fuelcell-ner-re

UPC-HUB/fuelcell-ner-re

fuelcell-ner-re is a machine learning model from UPC-HUB. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for allennlp. The card lists the license as mit.

Named entity recognition (NER) and relation extraction (RE) model for oxygen reduction reaction (ORR) catalyst literature in fuel cells.

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Public

Updated May 12, 2026

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2.5 GB

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At a glance

Library: allennlp
License: mit
Access: Public
Created: May 12, 2026
Updated: May 12, 2026
SHA: 62f55fed

Model card

From the Hugging Face model README

DyGIE++ Fuel Cell NER/RE Model

Named entity recognition (NER) and relation extraction (RE) model for oxygen reduction reaction (ORR) catalyst literature in fuel cells.

Trained using DyGIE++ on manually annotated fuel cell literature using the brat annotation tool.

Paper

Information Extraction from Literature for ORR Catalyst in Fuel Cell Hein Htet, Manae Hirano, Amgad Ahmed Ali Ibrahim, Yutaka Sasaki, Ryoji Asahi Computational Materials Science, 2026

GitHub

Full pipeline (RSC scraper + this model): https://github.com/upc-hub/FuelCell-IE-Pipeline

Entity Types

Type	Description	Example
`catalyst`	ORR catalyst material	Fe1Co2-ZNT-900
`support`	Catalyst support	carbon nanotube (CNT)
`additive`	Additive	KOH
`electrolyte`	Electrolyte	Nafion
`precursors`	Precursor material	ZIF-8
`other_material`	Other materials	Pt/C
`material_reference`	Reference material	commercial Pt/C
`property`	Physical/chemical property	half-wave potential
`structure`	Material structure	microporous
`process`	Synthesis/treatment process	pyrolysis
`condition`	Experimental condition	900 °C
`value`	Numerical value with unit	0.847 V

Relation Types

Type	Description
`related_to`	General relationship between entities
`equivalent`	Material equivalence (e.g. abbreviation ↔ full name)

Usage

See the GitHub repository for predict.py which downloads this model automatically.

git clone https://github.com/upc-hub/FuelCell-IE-Pipeline.git
cd FuelCell-IE-Pipeline
conda env create -f environment.yml
conda activate dygiepp
python predict.py --input article.txt --output results/

Citation

@article{htet2026fuelcell,
  title   = {Information Extraction from Literature for ORR Catalyst in Fuel Cell},
  author  = {Hein Htet and Manae Hirano and Amgad Ahmed Ali Ibrahim
             and Yutaka Sasaki and Ryoji Asahi},
  journal = {Computational Materials Science},
  year    = {2026}
}

Library: allennlp
License: mit
Languages: en
Created: May 12, 2026
Updated: May 12, 2026