Abstract Scope |
Organic molecules, known as dyes, which can absorb and emit light, have various potential applications, such as biomedical imaging, organic photovoltaics, non-linear optics, and quantum information systems. These applications are controlled by dye properties, including extinction coefficient, transition dipole moment, and aggregation ability. Dye aggregate networks via deoxyribonucleic acid (DNA) templating exhibit exciton delocalization, energy transport, and fluorescence emission. DNA nanotechnology provides scaffolding upon which dyes attach in an aqueous environment. In order to control the process and optimize the properties, we have combined machine learning and multiscale modeling to identify ideal dye candidates and reveal their dye aggregate-DNA interactions and the dye orientations. We found that those structural features have a strong impact on the resultant performance of the DNA-templated dye aggregates. The computational results were also validated with experimental observations. |