Resumen: Data-driven materials discovery has become increasingly important in identifying materials that exhibit specific, desirable properties from a vast chemical search space. Synergic prediction and experimental validation are needed to accelerate scientific advances related to critical societal applications. A design-to-device study that uses high-throughput screens with algorithmic encodings of structure–property relationships is reported to identify new materials with panchromatic optical absorption, whose photovoltaic device applications are then experimentally verified. The data-mining methods source 9431 dye candidates, which are auto-generated from the literature using a custom text-mining tool. These candidates are sifted via a data-mining workflow that is tailored to identify optimal combinations of organic dyes that have complementary optical absorption properties such that they can harvest all available sunlight when acting as co-sensitizers for dye-sensitized solar cells (DSSCs). Six promising dye combinations are shortlisted for device testing, whereupon one dye combination yields co-sensitized DSSCs with power conversion efficiencies comparable to those of the high-performance, organometallic dye, N719. These results demonstrate how data-driven molecular engineering can accelerate materials discovery for panchromatic photovoltaic or other applications. Idioma: Inglés DOI: 10.1002/aenm.201802820 Año: 2018 Publicado en: ADVANCED ENERGY MATERIALS 9, 5 (2018), 1802820 [10 pp] ISSN: 1614-6832 Factor impacto JCR: 24.884 (2018) Categ. JCR: CHEMISTRY, PHYSICAL rank: 3 / 148 = 0.02 (2018) - Q1 - T1 Categ. JCR: ENERGY & FUELS rank: 4 / 103 = 0.039 (2018) - Q1 - T1 Categ. JCR: PHYSICS, CONDENSED MATTER rank: 4 / 68 = 0.059 (2018) - Q1 - T1 Categ. JCR: PHYSICS, APPLIED rank: 4 / 148 = 0.027 (2018) - Q1 - T1 Categ. JCR: MATERIALS SCIENCE, MULTIDISCIPLINARY rank: 6 / 293 = 0.02 (2018) - Q1 - T1 Factor impacto SCIMAGO: 8.9 - Renewable Energy, Sustainability and the Environment (Q1) - Materials Science (miscellaneous) (Q1)