Communication: Fundamental equation of state correlation with hybrid data sets

Area of Science:

• Thermodynamics
• Physical Chemistry
• Computational Chemistry

Background:

• Fundamental equations of state are crucial for predicting fluid properties.
• Existing correlations often rely solely on experimental data, which can be limited.
• Molecular simulation offers a complementary data source for developing these equations.

Purpose of the Study:

• To propose a novel strategy for developing empirical fundamental equation of state correlations.
• To utilize hybrid data sets combining experimental and molecular simulation results.
• To demonstrate the strategy's effectiveness using pure fluids like argon and hydrogen chloride.

Main Methods:

• Developing a hybrid data set by integrating experimental measurements and molecular simulation outputs.
• Applying established correlation techniques to the hybrid data set.
• Validating the resulting equation of state against independent data.

Main Results:

• The proposed strategy successfully generated accurate fundamental equations of state for argon and hydrogen chloride.
• Hybrid data sets provided a more comprehensive basis for correlations compared to using experimental data alone.
• The developed correlations showed good agreement with known thermodynamic properties.

Conclusions:

• The hybrid data approach is a viable and effective strategy for empirical equation of state development.
• This method improves the accuracy and reliability of thermodynamic property predictions for pure fluids.
• The strategy offers a pathway for more robust correlations in chemical engineering and materials science.