Periodic Reporting for period 1 - Full-Fission (Singlet fission in fullerene-based single-material organic solar cells)
Reporting period: 2024-04-04 to 2026-04-03
Solar energy is one of the most promising ways to produce clean and renewable electricity. Today’s solar panels are mostly made of silicon and can reach efficiencies of up to 26%. However, making them is expensive and can harm the environment. A greener and cheaper alternative is to use organic materials instead of silicon. Organic solar cells (OSCs) are especially interesting because they are flexible, lightweight, and easy to produce. Within this field, single-material organic solar cells (SMOSCs) — where the two key components are part of the same molecule — offer even more advantages: easier manufacturing, better stability, and more consistent performance. At the same time, traditional solar cells face a natural efficiency limit of around 30%, known as the Shockley–Queisser limit. A way to overcome this is through singlet fission, a special process where one absorbed light particle (photon) can create two energy units instead of one, potentially doubling the efficiency. The Full-Fission project brings these ideas together. The goal is to develop new organic solar cells that include special molecules (fullerenes) combined with materials capable of singlet fission. To achieve this, the project combines computer simulations, chemical synthesis, and the building of working solar devices. First, new candidate molecules for singlet fission are identified using computational chemistry and machine learning techniques. Next, these molecules are prepared and chemically connected to fullerenes. Finally, the new materials are tested in solar cells to see how well they work. The overall aim is to create next-generation organic solar panels that are efficient, low-cost, and environmentally friendly.
The Full-Fission action was conceived as an interdisciplinary project combining computational design, chemical synthesis, and the implementation of donor–acceptor (D–A) fullerene dyads and donor–acceptor–donor (D–A–D) triads incorporating singlet fission (SF) chromophores as donor units. The project was structured around three main objectives. The first objective focused on the computational discovery and design of novel SF chromophores that fulfil the energy matching conditions (EMC) required for efficient singlet fission. To this end, large libraries of benzannulated polycyclic conjugated hydrocarbons (PCHs), based on ground-state antiaromatic and biradical scaffolds, were screened in silicon. To accelerate the screening process, a user-friendly machine learning (ML) protocol was developed to identify EMC-compliant molecules from extensive PCH libraries. This strategy led to the identification of three promising hit libraries, based on biphenylene, dibenzopentalene, and dibenzoindacene cores. These hits were further filtered according to several criteria, including their computed T₁ and T2 energies (via TD-DFT), LUMO levels, and synthetic feasibility, resulting in reduced libraries of lead compounds. The synthesis of these leads is currently underway. In parallel, the project explored the influence of molecular topology on the ground-state and T₁ energies of cata-condensed hexacene isomers. The findings from this study offer practical guidelines for tuning triplet energies through π-extension strategies. Additionally, computational studies were initiated to determine the optimal spatial arrangement of donor units on fullerene bis-adducts, with the goal of enhancing charge transfer (CT) efficiency from triplet excitons. These insights will be key in guiding the molecular design of the D–A dyads and D–A–D triads planned for synthesis. Due to the early termination of the action at month 12, only the activities related to computational design were fully completed.
The most significant contribution achieved so far is the development of a simple and user-friendly computational protocol that allows researchers — including synthetic organic chemists with no prior experience in machine learning — to efficiently screen large libraries of organic molecules and predict singlet fission activity. This pipeline combines DFT-based excited-state calculations with a ML classifier, enabling the identification of EMC-compliant molecules from structurally diverse scaffolds. While previous works have already used ML techniques to identify potential SF candidates, the protocol employed here is intended to be adopted broadly by the research community. Once fully disseminated and applied to other molecular families, this approach can significantly accelerate the discovery of novel SF chromophores by other academic and industrial groups worldwide. The project has already identified promising candidates based on underexplored π-extended polycyclic systems such as dibenzopentalene and dibenzoindacene, going beyond the usual tetracene- or pentacene-based designs that dominate the literature.