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Molecular Engineering of BiofuelsPDF
  • Introduction
  • Results I
  • Results II
  • Conclusions

Introduction & Motivation

Molecular engineering of biofuels can be accomplished through the use of model compound studies in combination with property prediction. Model compound studies give insight to the fundamental relationships between a catalyst and a molecule that govern product selectivity. In order to provide direction towards an optimized feed, fuel properties of interest (CN, ON, solubility in water, vapor pressure, stability, cloud point, etc.)must be known for each specific reaction product. For this reason, we implement QSPR to predict fuel properties of molecules whose properties have not previously been measured. With this tool, direction is given towards the specific bonds that must be broken, etc. in order to maximize the value of a fuel. Information gained through these studies is then used to develop optimized strategies for upgrading of biofuels.

introduction

QSPR Models for Prediction of Fuel Properties

Quantitative Structure Property Relationships

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QSPR is a very valuable tool for predicting fuel properties of reaction products which have not been previously measured.

project3c

QSPR models have been created by our group to predict Octane Number (RON and MON), Cetane number, sooting tendency, product selectivity, and many more fuel properties based only on molecular structure

Model compound studies and kinetic analysis

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QSPR prediction of fuel properties of potential reaction products

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Results

Maximum properties except for BP obtained with Cu at 290 °C while maximizing 2-methylfuran

result1results2

Model ketone to study C-O hydrogenolysis without decarbonylation

kinetics

Predicted Research Octane Number

 

Results

Initial benefits at lower temperature in ON and BP.

Higher T and conversion results in a tradeoff between ON, BP and specific volume, logP

Conclusions

A combination of QSPR with model compound studies provides direction for molecular engineering of fuels. Through these studies, catalytic strategies can be developed by optimizing fuel properties while at the same time understanding the fundamental relationships between the molecules and catalysts.