Setting up computational approaches enabling the correct prediction of the photophysical properties of rhodamine B (RB) derivatives and their aggregates (referred to as dimers here) is of fundamental importance to rationally drive the design of novel systems of applicative relevance, such as artificial light-harvesting nanosystems. Currently, approaches rooted in time-dependent density functional theory (TD-DFT), which are appealing for their relatively low computational cost, nonetheless have limitations in terms of accuracy, especially while considering RB dimeric species. In this work, we investigated the performances of optimally tuned range-separated hybrid functionals for describing the excited states of RB and its H dimer, focusing on dimeric charge-transfer (CT) states. We compared different optimal-tuning (OT) procedures including or not solvent screening. The results show that the properties of CT states, such as their CT extent, brightness and relative energy ordering, are crucially affected by the Hartree-Fock exchange amount dictated by OT, which is in turn driven by the chosen asymptotic behavior. Finally, to understand the dissimilar pictures provided for the CT states by different tuning approaches, we performed an extensive analysis aimed at elucidating how CT states are affected by range-separation parameters. As a result, a simple procedure is finally provided for easily achieving a unique functional to be applied on both monomer and dimers, its current limitations are highlighted and possible perspectives for future development are envisaged.Optimally tuned range-separated hybrid functionals are employed to study the excited states of rhodamine B and its H dimer. The impact of range-separation parameters on the description of dimeric charge-transfer states is extensively analyzed.
Fanciullo, G., Adamo, C., Rivalta, I., Ciofini, I. (2024). Optimal-tuning of range-separated density functionals to describe the optical and photophysical properties of rhodamine B dimers. PHYSICAL CHEMISTRY CHEMICAL PHYSICS, 26, 23920-23933 [10.1039/D4CP02147A].
Optimal-tuning of range-separated density functionals to describe the optical and photophysical properties of rhodamine B dimers
Giacomo Fanciullo;Ivan Rivalta;
2024
Abstract
Setting up computational approaches enabling the correct prediction of the photophysical properties of rhodamine B (RB) derivatives and their aggregates (referred to as dimers here) is of fundamental importance to rationally drive the design of novel systems of applicative relevance, such as artificial light-harvesting nanosystems. Currently, approaches rooted in time-dependent density functional theory (TD-DFT), which are appealing for their relatively low computational cost, nonetheless have limitations in terms of accuracy, especially while considering RB dimeric species. In this work, we investigated the performances of optimally tuned range-separated hybrid functionals for describing the excited states of RB and its H dimer, focusing on dimeric charge-transfer (CT) states. We compared different optimal-tuning (OT) procedures including or not solvent screening. The results show that the properties of CT states, such as their CT extent, brightness and relative energy ordering, are crucially affected by the Hartree-Fock exchange amount dictated by OT, which is in turn driven by the chosen asymptotic behavior. Finally, to understand the dissimilar pictures provided for the CT states by different tuning approaches, we performed an extensive analysis aimed at elucidating how CT states are affected by range-separation parameters. As a result, a simple procedure is finally provided for easily achieving a unique functional to be applied on both monomer and dimers, its current limitations are highlighted and possible perspectives for future development are envisaged.Optimally tuned range-separated hybrid functionals are employed to study the excited states of rhodamine B and its H dimer. The impact of range-separation parameters on the description of dimeric charge-transfer states is extensively analyzed.File | Dimensione | Formato | |
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