Insights from principal component analysis applied to Py-GCMS study of Indian coals and their solvent extracted clean coal products

Abstract The present work aims at studying five Indian coals and their solvent extracted clean coal products using Py-GCMS analysis correlating the characterization data theoretical principal component analysis. pyrolysis of original super were classified as mono-, di- tri-aromatics, while other prominent that obtained included cycloalkanes, n -alkanes, alkenes ranging from C 10 –C 29 . is a dimensionality reduction technique reduced number input variables in dataset gave inferences on relative composition constituent compounds functional groups structural insights based scores loading plots which consistent with experimental observations. ATR-FTIR studies confirmed concentration ash presence aromatics. spectra led to conclusion behaved similarly for both coking non-coking high aromatic concentrations compared raw coal. Neyveli lignite was found show some similarity coals, whereas showed within themselves but not samples confirming selective action e,N solubilizing polycondensed structures samples.