tmQMg* Dataset: Excited State Properties of 74k Transition Metal Complexes

The application of machine learning approaches to meaningful problems in chemistry and materials science is still challenged by the limited availability of data. In order to close this gap, we report the tmQMg* dataset, which provides excited state properties for 74k mononuclear transition metal complexes extracted from the Cambridge Structural Database. All properties were computed at the TD-DFT wB97xd/def2SVP level of theory. The strongest electron excitations in the ultraviolet, visible, and near-infrared ranges are included, together with the wavelengths and intensities of the first 30 excited states. Further, natural transition orbitals were computed for the strongest excitation in the visible range to determine the nature of the associated charge transfer. By computing the TD-DFT spectra in both gas phase and acetone, we quantified solvatochromic effects, which are also provided with the dataset, in terms of both wavelength shifts and intensity changes. The tmQMg* dataset will enable the development of discriminative and generative AI models with respect to absorption spectra, charge transfer character, and solvatochromism, enabling novel advances in the field of transition metal photochemistry.