Effect of Triton X-100 surfactant and agitation on tetramethylammonium hydroxide wet etching for microneedle fabrication
Bibliographic record
Abstract
Solid silicon (Si) microneedles have many applications such as skin pretreatment to form micrometer-sized holes in the skin surface in transdermal drug delivery systems. Wet etching based on tetramethylammonium hydroxide (TMAH) is an efficient method to fabricate solid microneedles. However, it is challenging to increase the density of microneedle arrays due to the faster lateral etching than the vertical etching that requires a large initial mask size. In this work, we used wet etching based on TMAH to fabricate solid Si microneedles. One kind of nonionic surfactant, Triton X-100, was introduced into the TMAH solution to suppress the lateral etching. When Triton X-100 was added into TMAH for a given etching condition, the maximum height (attained right before the mask fell off) of microneedles could reach ∼230 μm for 600 μm square-shaped mask size and 700 μm array period, compared to microneedles of maximum 152 μm height for the same mask size and period without surfactant addition. Correspondingly, when the target heights of microneedles were the same as ∼230 μm, denser (down to 700 μm period, 600 μm mask size) microneedle arrays were achieved with the help of Triton X-100, in comparison to arrays down to 900 μm period (800 μm mask size) without surfactant addition. Furthermore, agitation by a magnetic stirring bar is important for the fabrication of dense solid Si microneedle arrays based on TMAH. The microneedle structures were rhombic pyramid in shape with Triton X-100 and agitation. But microneedle structures obtained with Triton X-100 yet without agitation were octagonal pyramid in shape with a much less steep side surface.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".