Harry Ramanantoanina from the Institute of Nuclear Chemistry (Johannes Gutenberg University Mainz) will give a lecture entitled “Structure-and-Property Relationship – Tunable Photoluminescence Driven by Counterions Binding in Eu2+-organometallics ” on the February 18, 2020 at the Institute for Analytical Sciences. (free attending. 11 am – seminar room)

Theoretical studies nowadays play an important role in chemistry research through an in-depth evaluation of the electronic structures and characterising photoluminescence properties lanthanide materials. Theoretical models conventionally rely on simple Cartesian coordinates as input. Some models use parameters to reproduce experimental data. But, these models are not really suitable for prediction purpose, characterised by the mutatis mutandis algorithm in which parameters are simply adjusted from one system to another. Additionally, some models use very elaborative theoretical grounds (first principles methods), willing to evaluate the quantum physical properties of electrons and nuclei without empirical data. But, these models are often heavy and demand huge amount of computational time and resources. Therefore, we develop an alternative approach, in which the parameters that are defined in the semi-empirical methods are determined from first principles Density-Functional Theory (DFT) calculation, within the framework of the Ligand-Field DFT (LFDFT) methodology. In this presentation, we develop a formalism, purely based on atomic structure, within which to predict the 4f – 5d photoluminescence in organometallic compounds of lanthanide Eu2+ ion. The electronic excitation and emission spectra are calculated with remarkable agreements with the experiments, shedding light on the structure-and-property relationship, which in particular will have a great value in the preparation and engineering of organometallic materials with Eu2+ ion. Our results eventually open up the possibility to address complex electronic structure problems by means of a computational chemistry tool (LFDFT) at much-reduced computational time and resources