A database of thermally activated delayed fluorescent molecules auto-generated from scientific literature with ChemDataExtractor.

A database of thermally activated delayed fluorescent (TADF) molecules was automatically generated from the scientific literature. It consists of 25,482 data records with an overall precision of 82%. Among these, 5,349 records have chemical names in the form of SMILES strings which are represented with 91% accuracy; these are grouped in a subsidiary database. Each data record contains one of the following four properties: maximum emission wavelength (λEM), photoluminescence quantum yield (PLQY), singlet-triplet energy splitting (ΔEST), and delayed lifetime (τD). The databases were created through text mining using ChemDataExtractor, a chemistry-aware natural-language-processing toolkit, which has been adapted for TADF research. The text-mined corpus consisted of 2,733 papers from the Royal Society of Chemistry and Elsevier. To the best of our knowledge, these databases are the first databases that have been auto-generated for TADF molecules from existing publications. The databases have been publicly released for experimental and computational applications in the TADF research field.

Description

Acknowledgements: J.M.C. is grateful for the BASF/Royal Academy of Engineering Research Chair in Data-Driven Molecular Engineering of Functional Materials, which is partly supported by the STFC via the ISIS Neutron and Muon Source. D.H. is thankful to the Cambridge Commonwealth, European and International Trust and the China Scholarship Council for a PhD scholarship. The authors thank the Argonne Leadership Computing Facility, which is a DOE Office of Science Facility, for use of its research resources, under contract No. DE-AC02-06CH11357.

Funder: China Scholarship Council (CSC); doi: https://doi.org/10.13039/501100004543

Keywords

4605 Data Management and Data Science, 46 Information and Computing Sciences, 34 Chemical Sciences, Networking and Information Technology R&D (NITRD), Generic health relevance

Journal Title

Sci Data

Journal ISSN

2052-4463
2052-4463

Volume Title

11

Publisher

Springer Nature

Publisher DOI

https://doi.org/10.1038/s41597-023-02897-3

Rights and licensing

Except where otherwised noted, this item's license is described as Attribution 4.0 International

Sponsorship

Royal Academy of Engineering (RCSRF1819\7\10)

Collections

Jisc Publications Router