Multivariate statistical analysis approach to investigate the thermodynamic quantities of the benign alternative fuel

Abstract

In order to extract meaningful interpretation from the large data and provide their value to the application areas, chemical data analysis has become a serious challenge in the development and applications of new protocols, technique and methodologies for the mathematical modelling communities and other data science societies. Therefore, in the present work a rapid and robust box-and-whisker plot and multivariate principal component statistical techniques (PCA) are being proposed for the evaluations of the thermodynamic molecular properties data of the benign fuel structures. We observed that, the box-and-whisker plot technique successfully explored all of the thermochemical molecular properties precisely, and described symmetrical distribution of the data along the median values with respect to the rise in temperature. Moreover, applying the PCA technique, the score-plots of PCs diagnosed the peculiar molecular properties variations after a certain peak of temperature with descendant variation in the statistical parameters. Furthermore, PCA parameters not only segregated the thermodynamic properties of propanol and butanol but also, their variations with the temperature. Thus, we concluded that, Box-whisker and PCA statistical techniques are robust and rapid method for the assessment and evaluation of the large molecular thermodynamic quantities data.