Artificial Neural Network-Group Contribution Method for Predicting Standard Enthalpy of Formation in the Solid State: C–H, C–H–O, C–H–N, and C–H–N–O Compounds

Abstract

In this work, an artificial neural network-group contribution model is developed to predict the standard enthalpy of formation in the solid (crystal) state of pure compounds. Several classes of hydrocarbon compounds CH, oxygenated compounds CHO, nitrogen compounds CHN, and energetic compounds CHNO are investigated to propose a comprehensive and predictive model. The new model is developed and tested for 1222 organic compounds containing complex molecular structures. The performance of the new model has been compared with previous work and is shown to be far more accurate. The obtained results show an average absolute deviation of $$9.33 \,\hbox {kJ}{\cdot }\hbox {mol}^{-1}$$ and a coefficient of determination of 0.9972 for the experimental values.