Self-sustained Marangoni Flows Driven by Chemical Reactions
Bibliographic record
Abstract
Out-of-equilibrium chemical systems, comprising reaction networks and molecular self-assembly pathways, rely on the delivery of reagents. Rather than via external flow, diffusion or convection, we aim at self-sustained reagent delivery. Therefore, we explore how the coupling of Marangoni flow with chemical reactions can generate self-sustained flows, driven by said chemical reactions, and – in turn – sustained by the delivery of reagents for this reaction. We combine a photoacid generator with a pH-responsive surfactant, such that local UV exposure decreases the pH, increases the surface tension and triggers the emergence of a Marangoni flow. We study the impact of reagent concentrations and identify threshold conditions at which flow can emerge. Surprisingly, we unraveled an antagonistic influence of the reagents on key features of the flow such as interfacial velocity and duration, and rationalize these findings via a kinetic model. Our study displays the potential of reaction-driven flow to establish autonomous control in fuel delivery of out-of-equilibrium systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".