Prediction of Standard Enthalpies of Formation Based on Hydrocarbon Molecular Descriptors and Active Subspace Methodology

Abstract

Standard enthalpy of formation is an important fuel thermochemical property for energy balance calculation and equilibrium dynamics determination in combustion reactions. In this study, an approach combining the quantitative structure–property relation and the active subspace method was applied to predict the standard enthalpies of formation of different hydrocarbon classes, including alkanes, cycloalkanes, alkenes, alkynes, and aromatics. The standard enthalpies of formation in a database of 1020 hydrocarbons were predicted by a one-dimensional active subspace model, with 902 molecule topological indices being used as input descriptors. The correlation coefficient between the measured and predicted values was 0.99, and the average absolute error was 6.74 kJ/mol. The sensitivity of the prediction output to each descriptor was further evaluated, which enables us to build simplified models by only considering the most representative descriptors. Also, to assess the influences of model simplification on the prediction performance, the relation between the descriptor number and the prediction accuracy was explored. It was observed that simplified but well-predictive models can be established when the top 10 influential descriptors were selected for model building, and the correlation coefficient between the predicted and measured standard enthalpies of formation was as high as 0.96.

New Method of NPOH Equation-Based to Estimate the Physicochemical Properties of Noncyclic Alkanes

“…Until now, people have gradually established many valuable estimation methods, 1−95 such as (i) group-contribution (GC) methods, 4,9,18,37,54,55,70,86 (ii) estimating one physicochemical p r o p e r t y f r o m t h a t o f o t h e r c o mpounds, 1,2,8, 14,16,17,19,20,22,24,36,39,45,48,57,[64][65][66]74,75,78,85,89 (iii) l i q u i d e q u a t i o n s o f s t a t e s ( E o S ) -b a s e d m e t hods, 3,5,7,11,13,21,25,26,31,34,40,41,46,47,49−51,53,61,88,90−92 and (iv) q u a n t i t a t i v e s t r u c t u r e − p r o p e r t y r e l a t i o n s h i p s (QSPRs). 15,30,38,42,44,52,56,59,60,[67][68][69][71][72][73]77,[80][81][82]87,…”

“…Due to the huge number of isomers of alkanes, determining the physicochemical properties of all compounds experimentally is an impossible task, so it is very meaningful to establish an estimation method. Until now, people have gradually established many valuable estimation methods, − such as (i) group-contribution (GC) methods, ,,,,,,, (ii) estimating one physicochemical property from that of other compounds, <...…”

Weaving a Network of Reliable Thermochemistry around Lignin Building Blocks: Methoxy-Phenols and Methoxy-Benzaldehydes

“…It correlates strongly with the molecular structural features, e.g., the number and order of chemical bonds and the molecular size. 6 The correlation of enthalpies of the formation of lignin, constituting monomers with their molecular structures, can therefore open a window of opportunity for reliably predicting the energetics of large lignin building blocks. Such a prediction is crucial for optimizing the lignin conversion lignin into valueadding and sustainable platform chemicals.…”

“…The standard molar enthalpy of formation reflects an overall result of breaking and the formation of chemical bonds. It correlates strongly with the molecular structural features, e.g., the number and order of chemical bonds and the molecular size . The correlation of enthalpies of the formation of lignin, constituting monomers with their molecular structures, can therefore open a window of opportunity for reliably predicting the energetics of large lignin building blocks.…”

Topological descriptors, entropy measures and NMR spectral predictions for nanoporous graphenes with [14]annulene pores

“…Quantitative structure activity/property relations (QSAR/QSPR) techniques seek to obtain mathematical expression to predict the properties of such materials using parameters derived from graph theory and other methods [29][30][31][32][33][34][35][36][37][38][39]. Topological index (TI), is one such structural descriptor which has exhibited considerable promise in recent years [19,[40][41][42][43].…”