Machine learning the frontier orbital energies of SubPc based triads

Organic photovoltaic devices are promising candidates for efficient energy harvesting from sunlight. Designing new dye molecules suitable for such devices is a challenging task restricted by the rapid increase of computational cost with system size. Solar cell material properties are closely related to the electronic structure of the dye, and an effective molecular orbital energy screening method for a family of dyes is therefore desired. In this work, a machine learning approach is used to sort through the chemical space of peripheral double-substituted boron-Subphthalocyanine dyes. A database of 12,102 PM6 optimized structures was built and for each of the structures time-dependent density functional theory (LC-[Formula: see text]HPBE/6-31+G(d)) calculations were performed. We investigated the changes of the molecular orbital energies of the molecular orbitals related to reduction and oxidation of the compounds. With the Electrotopological-state index moleculear representation all the tested algorithms, Support Vector Machine, Random Forest Regression, Neural Network, and Simple Linear Regression, captured the calculated frontier orbital energies with a prediction root-mean-square-error in the order of 0.05 eV. Finally, frontier orbital energies were predicted for more than 40,000 new structures by the trained Support Vector Machine algorithm. Compared to the parent boron-Subphthalocyanine structure, 237 and 132 functionalized dyes were predicted to have upshifted molecular orbital energies using the Electrotopological-state index and OneHot encoding feature vector, respectively. Out of 27 investigated donor and acceptor ligands, the acetamide and hydroxyl ligands gave rise to the desired increase in frontier molecular orbital energy.

Fusing Thienyl with N-Annulated Perylene Dyes and Photovoltaic Parameters for Dye-Sensitized Solar Cells

Due to the role of dyes in dye-sensitized solar cells (DSSCs), designing novel dye sensitizers is an effective strategy to improve the power conversion efficiency. To this end, the fundamental issue is understanding the sensitizer's trilateral relationship among its molecular structure, optoelectronic properties, and photovoltaic performance. Considering the good performance of N-annulated perlyene dye sensitizers, the geometries, electronic structures, and excitations of the selected representative organic dye sensitizers C276, C277, and C278 as well as dyes adsorbed on TiO₂ clusters were calculated in order to investigate the relationship between molecular structures and properties. It was found that fusing thienyl to N-annulated perlyene can elevate the highest occupied molecular orbital (HOMO) energy, reduce the orbital energy gap, increase the density of states, expand the HOMO to the benzothiadiazole moiety, enhance the charge transfer excitation, elongate the fluorescence lifetime, amplify the light harvesting efficiency, and induce a red-shift of the absorption spectra. The transition configurations and molecular orbitals of the dye-adsorbed systems support that the electron injection in DSSCs based on these dyes is a fast mode. Based on extensive analysis of the electronic structures and excitation properties of these dye sensitizers and the dye-adsorbed systems, we present new quantities as open-circuit voltage and short-circuit current density descriptors that celebrate the quantitative bridge between the photovoltaic parameters and the electronic structure-related properties in order to expose the relationship between properties and performance. The results of this work are critical for the design of novel dye sensitizers for solar cells.