Application of principal-component analysis to the interpretation of coal tar physico-chemical properties

[Display omitted] •Non-destructively identifying for organics in coal tar by molecular simulations.•Constituting three principal components from 15 factors by principle-component analysis.•Establishing an electronic-scale comprehension for the correlation of coal tar chemical properties. Coal tars, mixtures of heavy polyaromatic hydrocarbons (PAHs) by-produced in the coking processes of coals, are used as resources for further refining, burnt for carbon black, or just disposed in landfills. Direct application of rich PAHs in coal tars in renewable applications such as photovoltaic devices will not only reduce the carbon emission and waste production, but also upgrade the tar-to-product chain with higher additive value. Decoding the component of coal tars and their optical properties is the basis to apply these complex PAHs in optical devices. Herein, we perform density functional theory (DFT) simulations and time-dependent DFT (TDDFT) simulations of all organic molecules in coal tar, calculating their molecular dipole moment, optical gap, fundamental gap, Urbach tail energy, vibrational spectrum, etc. Using Principal-component analysis (PCA) with maximum variance criterion, we decouple three principal components associated with structural, electronic, and vibrational properties. Through comparison between simulation results and experiments, an electronic-scale comprehension for the correlation of properties can be convinced, contributing to the interpretation of coal tar.