Laser-Driven Calorimetry and Chemometric Quantification of Standard Reference Material Diesel/Biodiesel Fuel Blends

Area of Science:

• Analytical Chemistry
• Materials Science
• Chemical Engineering

Background:

• Drop-in petroleum/bio-derived fuels require specific thermophysical and thermochemical properties.
• Predictive chemometric models are essential for analyzing fuel blends.

Purpose of the Study:

• To evaluate multivariate calibration methods for predicting properties of diesel/biodiesel fuel blends.
• To assess the effectiveness of laser-driven calorimetry and chemometrics for fuel analysis.

Main Methods:

• 11 diesel/biodiesel blends were prepared using National Institute of Standards and Technology (NIST) Standard Reference Material (SRM) pure fuels.
• Laser-driven calorimetry was employed to measure thermograms (temperature change over time).
• Partial least squares (PLS) and Support Vector Machine (SVM) models were constructed for quantification.

Main Results:

• SVM models demonstrated a stronger correlation with experimental results compared to PLS models.
• The study successfully quantified fuel-blend volume fractions and heating values.
• Thermograms provided valuable thermochemical characteristics of the fuel blends.

Conclusions:

• Laser-driven calorimetry combined with multivariate calibration offers a promising approach for fuel quantification.
• Thermograms can be effectively utilized for analyzing fuel blend properties and composition.
• SVM models show superior performance for predicting fuel blend characteristics.