首页|Studies from Benemerita University Autonoma of Puebla Yield New Data on Machine Learning (7-methoxy-4-methylcoumarin: Standard Molar Enthalpy of Formation Prediction In the Gas Phase Using Machine Learning and Its Comparison To the Experimental ...)
Studies from Benemerita University Autonoma of Puebla Yield New Data on Machine Learning (7-methoxy-4-methylcoumarin: Standard Molar Enthalpy of Formation Prediction In the Gas Phase Using Machine Learning and Its Comparison To the Experimental ...)
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NETL
NSTL
Amer Chemical Soc
Research findings on Machine Learning are discussed in a new report. According to news originating from Puebla, Mexico, by NewsRx correspondents, research stated, “Experimentally, the standard molar enthalpy of formation in the crystalline phase at 298.15 K, Delta H-f(m)degrees(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, Delta H-f(m)degrees(g).” Funders for this research include Consejo Nacional de Ciencia y Tecnologia (CONACyT), Consejo Nacional de Ciencia y Tecnologia (CONACyT), VIEP-BUAP. Our news journalists obtained a quote from the research from the Benemerita University Autonoma of Puebla, “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%.”
PueblaMexicoNorth and Central AmericaCyborgsEmerging TechnologiesMachine LearningBenemerita University Autonoma of Puebla
NETL
NSTL
Amer Chemical Soc
