ArticleScientific data2023
Automated Construction of a Photocatalysis Dataset for Water-Splitting Applications.
Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed.
- Data-Driven Materials Science for Energy-Sustainable Applications.Advanced materials (Deerfield Beach, Fla.) · 2026Review
- Article
- Autogenerating a Domain-Specific Question-Answering Data Set to Enable High-Performing Language Models for Magnetic Materials.Journal of chemical information and modeling · 2026Article
- A dataset of Curie and Néel temperatures auto-generated with ChemDataExtractor and the Snowball algorithm.Scientific data · 2025Article
- High-Throughput Photocatalysis for Generating Reliable Datasets Analyzed by Machine Learning.Chemphyschem : a European journal of chemical physics and physical chemistry · 2025Article
- Autogenerating a Domain-Specific Question-Answering Data Set from a Thermoelectric Materials Database to Enable High-Performing BERT Models.Journal of chemical information and modeling · 2025Article
- Cost-Efficient Domain-Adaptive Pretraining of Language Models for Optoelectronics Applications.Journal of chemical information and modeling · 2025Article
- MechBERT: Language Models for Extracting Chemical and Property Relationships about Mechanical Stress and Strain.Journal of chemical information and modeling · 2025Article
- A Database of Stress-Strain Properties Auto-generated from the Scientific Literature using ChemDataExtractor.Scientific data · 2024Article
- Materials science in the era of large language models: a perspective.Digital discovery · 2024Review
- How Beneficial Is Pretraining on a Narrow Domain-Specific Corpus for Information Extraction about Photocatalytic Water Splitting?Journal of chemical information and modeling · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
We present an automatically generated dataset of 15,755 records that were extracted from 47,357 papers. These records contain water-splitting activity in the presence of certain photocatalysts, along with additional information about the chemical reaction conditions under which this activity was recorded. These conditions include any co-catalysts and additives that were present during water splitting, the length of time for which the photocatalytic experiment was conducted, and the type of light source used, including its wavelength. Despite the text extraction of such a wide range of chemical reaction attributes, the dataset afforded good precision (71.2%) and recall (36.3%). These figures-of-merit were calculated based on a random sample of open-access papers from the corpus. Mining such a complex set of attributes required the development of novel techniques in knowledge extraction and interdependency resolution, leveraging inter- and intra-sentence relations, which are also described in this paper. We present a new version (version 2.2) of the chemistry-aware text-mining toolkit ChemDataExtractor, in which these new techniques are included.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.