Fabrication of sharp silicon hollow microneedles by deep-reactive ion etching towards minimally invasive diagnostics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Microneedle technologies have the potential for expanding the capabilities of wearable health monitoring from physiology to biochemistry. This paper presents the fabrication of silicon hollow microneedles by a deep-reactive ion etching (DRIE) process, with the aim of exploring the feasibility of microneedle-based in-vivo monitoring of biomarkers in skin fluid. Such devices shall have the ability to allow the sensing elements to be integrated either within the needle borehole or on the backside of the device, relying on capillary filling of the borehole with dermal interstitial fluid (ISF) for transporting clinically relevant biomarkers to the sensor sites. The modified DRIE process was utilized for the anisotropic etching of circular holes with diameters as small as 30 μm to a depth of >300 μm by enhancing ion bombardment to efficiently remove the fluorocarbon passivation polymer. Afterward, isotropic wet and/or dry etching was utilized to sharpen the needle due to faster etching at the pillar top, achieving tip radii as small as 5 μm. Such sharp microneedles have been demonstrated to be sufficiently robust to penetrate porcine skin without needing any aids such as an impact-insertion applicator, with the needles remaining mechanically intact after repetitive penetrations. The capillary filling of DRIE-etched through-wafer holes with water has also been demonstrated, showing the feasibility of use to transport the analyte to the target sites.
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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) | 0.001 | 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 | 0.001 |
| 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 it