The radius of the TC was set to 2. This value was selected because IR spectra are particularly sensitive to functional groups. This resulted in high TCs even when the long alkyl chain lengths differed. Principal component analysis (PCA) reduces the dimensionality of large datasets by transforming potentially correlated variables into a smaller set of uncorrelated variables, known as principal components, which retain most of the information from the original data 21 . For clustering, the k-means algorithm was employed, with the number of clusters set to 7 22 . Both were implemented using scikit-learn 2316c .