Geomaterial‐Functionalized Microfluidic Devices Using a Universal Surface Modification Approach
Bibliographic record
Abstract
Abstract The layer‐by‐layer (LbL) self‐assembly technique is used to coat the surface of flow channels in microfluidic chips with geomaterials. The surface modifications diminish the discrepancy between the surface chemistry of synthesized microfluidic devices and those of underground porous rocks. Hence, the use of visual models and, in particular, microfluidic devices is broadened to simulate the multiphase flows and fluid–solid interactions in actual rocks. Glass and quartz substrates are successfully coated with silicon dioxide (SiO2), bentonite, and montmorillonite. On‐chip functionalization of polydimethylsiloxane (PDMS) and glass micromodels with SiO2 is also accomplished. The functionalized coatings using confocal laser scanning microscopy (CLSM), atomic force microscopy (AFM), and contact angle measurements are characterized. The surface modification technique is shown to be material‐independent, which generates a hydrophilic surface. The surface‐coated chips, functionalized by clay particles, are utilized to illustrate the role of water salinity on oil displacement.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".