Computing Entropy for Long-Chain Alkanes Using Linear Regression
Author Information
Author(s): Sharma Shrinjay, Baur Richard, Rigutto Marcello, Zuidema Erik, Agarwal Umang, Calero Sofia, Dubbeldam David, Vlugt Thijs J. H.
Primary Institution: Delft University of Technology
Hypothesis
Can a linear regression model based on second-order group contributions accurately predict the thermochemical properties of long-chain alkanes?
Conclusion
The linear regression model effectively predicts the absolute entropies of long-chain alkanes, showing excellent agreement with experimental data.
Supporting Evidence
- The computed entropies show excellent agreement with experimental data.
- Entropy production and heat input were calculated for hydroisomerization of C7 isomers in various zeolites.
- Longer alkanes showed increased heat input and entropy production.
- The model captures variations in entropy due to differences in branching.
- Unique reaction product distributions were observed in hydroisomerization across different zeolites.
Takeaway
This study shows how scientists can use math to figure out the energy and heat of long-chain molecules, which helps in making better fuels.
Methodology
A linear regression model based on second-order group contributions was developed to predict thermochemical properties of alkanes.
Limitations
The model may struggle with extrapolation for alkanes longer than C10 and relies on accurate independent variables.
Digital Object Identifier (DOI)
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