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Updated: Sep 5, 2025
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Phase Behavior of Charged Vesicles Under Symmetric and Asymmetric Solution Conditions Monitored with Fluorescence Microscopy
Published on: October 24, 2017
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Uncertainty quantification of phase transition quantities from cluster weighting calculations.
Jan Blasius1, Paul Zaby1, Jürgen Dölz2
1Mulliken Center for Theoretical Chemistry, Institute for Physical and Theoretical Chemistry, University of Bonn, Beringstr. 4+6, 53115 Bonn, Germany.
The Journal of Chemical Physics
|July 8, 2022
Summary
Uncertainty in experimental data significantly impacts quantum calculations of vaporization thermodynamics for organic liquids. The boiling point strongly affects enthalpy but not entropy, with Gauss-Hermite estimators proving superior for uncertainty quantification.
Area of Science:
- Theoretical Chemistry
- Physical Chemistry
- Computational Chemistry
Background:
- Quantum cluster equilibrium calculations are crucial for determining thermodynamic properties.
- Experimental data uncertainties can propagate and affect the accuracy of these calculations.
- Understanding this influence is vital for reliable theoretical chemistry predictions.
Purpose of the Study:
- To investigate the impact of experimental input data uncertainties on quantum cluster equilibrium calculations.
- To analyze the influence of reference density and boiling point on vaporization thermodynamics.
- To compare computational approaches for uncertainty quantification in thermodynamic functions.
Main Methods:
- Calculated vaporization enthalpies and entropies for seven organic liquids using quantum cluster equilibrium.
- Varied experimental input data (reference density, boiling point) to assess sensitivity.
- Employed the Gauss-Hermite estimator and Monte Carlo methods for uncertainty quantification.
Main Results:
- Vaporization thermodynamics exhibit a smooth dependence on reference density and boiling point.
- Boiling point significantly influences vaporization enthalpy but minimally affects vaporization entropy.
- Gauss-Hermite estimator demonstrated superior convergence and computational efficiency compared to Monte Carlo.
Conclusions:
- Uncertainty quantification in theoretical chemistry is feasible and essential for accurate thermodynamic predictions.
- The Gauss-Hermite estimator provides a robust method for assessing data uncertainties in computational chemistry.
- This study highlights the importance of carefully considering experimental data quality in theoretical calculations.
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