Superhydrophobic bowl-like SERS substrates patterned from CMOS sensors for extracellular vesicle characterization
Bibliographic record
Abstract
Using a regular CMOS sensor as a template, we are able to fabricate a simple but highly effective superhydrophobic SERS substrate. Specifically, we decorated the microlens layer of the sensor with 7 μm polystyrene beads to obtain a PDMS patterned replica. The process resulted in a uniform pattern of voids in the PDMS (denoted nanobowls) that are intercalated with a few larger voids (denoted here microbowls). The voids act as superhydrophobic substrates with analyte concentration capabilities in bigger bowl-like structures. Silver nanoparticles were directly grown on the patterned PDMS substrate inside both the nano- and microbowls, and serve as strong electromagnetic field enhancers for the SERS substrate. After systematic characterization of the fabricated SERS substrate by atomic force microscopy and scanning electron microscopy, we demonstrated its SERS performance using 4-aminothiophenol as a reporter molecule. Finally, we employed this innovative substrate to concentrate and analyze extracellular vesicles (EVs) isolated from an MC65 neural cell line in an ultralow sample volume. This substrate can be further exploited for the investigation of various EV biomarkers for early diagnosis of different diseases using liquid biopsy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".