Organic solar cells (OSCs) represent one of the most promising technologies for accessing low-cost solar energy conversion. The active layer in OSCs affects the performance of the device, thus a proper design of photovoltaic materials is of utmost importance. Advocating the rapid and large-scale production of OSCs, computational simulations can be employed to account for both the structure and properties of photovoltaic materials.
DFT will be employed to understand the electronic structure and spectroscopic characteristics of materials. This will generate highly valuable data, that can be employed in the design of more efficient donors and acceptors. Several descriptors calculated with DFT will be correlated to the efficiency of the photovoltaic material. Data analysis will allow us to predict structural modifications to generate more efficient solar cells, using QSPR (Quantitative Structure-Property Relationships). This part of the project will use DFT calculations in Gaussian and Jaguar on Tetralith@NSC. The expected outcome is new donors and acceptors that will enter the next stage of the project.
Molecular dynamics (MD) simulations can be used to understand and predict the intermolecular interactions of donors and acceptors, and even include the effect of the solvent. MD simulations will be employed to study the macromolecular properties of the films formed between the donor and acceptor (both known and developed in the previous stage). During experiments, different solvent blends are frequently employed and the properties of the resulting films after evaporation of the solvent are essential for the performance of the material. MD simulations are a valuable tool for studying solvent evaporation and film formation. As the formation of the dried film relies on the evaporation of the solvent from a solution containing donor/acceptor molecules, solvent screening is a critical aspect that controls the nanomorphology of the materials.
We will employ GROMACS and Schrödinger (Desmond) on Tetralith@NSC.