Perovskite- and Dye-Sensitized Solar-Cell Device Databases Auto-generated Using ChemDataExtractor

Beard, Edward J.; Cole, Jacqueline M.

doi:10.1038/s41597-022-01355-w

Perovskite- and Dye-Sensitized Solar-Cell Device Databases Auto-generated Using ChemDataExtractor

Journal Article · Fri Jun 17 00:00:00 EDT 2022 · Scientific Data

DOI:https://doi.org/10.1038/s41597-022-01355-w· OSTI ID:2469490

Beard, Edward J. ^[1]; ^[2]

Univ. of Cambridge (United Kingdom); Science and Technology Facilities Council (STFC), Oxford (United Kingdom). Rutherford Appleton Lab., ISIS Neutron Source
Univ. of Cambridge (United Kingdom); Science and Technology Facilities Council (STFC), Oxford (United Kingdom). Rutherford Appleton Lab., ISIS Neutron Source; Argonne National Laboratory (ANL), Argonne, IL (United States)

The number of scientific publications reporting cutting-edge third-generation photovoltaic devices is increasing rapidly, owing to the pressing need to develop renewable-energy technologies that address the climate-change crisis. Consequently, the field could benefit from a central repository where photovoltaic-performance metrics, such as the power-conversion efficiency (η) are recorded. We present two automatically generated databases that contain photovoltaic properties and device material data for dye-sensitized solar cells (DSCs) and perovskite solar cells (PSCs), totalling 660,881 data entries representing 57,678 photovoltaic devices. The databases were generated by applying the text-mining toolkit ChemDataExtractor on a corpus of 25,720 articles. A multi-faceted evaluation, incorporating manual and automatic methods, was applied to ensure that the data contained therein were of the highest quality, with precision metrics ranging from 73.1% to 95.8%. The DSC database contains 475,045 entries representing 41,680 devices, and the PSC database contains 185,836 entries representing 15,818 devices. The databases are available in MongoDB and JSON formats, which can be queried in Python, R, Java and MATLAB for data-driven photovoltaic materials discovery.

View Accepted Manuscript (DOE)

Research Organization:: Argonne National Laboratory (ANL), Argonne, IL (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES)

Grant/Contract Number:: AC02-06CH11357

OSTI ID:: 2469490

Journal Information:: Scientific Data, Journal Name: Scientific Data Journal Issue: 1 Vol. 9; ISSN 2052-4463

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United States

Language:: English

References (39)

Dye-sensitized Solar Cell Database beard, edward; Cole, Jacqueline figshare https://doi.org/10.6084/m9.figshare.13516220	dataset	January 2022
Perovskite Solar Cell Database beard, edward; Cole, Jacqueline figshare https://doi.org/10.6084/m9.figshare.13516238.v1	dataset	January 2022
Data‐Driven Materials Science: Status, Challenges, and Perspectives Himanen, Lauri; Geurts, Amber; Foster, Adam Stuart Advanced Science, Vol. 6, Issue 21 https://doi.org/10.1002/advs.201900808	journal	September 2019
Design-to-Device Approach Affords Panchromatic Co-Sensitized Solar Cells Cooper, Christopher B.; Beard, Edward J.; Vázquez-Mayagoitia, Álvaro Advanced Energy Materials, Vol. 9, Issue 5 https://doi.org/10.1002/aenm.201802820	journal	December 2018
Optimizing Dyes for Dye-Sensitized Solar Cells Robertson, Neil Angewandte Chemie International Edition, Vol. 45, Issue 15 https://doi.org/10.1002/anie.200503083	journal	April 2006
Metal-Free Organic Dyes for Dye-Sensitized Solar Cells: From Structure: Property Relationships to Design Rules Mishra, Amaresh; Fischer, Markus K. R.; Bäuerle, Peter Angewandte Chemie International Edition, Vol. 48, Issue 14 https://doi.org/10.1002/anie.200804709	journal	March 2009
A Design-to-Device Pipeline for Data-Driven Materials Discovery Cole, Jacqueline M. Accounts of Chemical Research, Vol. 53, Issue 3 https://doi.org/10.1021/acs.accounts.9b00470	journal	February 2020
Materials Synthesis Insights from Scientific Literature via Text Extraction and Machine Learning Kim, Edward; Huang, Kevin; Saunders, Adam Chemistry of Materials, Vol. 29, Issue 21 https://doi.org/10.1021/acs.chemmater.7b03500	journal	October 2017
Halide Perovskite Photovoltaics: Background, Status, and Future Prospects Jena, Ajay Kumar; Kulkarni, Ashish; Miyasaka, Tsutomu Chemical Reviews, Vol. 119, Issue 5 https://doi.org/10.1021/acs.chemrev.8b00539	journal	March 2019
Cosensitization in Dye-Sensitized Solar Cells Cole, Jacqueline M.; Pepe, Giulio; Al Bahri, Othman K. Chemical Reviews, Vol. 119, Issue 12 https://doi.org/10.1021/acs.chemrev.8b00632	journal	April 2019
ChemDataExtractor 2.0: Autopopulated Ontologies for Materials Science Mavračić, Juraj; Court, Callum J.; Isazawa, Taketomo Journal of Chemical Information and Modeling, Vol. 61, Issue 9 https://doi.org/10.1021/acs.jcim.1c00446	journal	September 2021
ChemDataExtractor: A Toolkit for Automated Extraction of Chemical Information from the Scientific Literature Swain, Matthew C.; Cole, Jacqueline M. Journal of Chemical Information and Modeling, Vol. 56, Issue 10 https://doi.org/10.1021/acs.jcim.6b00207	journal	October 2016
Anchoring Groups for Dye-Sensitized Solar Cells Zhang, Lei; Cole, Jacqueline M. ACS Applied Materials & Interfaces, Vol. 7, Issue 6 https://doi.org/10.1021/am507334m	journal	February 2015
SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules Weininger, David Journal of Chemical Information and Modeling, Vol. 28, Issue 1 https://doi.org/10.1021/ci00057a005	journal	February 1988
Dye-Sensitized Solar Cells Hagfeldt, Anders; Boschloo, Gerrit; Sun, Licheng Chemical Reviews, Vol. 110, Issue 11 https://doi.org/10.1021/cr900356p	journal	November 2010
Efficient Computational Screening of Organic Polymer Photovoltaics Kanal, Ilana Y.; Owens, Steven G.; Bechtel, Jonathon S. The Journal of Physical Chemistry Letters, Vol. 4, Issue 10 https://doi.org/10.1021/jz400215j	journal	April 2013
Warming caused by cumulative carbon emissions towards the trillionth tonne Allen, Myles R.; Frame, David J.; Huntingford, Chris Nature, Vol. 458, Issue 7242 https://doi.org/10.1038/nature08019	journal	April 2009
The proportionality of global warming to cumulative carbon emissions Matthews, H. Damon; Gillett, Nathan P.; Stott, Peter A. Nature, Vol. 459, Issue 7248 https://doi.org/10.1038/nature08047	journal	June 2009
The high-throughput highway to computational materials design Curtarolo, Stefano; Hart, Gus L. W.; Nardelli, Marco Buongiorno Nature Materials, Vol. 12, Issue 3 https://doi.org/10.1038/nmat3568	journal	February 2013
New frontiers for the materials genome initiative de Pablo, Juan J.; Jackson, Nicholas E.; Webb, Michael A. npj Computational Materials, Vol. 5, Issue 1 https://doi.org/10.1038/s41524-019-0173-4	journal	April 2019
Unsupervised word embeddings capture latent knowledge from materials science literature Tshitoyan, Vahe; Dagdelen, John; Weston, Leigh Nature, Vol. 571, Issue 7763 https://doi.org/10.1038/s41586-019-1335-8	journal	July 2019
Comparative dataset of experimental and computational attributes of UV/vis absorption spectra Beard, Edward J.; Sivaraman, Ganesh; Vázquez-Mayagoitia, Álvaro Scientific Data, Vol. 6, Issue 1 https://doi.org/10.1038/s41597-019-0306-0	journal	December 2019
A database of battery materials auto-generated using ChemDataExtractor Huang, Shu; Cole, Jacqueline M. Scientific Data, Vol. 7, Issue 1 https://doi.org/10.1038/s41597-020-00602-2	journal	August 2020
Machine-learned and codified synthesis parameters of oxide materials Kim, Edward; Huang, Kevin; Tomala, Alex Scientific Data, Vol. 4, Issue 1 https://doi.org/10.1038/sdata.2017.127	journal	September 2017
Auto-generated materials database of Curie and Néel temperatures via semi-supervised relationship extraction Court, Callum J.; Cole, Jacqueline M. Scientific Data, Vol. 5, Issue 1 https://doi.org/10.1038/sdata.2018.111	journal	June 2018
Lead candidates for high-performance organic photovoltaics from high-throughput quantum chemistry – the Harvard Clean Energy Project Hachmann, Johannes; Olivares-Amaya, Roberto; Jinich, Adrian Energy Environ. Sci., Vol. 7, Issue 2 https://doi.org/10.1039/C3EE42756K	journal	January 2014
Dye aggregation in dye-sensitized solar cells Zhang, Lei; Cole, Jacqueline M. Journal of Materials Chemistry A, Vol. 5, Issue 37 https://doi.org/10.1039/C7TA05632J	journal	January 2017
Hole transporting materials for perovskite solar cells: a chemical approach Urieta-Mora, Javier; García-Benito, Inés; Molina-Ontoria, Agustín Chemical Society Reviews, Vol. 47, Issue 23 https://doi.org/10.1039/C8CS00262B	journal	January 2018
Molecular engineering strategies for fabricating efficient porphyrin-based dye-sensitized solar cells Zeng, Kaiwen; Tong, Zhangfa; Ma, Lin Energy & Environmental Science, Vol. 13, Issue 6 https://doi.org/10.1039/C9EE04200H	journal	January 2020
Commentary: The Materials Project: A materials genome approach to accelerating materials innovation Jain, Anubhav; Ong, Shyue Ping; Hautier, Geoffroy APL Materials, Vol. 1, Issue 1 https://doi.org/10.1063/1.4812323	journal	July 2013
Perspective: Materials informatics and big data: Realization of the “fourth paradigm” of science in materials science Agrawal, Ankit; Choudhary, Alok APL Materials, Vol. 4, Issue 5 https://doi.org/10.1063/1.4946894	journal	April 2016
Irreversible climate change due to carbon dioxide emissions Solomon, Susan; Plattner, Gian-Kasper; Knutti, Reto Proceedings of the National Academy of Sciences, Vol. 106, Issue 6 https://doi.org/10.1073/pnas.0812721106	journal	January 2009
The 2019 materials by design roadmap Alberi, Kirstin; Nardelli, Marco Buongiorno; Zakutayev, Andriy Journal of Physics D: Applied Physics, Vol. 52, Issue 1 https://doi.org/10.1088/1361-6463/aad926	journal	October 2018
ChemicalTagger: A tool for semantic text-mining in chemistry Hawizy, Lezan; Jessop, David M.; Adams, Nico Journal of Cheminformatics, Vol. 3, Issue 1 https://doi.org/10.1186/1758-2946-3-17	journal	May 2011
The dye-sensitized solar cell database Venkatraman, Vishwesh; Raju, Rajesh; Oikonomopoulos, Solon P. Journal of Cheminformatics, Vol. 10, Issue 1 https://doi.org/10.1186/s13321-018-0272-0	journal	April 2018
A database of battery materials auto-generated using ChemDataExtractor Huang, Shu; Cole, Jacqueline figshare https://doi.org/10.6084/m9.figshare.11888115	dataset	January 2020
Perovskite Solar Cell Database beard, edward; Cole, Jacqueline figshare https://doi.org/10.6084/m9.figshare.13516238	dataset	January 2022
Comparative dataset of experimental and computational attributes of UV/vis absorption spectra Beard, Edward; Sivaraman, Ganesh; Vazquez-Mayagoitia, Alvaro figshare https://doi.org/10.6084/m9.figshare.7619672.v1	dataset	January 2019
Auto-generated materials database of Curie and Néel temperatures via semi-supervised relationship extraction [Supplemental Data] Court, Callum James; Cole, Jacqueline M. figshare-Supplementary information for journal article at DOI: 10.1038/sdata.2018.111, 1 ZIP file (7.18 MB) https://doi.org/10.6084/m9.figshare.c.3954418.v1	dataset	June 2018

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