Quantitative Correlation of Physical and Chemical Properties with Chemical Structure: Utility for Prediction

An improved model for the prediction of ignition quality of hydrocarbon fuels has been developed using 1H nuclear magnetic resonance (NMR) spectroscopy and multiple linear regression (MLR) modeling. Cetane number (CN) and derived cetane number (DCN) of 71 pure hydrocarbons and 54 hydrocarbon blends were utilized as a data set to study the relationship between ignition quality and molecular structure. CN and DCN are functional equivalents and collectively referred to as D/CN, herein. The effect of molecular weight and weight percent of structural parameters such as paraffinic CH3 groups, paraffinic CH2 groups, paraffinic CH groups, olefinic CH–CH2 groups, naphthenic CH–CH2 groups, and aromatic C–CH groups on D/CN was studied. A particular emphasis on the effect of branching (i.e., methyl substitution) on the D/CN was studied, and a new parameter denoted as the branching index (BI) was introduced to quantify this effect. A new formula was developed to calculate the BI of hydrocarbon fuels using 1H NMR spect...

Predicting Fuel Ignition Quality Using 1H NMR Spectroscopy and Multiple Linear Regression

The assessment of the ignition quality of a wide range of oxygenated hydrocarbons is one key challenge in the identification of novel molecular entities qualifying as biofuels or biofuel blend components derived from oxygen-rich lignocellulosic feedstocks. The present contribution summarizes the results from a comprehensive experimental screening campaign targeting a diverse set of pure-component oxygenated hydrocarbon fuels and their ignition characteristics in an ASTM D6890 Ignition Quality Tester (IQT). This constant-volume combustion chamber experiment has been chosen because of its rapid screening potential. The unique collection of data is utilized for group contribution modeling with the aim of unraveling relationships between the ignition delay observed in IQT experiments and the fuel’s molecular structure. We propose a simple, yet predictive, estimator for the derived cetane number of pure oxygenated hydrocarbons covering acyclic and cyclic, branched and straight, saturated and unsaturated hydroc...

A Novel Group Contribution Method for the Prediction of the Derived Cetane Number of Oxygenated Hydrocarbons

Prediction of combustion-related properties of (oxygenated) hydrocarbons is an important and challenging task for which quantitative structure–property relationship (QSPR) models are frequently emp...

Graph neural networks for prediction of fuel ignition quality

In the present work, a quantitative structure property relationship (QSPR) methodology has been applied to predict the cetane number (CN) of hydrocarbons that are likely to be found in diesel fuels. A database containing 147 molecules has been set up with experimental CNs available in the literature. The prediction of the CN was improved by dividing the database into four chemical families: (i) linear (n-) and branched (iso-) paraffins, (ii) naphthenes, (iii) aromatics, and (iv) n- and iso-olefins. A genetic algorithm working on molecular descriptors was used to build specific CN models for each of these classes. The predictive models return CN values roughly in the range from 0 to 100, which is in line with the definition of CN, with average absolute deviations similar to the experimental reproducibility (3−5 points).

Prediction of the Cetane Number of Diesel Compounds Using the Quantitative Structure Property Relationship

The QSPR problem for cetane numbers of hydrocarbons, a key property of oil fuels, was considered for the first time. Based on the approach developed, calculations have been carried out and relations derived for prediction of the cetane numbers of alkanes and cycloalkanes. Results of cetane number calculations for 180 unknown and non studied hydrocarbons are presented.

Cetane numbers of hydrocarbons: calculations using optimal topological indices

Entries of the topological distance matrix are shown to be functions of entries of the reduced distance matrix, which has a smaller size. The latter entries are expressed through a minimum number m of independent parameters (m ≤ 2n − 3). The expanded distance matrices, whose sum constitutes the reduced matrix, are defined. The reduced vectors have lower degeneracy than the corresponding vectors proposed by Randic as molecular codes. Nondegenerate sets of reduced-matrix entries are proposed as molecular codes.

I. V. Chuvaeva

Papers

Cetane numbers of hydrocarbons: calculations using optimal topological indices

Reduced matrix of topological distances with a minimum number of independent parameters: distance vectors and molecular codes

Method of inverse functions for solution of structure-property relationship problems

Cetane numbers of hydrocarbons as a function of their molecular structure

Information Significance of Topological Indices