Reference health
Large Language Models as Master Key: Unlocking the Secrets of Materials Science
7/7 checkable references clean · checked 2026-08-27
Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.
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The 7 checked references that resolve
resolves10.1038/s41586-019-1335-8
Unsupervised word embeddings capture latent knowledge from materials science literature
resolves10.1038/s41560-021-00941-3
An open-access database and analysis tool for perovskite solar cells based on the FAIR data principles
resolves10.1021/acs.jcim.6b00207
ChemDataExtractor: A Toolkit for Automated Extraction of Chemical Information from the Scientific Literature
resolves10.1021/acs.jcim.9b00470
Named Entity Recognition and Normalization Applied
to Large-Scale Information Extraction from the Materials Science Literature
resolves10.1109/BigData52589.2021.9671697
Fine-Tuning BERT Model for Materials Named Entity Recognition
resolves10.1016/j.jbi.2015.08.008
PKDE4J: Entity and relation extraction for public knowledge discovery
resolves10.1021/ci00057a005
SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules
The 29 references without a DOI — listed, not checked
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no DOI — not checkedBatteryBERT: A Pretrained Language Model for Battery Database Enhancement
no DOI — not checkedBatteryDataExtractor: battery-aware text-mining software embedded with BERT models
no DOI — not checkedEmpty rhetoric over data sharing slows science
no DOI — not checkedData-driven materials research enabled by natural language processing and information extraction
no DOI — not checkedref7
no DOI — not checkedA database of battery materials auto-generated using ChemDataExtractor
no DOI — not checkedComparative dataset of experimental and computational attributes of UV/vis absorption spectra
no DOI — not checkedref12
no DOI — not checkedText-mined dataset of inorganic materials synthesis recipes
no DOI — not checkedref15
no DOI — not checkedref16
no DOI — not checkedref18
no DOI — not checkedQuantifying the advantage of domain-specific pre-training on named entity recognition tasks in materials science
no DOI — not checkedref20
no DOI — not checkedAuto-generated database of semiconductor band gaps using
no DOI — not checkedPerovskite-and Dye-Sensitized Solar-Cell Device Databases Autogenerated Using ChemDataExtractor
no DOI — not checkedref23
no DOI — not checkedMatSciBERT: A materials domain language model for text mining and information extraction
no DOI — not checkedref25
no DOI — not checkedLocText: relation extraction of protein localizations to assist database curation
no DOI — not checkedref28
no DOI — not checkedLanguage models are few-shot learners
no DOI — not checkedHow Machine Learning Predicts and Explains the Performance of Perovskite Solar Cells
no DOI — not checkedIs GPT-3 all you need for low-data discovery in chemistry ?
no DOI — not checkedref33
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no DOI — not checkedMachine learning property prediction for organic photovoltaic devices
no DOI — not checkedref36
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