Experimental Determination of the Standard Enthalpy of Formation of Trimellitic Acid and Its Prediction by Supervised Learning.

The standard molar enthalpy of formation for trimellitic acid (TMAc) in the crystalline phase at 298.15 K, ΔfHm°(cr), was calculated experimentally from the enthalpy of combustion through combustion calorimetry experiments. Likewise, the standard molar enthalpy of sublimation was determined from the standard molar enthalpy of fusion and from the standard molar enthalpy of vaporization from differential scanning calorimetry and thermogravimetry, respectively. Subsequently, the standard molar enthalpies of formation in the gas-phase at 298.15 K, ΔfHm°(g), were calculated. The enthalpies of formation for TMAc, hemimellitic, and trimesic acids were predicted using multiple linear regression (MLR) with a nonreplacement evaluation technique. MLR was applied to the data set that allowed estimating these thermochemical properties with an R2 greater than 0.99. This model was used to compare the predicted and experimental results for benzene carboxylic acids.

7-Methoxy-4-methylcoumarin: Standard Molar Enthalpy of Formation Prediction in the Gas Phase Using Machine Learning and Its Comparison to the Experimental Data.

Experimentally, the standard molar enthalpy of formation in the crystalline phase at 298.15 K, ΔfHm°(cr) for 7-methoxy-4-methylcoumarin (7M4MC) was calculated by traditional linear regression, which was obtained by combustion calorimetry. Similarly, the standard molar enthalpy of sublimation was determined through the standard molar enthalpy of fusion and by the standard molar enthalpy of vaporization, from differential scanning calorimetry and thermogravimetry, respectively; lately using these results, the standard molar enthalpy of formation in the gas phase was calculated at 298.15 K, ΔfHm°(g). In addition ML was used to predict the standard molar enthalpy of formation in the gas phase for the 7M4MC, constructing an experimental data set containing three kinds of functional groups: esters, coumarins, and aromatic compounds. The procedure was performed by using multiple linear regression algorithms and stochastic gradient descent with a R2 of 0.99. The obtained models were used to compare those predicted values versus experimental for coumarins, resulting in an average error rate of 9.0%. Likewise, four homodesmic reactions were proposed and predicted with the multiple linear regression algorithm of ML obtaining good results.