ThermoPropDatabase: Experimental Thermophysical Properties for Model Benchmarking

A curated SQLite database of experimental thermophysical properties supports transparent benchmarking for model development. The database includes properties such as vapor-liquid equilibrium, liquid density, isobaric heat capacity, excess enthalpy of mixing, and speed of sound. It was authored by Javad Amanabadi and last updated on May 12, 2026.

Use Cases

• Benchmarking predictive models for vapor-liquid equilibrium based on experimental data.
• Validating thermodynamic property calculators against liquid density measurements.
• Training machine learning models on isobaric heat capacity data.
• Assessing mixture models using excess enthalpy of mixing data.
• Calibrating acoustic property models with speed of sound measurements.

Strengths

• Curated and extensible SQLite database structure facilitates consistent benchmarking.
• Covers a wide range of thermophysical properties including VLE, density, heat capacity, enthalpy, and speed of sound.
• Released under a permissive CC-BY-4.0 license for open use and sharing.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for large-scale training.

Provenance

Source

figshare

Collection Method

Curated from experimental sources.

Freshness

Last updated 2026-05-12 10:51:38.