para la preselección de NADES.
Conclusiones:
- La metodología in silico predice eficazmente las composiciones eutécticas de NADES con propiedades mejoradas de control de hielo.
- Los NADES desarrollados demuestran un potencial significativo para aplicaciones sostenibles de lucha contra el hielo.
- Los descriptores de química cuántica ofrecen nuevas vías para desarrollar modelos de relación cuantitativa estructura-propiedad (QSPR) para el diseño de NADES.
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