High density cleanroom-free microneedle arrays for pain-free drug delivery
Bibliographic record
Abstract
Abstract The purpose of this work is to demonstrate the fabrication process for cleanroom-free solid metal microneedles and perform quantification of insertion profiles. Metal microneedles were created using a modified wirebonding process and inserted into porcine tissue to determine design efficacy. Microneedle arrays were analyzed through optical imaging and scanning electron microscopy. Insertion forces were measured using combined uniaxial load cell and resistance measurement data. Microneedle arrays were successfully inserted into porcine tissue with high repeatability and reliability. These arrays demonstrate lower or equivalent insertion forces (less than 3 N) to other forms of microneedles in the literature without the need for complex cleanroom fabrication processes. The microneedle fabrication method presented here rapidly produces mass manufacturable, high-quality microneedle arrays with minimal insertion forces, able to reliably penetrate tissue samples. The manufacturing method presented here achieved array densities as high as 3200 needles cm−2. These microneedle arrays demonstrate simple fabrication of a reliable, high-density, pain-free drug delivery system, with potential applications in biosensing and electric field modulated drug delivery.
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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 | 0.001 |
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".