Login / Signup

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

Fausto Díaz-SánchezMiguel Angel García-CastroMaría Patricia Amador-RamírezDiego Espinosa-MoralesJenaro Leocadio Varela-Caselis
Published in: ACS omega (2023)
Experimentally, the standard molar enthalpy of formation in the crystalline phase at 298.15 K, Δ f H m °(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, Δ f H m °(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 R 2 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.
Keyphrases
  • machine learning
  • electronic health record
  • deep learning
  • big data
  • risk assessment
  • neural network