ArticleScientific data2022
Text-mined dataset of gold nanoparticle synthesis procedures, morphologies, and size entities.
Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed.
- Prospects of Nanoscience with Nanocrystals: 2025 Edition.ACS nano · 2025Review
- Intelligent Systems for Inorganic Nanomaterial Synthesis.Nanomaterials (Basel, Switzerland) · 2025Review
- A Holistic Data-Driven Approach to Synthesis Predictions of Colloidal Nanocrystal Shapes.Journal of the American Chemical Society · 2025Article
- Synthesis of anisotropic gold nanoparticles in binary surfactant mixtures: a review on mechanisms of particle formation.RSC advances · 2025Review
- Expanding Chemical Space in the Synthesis of Gold Bipyramids.Small (Weinheim an der Bergstrasse, Germany) · 2025Article
- Materials science in the era of large language models: a perspective.Digital discovery · 2024Review
- Large language model enhanced corpus of COScientific data · 2024Article
- Text Mining the Literature to Inform Experiments and Rationalize Impurity Phase Formation for BiFeOChemistry of materials : a publication of the American Chemical Society · 2024Article
- Emerging Trends in Hybrid Nanoparticles: Revolutionary Advances and Promising Biomedical Applications.Current drug metabolism · 2024Review
- EXSCLAIM!: Harnessing materials science literature for self-labeled microscopy datasets.Patterns (New York, N.Y.) · 2023Article
- Precursor recommendation for inorganic synthesis by machine learning materials similarity from scientific literature.Science advances · 2023Article
- A corpus of COScientific data · 2023Article
- BatteryDataExtractor: battery-aware text-mining software embedded with BERT models.Chemical science · 2022Article
- Machine-Learning Rationalization and Prediction of Solid-State Synthesis Conditions.Chemistry of materials : a publication of the American Chemical Society · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Gold nanoparticles are highly desired for a range of technological applications due to their tunable properties, which are dictated by the size and shape of the constituent particles. Many heuristic methods for controlling the morphological characteristics of gold nanoparticles are well known. However, the underlying mechanisms controlling their size and shape remain poorly understood, partly due to the immense range of possible combinations of synthesis parameters. Data-driven methods can offer insight to help guide understanding of these underlying mechanisms, so long as sufficient synthesis data are available. To facilitate data mining in this direction, we have constructed and made publicly available a dataset of codified gold nanoparticle synthesis protocols and outcomes extracted directly from the nanoparticle materials science literature using natural language processing and text-mining techniques. This dataset contains 5,154 data records, each representing a single gold nanoparticle synthesis article, filtered from a database of 4,973,165 publications. Each record contains codified synthesis protocols and extracted morphological information from a total of 7,608 experimental and 12,519 characterization paragraphs.
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.