ArticleMacromolecules2023
Machine-Learning-Assisted Understanding of Polymer Nanocomposites Composition-Property Relationship: A Case Study of NanoMine Database.
Article in Macromolecules, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
8 citing papers in PubMed.
- A review on the controlled preparation, structure-property relationship and application progress of multifunctional metal nanoparticle-based polymer nanocomposites.RSC advances · 2026Review
- Artificial intelligence for design strategies of tissue engineering materials.Fundamental research · 2026Review
- Physics-informed AI framework for multiscale design, discovery, and optimization of polymer nanocomposite microstructures using neural operators.Scientific reports · 2026Article
- Machine Learning Framework for Characterizing Processing-Structure Relationship in Block Copolymer Thin Films.Macromolecules · 2026Article
- Emerging nanomedicine for liver diseases treatment.Journal of nanobiotechnology · 2025Review
- Holistic concept guided quality control of traditional Chinese medicines for optimizing bioavailability.Chinese medicine · 2025Review
- Machine Learning in Polymer Research.Advanced materials (Deerfield Beach, Fla.) · 2025Review
- Expanding the Horizons of Machine Learning in Nanomaterials to Chiral Nanostructures.Advanced materials (Deerfield Beach, Fla.) · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The NanoMine database, one of two nodes in the MaterialsMine database, is a new materials data resource that collects annotated data on polymer nanocomposites (PNCs). This work showcases the potential of NanoMine and other materials data resources to assist fundamental materials understanding and therefore rational materials design. This specific case study is built around studying the relationship between the change in the glass transition temperature
Identifiers
What OpenQuestion holds
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.