Supplemetary Data for the article: Machine-learning identified molecular fragments responsible for infrared emission features of polycyclic aromatic hydrocarbons

This is a set of Supplementary materials for the article 'Machine-learning identified molecular fragments responsible for infrared emission features of polycyclic aromatic hydrocarbons', by Meng et al.

Supplementary_Data_I.pdf contains an extensive table spanning 36 pages that lists the top-10 molecular fragments accountable for the spectral bands between 2.761 and 1172.745 μm. To access this table, hyperlinks within the document can be used for navigation.

Supplementary_Data_II.pdf comprises a large table that encompasses 10,691 pages, including the top-100 molecular fragments responsible for the spectral bands between 2.761 and 1172.745 μm. Navigation through the hyperlinks enables access to this table.

Supplementary_Data_III.csv encompasses the chemical formulas, number of unpaired valence electrons, spin multiplicities, xyz data, and SMILES strings of the PAHs carrying the additional spectra.

Supplementary_data_IV.zip includes the input and output datasets along with the ML code. The code script is written in Python 3.7, and is supported by the following libraries: sklearn, json, numpy, and pandas.

Supplementary_Information.pdf contains the evidence supporting the choice of the cutoff radius, as well as the figures of the count of the molecules in the dataset, the FI with changing datasets and hyperparameters, of cross-validation, and of UIE bands and emission features of four SH PAHs.