Calculating the Theoretical Octane Number for a Number of Petroleum Derivatives Using Quantum Mechanical Methods AM1 and PM3
DOI:
https://doi.org/10.70135/seejph.vi.962Keywords:
Social Medical Systems, Healthcare Security, IoT-23 Analysis, Machine Learning, Deep LearningAbstract
This research included calculating a number of physical variables that affect the octane number using semi-empirical methods of quantum mechanics, including AM1, PM3, hardness (η), electron-chemical potential (µ), spherical electrophilic index (W, ∆G, ∆H, ∆S, ∆E and dipole moment). Multiple statistical analyses were used to find the relationship between the calculated variables and the practical value of the octane number and then calculate the octane number theoretically. Through the four-way statistical analysis, we obtained the best correlation coefficient (R2) for the variables (HOMO + η + ∆S + ∆E) calculated by the PM3 method (R2 = 0.998) and the correlation coefficient values for the variables (HOMO + η + W+ µ) calculated by the AM1 method (R2 = 0.980). Through the single and multiple statistical analysis, the most influential variables on the octane number values are (HOMO, LOMO).
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