Three-Compound Mixture Phase Behavior in Liquid-Liquid Equilibrium

These datasets contain tieline information for generic three-compound mixtures in liquid-liquid equilibrium, including an ionic liquid and two organic molecules. The data was collected from the ILThermo database and transformed to model molar fractions, with separate training, optimization, and test sets randomly generated to ensure chemical system uniqueness. Author Gonçalo V. S. M. Carrera compiled the information, which focuses on molar and weight fractions.

Use Cases

• Training machine learning models to predict phase behavior based on mixture composition, temperature, and pressure parameters.
• Optimizing thermodynamic models for ionic liquid-rich and ionic liquid-poor phases in equilibrium.
• Testing model generalization on chemical systems not present in the training or optimization datasets.

Strengths

• Data is derived from the authoritative ILThermo database.
• Datasets were split into training, optimization, and test sets with non-overlapping chemical systems.
• Each tieline is represented by five randomly generated global composition points.

Limitations

• Row count and dataset size are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

ILThermo database

Collection Method

Information on molar and weight fractions was collected and transformed for modeling.