FC-CoMIcs (Fuel Cell-Corpus for Materials Informatics)

We provide automated knowledge extractions from scientific literature to support data-driven materials discovery. This corpus, FC-CoMIcs, contains semantic annotations automatically extracted from approximately 1,000 research articles focused on Oxygen Reduction Reaction (ORR) catalysts for fuel cells.

The data was generated using a specialized DyGIE++ model fine-tuned on MatSciBERT, specifically trained to recognize complex materials, properties, and relationships in the fuel cell domain. FC-CoMIcs contributes to the advancement of Materials Informatics (MI), particularly for polymer electrolyte fuel cells, by providing structured data ready for Knowledge Graph construction and statistical analysis.

The dataset consists of:
1. DOI Index: A mapping file linking our internal IDs to the original article Digital Object Identifiers (DOIs).
2. Structured JSON Extractions: Machine-generated files containing recognized entities (e.g., catalysts, precursors, operating conditions) and their semantic relationships.
3. Interactive Knowledge Maps: Visual representations of the extracted relations for each article, generated via the Pyvis library for rapid human exploration.

Note on Accessibility: To comply with publisher copyright and funding guidelines, the original full-text articles are not redistributed. Researchers can use the provided DOIs to link these high-fidelity semantic extractions back to the source literature.