Machines cannot directly interpret molecular structure. Therefore, it is necessary to represent molecules and their structure in a machine-readable format. Choosing an appropriate representation is crucial to achieving accurate and interpretable models. We examined several methods for representing molecules in this task (Figure ). The simplest such approaches represent a molecule with a binary value (one-hot encoding, OHE) or with values corresponding to material properties. OHE encodes the presence of a molecule in a data point as a binary (truefalse) bit in a vector wherein the position of each bit corresponds to a unique molecule, but provides no information about the identity or properties. When representing molecules simply with their material properties, we chose energetic quantities that are known to be relevant in OPV applications: HOMO and LUMO energy levels, the HOMO-LUMO energy gap (E g HL ), and the optical excitation gap (Eg opt ). However, these descriptors still lack any information about molecular structure, which is relevant to solubility, solid-state packing and microstructure. Some information about molecular structure and physical properties can be encoded using Mordred descriptors, a set of computed numerical values describing two-and three-dimensional molecular properties, such as constitutional, topological, and electronic features. Alternatively, molecules can be decomposed into substructures, or fragments, which are then encoded as arrays. Extended-connectivity fingerprints (ECFP) effectively capture local structural information and are a common cheminformatics tool for modeling structure-activity relationships and calculating structural similarity. ECFP breaks down molecular structures into circular topological fingerprints around each atom up to a set maximum radius and hashes the presence or absence of the substructure into a bit vector of set lengthsimilar to OHE but for substructures. ECFP includes additional atomic characteristics including "heavy" atom count, valence minus the number of hydrogens, atomic number, atomic mass, atomic charge, the number of implicit and explicit hydrogens, and whether the atom is part of a ring. BRICS decomposes molecules into fragments of varying size based on common retrosynthetic and drug-like substructures, which are then encoded as arrays of varying length. This representation makes it possible to identify common substructures and analyze their impact on the overall molecular properties.