ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025
Data-Driven Theoretical Modeling of Centrifugal Step Emulsification and Its Application in Comprehensive Multiscale Analysis.
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Multi-mode droplet splitting on active-matrix digital microfluidics: quantitative boundaries and optimal sequential generation.Microsystems & nanoengineering · 2026Article
- Food-Grade Emulsion Gels as Nutrient Delivery Systems-Standardized Workflow for Fabrication, Characterization, and Application.Gels (Basel, Switzerland) · 2026Review
- Data-Driven Theoretical Modeling of Centrifugal Step Emulsification and Its Application in Comprehensive Multiscale Analysis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
Tailored droplet generation is crucial for droplet microfluidics that involve samples of varying sizes. However, the absence of precise predictive models forces droplet platforms to rely on empiricism derived from extensive experiments, underscoring the need for comprehensive modeling analysis. To address this, a novel customized assembled centrifugal step emulsifier (CASE) is presented by incorporating a "jigsaw puzzles" design to efficiently acquire large-scale experimental data. Numerical simulations are utilized to analyze fluid configurations during step emulsification, identifying a key connection tube that determines droplet size. By training and verifying with the experimental and simulation datasets, a comprehensive theoretical model is established that allows for the preliminary design of the droplet size and generation frequency with an average error rate of 4.8%, successfully filling a critical gap in existing field. This predictive model empowers the CASE to achieve all-in-one functionality, including droplet pre-design, generation, manipulation, and on-site detection. As a proof of concept, multiscale sample analysis ranging from nanoscale nucleic acids to microscale bacteria and 3D cell spheroids is realized in the CASE. In summary, this platform offers valuable guidance for customized droplet generation by centrifugal step emulsifiers and promotes the adoption of droplet microfluidics in biochemical assays.
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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.