Predicting the photocurrent–composition dependence in organic solar cells
Xabier Rodríguez‐Martínez, Enrique Pascual‐San‐José, Zhuping Fei, Martin Heeney, Roger Guimerà, Mariano Campoy‐Quiles
Abstract
High-throughput experimental screening and machine-learning algorithms are implemented in a synergic workflow to predict the photocurrent phase space of organic photovoltaic blends. We identify accurate models employing only the materials band gaps.
Topics & Concepts
PhotocurrentPhotovoltaic systemOrganic solar cellWorkflowMaterials scienceComputer scienceThroughputOptoelectronicsCurse of dimensionalityBiological systemEnvironmental scienceArtificial intelligenceEngineeringElectrical engineeringWirelessTelecommunicationsBiologyDatabaseOrganic Electronics and PhotovoltaicsMachine Learning in Materials ScienceConducting polymers and applications