Structural Modelling of Hydrocarbons for the Prediction of Octane Number and Designing of Sustainable Synthetic Fuel

EasyChair Preprint 4265

Abstract

Quantitative Structure Property Relationship has been performed in order to model a hydrocarbon structure with effective octane number. To achieve this goal, a set of 42 hydrocarbon has been taken and encoded in the form of structural descriptors viz., Wiener Index (W), Zero order, First order and Second order Connectivity Index(χ0,χ1,χ2), Shultz Molecular Topological Index(SMTI), Balaban J Index(J) and Indicator parameter(Ic) and multiple linear regression analysis (MLR) has been performed. The results of MLR indicate that SMTI, J, Connectivity Indices with an indicator parameter were playing a dominating role to regulate Octane number, therefore these descriptors can be used to predict the Octane number of an unknown hydrocarbon. The predictive ability of the mathematical model obtained in Quantitative Structure Property Relationship analysis is further cross validated by External validation method in which a set of 25 other hydrocarbons were tested on the same model. The model obtained in the study is effectively reflecting the structural requirements within the hydrocarbon to obtain higher octane number, also it can be used to model novel hydrocarbon structures that can be used as a synthetic fuel and that can be a sustainable energy resource in future.

Keyphrases: Hydrocarbon, Octane Number, fuel, molecular modeling

@booklet{EasyChair:4265,
  author    = {Sanjay Kumar and Mamta Thakur and Naman Shah and Sarthak Jain},
  title     = {Structural Modelling of Hydrocarbons for the Prediction of Octane Number and Designing of Sustainable Synthetic Fuel},
  howpublished = {EasyChair Preprint 4265},
  year      = {EasyChair, 2020}}