ArticleThe journal of physical chemistry. B2023
Can Machine Learning Predict the Phase Behavior of Surfactants?
Article in The journal of physical chemistry. B, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- A dataset for aqueous surfactant phase behavior as a function of temperature and composition.Scientific data · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We explore the prediction of surfactant phase behavior using state-of-the-art machine learning methods, using a data set for twenty-three nonionic surfactants. Most machine learning classifiers we tested are capable of filling in missing data in a partially complete data set. However, strong data bias and a lack of chemical space information generally lead to poorer results for entire
Identifiers
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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.