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The ability to auto-generate databases of optical properties holds great prospects in data-driven materials discovery for optoelectronic applications. We present a cognate set of experimental and computational data that describes key features of optical absorption spectra. This includes an auto-generated database of 18,309 records of experimentally determined UV/vis absorption maxima,  λ   max  , and associated extinction coefficients,  ϵ , where present. This database was produced using the text-mining toolkit, ChemDataExtractor, on 402,034 scientific documents. High-throughput electronic-structure calculations using fast (simplified Tamm-Dancoff approach) and traditional (time-dependent) density functional theory were executed to predict  λ   max   and oscillation strengths,  f  (related to ϵ) for a subset of validated compounds. Paired quantities of these computational and experimental data show strong correlations in  λ   max  ,  f  and  ϵ , laying the path for reliable  in silico  calculations of additional optical properties. The total dataset of 8,488 unique compounds and a subset of 5,380 compounds with experimental and computational data, are available in MongoDB, CSV and JSON formats. These can be queried using Python, R, Java, and MATLAB, for data-driven optoelectronic materials discovery.

Comparative dataset of experimental and computational attributes of UV/vis absorption spectra