Measurement uncertainty of thermodynamic data

Area of Science:

• Chemical Thermodynamics
• Metrology
• Analytical Chemistry

Background:

• Thermodynamic quantities are typically derived from experimental chemical analysis data.
• Measurement uncertainty in analytical techniques limits the accuracy of evaluated thermodynamic quantities.
• Existing metrological rules are insufficient for complex thermodynamic evaluations.

Purpose of the Study:

• To integrate metrological concepts with computer-intensive statistical methods for evaluating thermodynamic quantities.
• To address the limitations of traditional analytical methods in determining thermodynamic accuracy.
• To present an initial stage of integrating these concepts using solubility data.

Main Methods:

• Utilized computer-intensive statistical methods and Monte Carlo techniques.
• Applied resampling-based Monte Carlo studies for uncertainty analysis.
• Employed a cause and effect diagram to identify uncertainty sources.

Main Results:

• Demonstrated the integration of metrological concepts with advanced statistical methods.
• Successfully produced a probability distribution for a quantity's value using uncertainty data.
• Illustrated the approach with solubility data for Americium(III) in carbonate media.

Conclusions:

• Computer-intensive methods enable a more robust evaluation of thermodynamic quantities.
• The presented approach enhances the integration of metrology and statistical analysis.
• This methodology improves the assessment of uncertainty in thermodynamic measurements.