The Effects Of Blast Lag In Abrasive Jet Machined Micro-Channel Intersections
Bibliographic record
Abstract
Abrasive jet micro-machining (AJM) uses compressed air carrying abrasive solid particles to micro-machine a variety of features into surfaces. If the features are smaller than a few mm, then a patterned erosion-resistant mask is used to protect the substrate material, leaving exposed areas to define the features. Previous investigations have revealed a ‘blast lag’ phenomenon in which, for the same dose of abrasive particles, the etched depth of micro-channels and holes tends to decrease as the features become narrower. Blast lag occurs when using AJM on brittle substrates because of the natural tendency to rapidly form a V-shaped cross-sectional profile which inhibits abrasive particle strikes on the narrow vertex at the feature centerline. In this thesis, for the first time, the blast lag phenomenon is studied when using AJM to machine a network of microfluidic channels. It is found that, in some cases, differences in blast lag occurring at channel intersections and within the channels themselves, can lead to channel networks of non-uniform depth. A previously developed surface evolution model is used to predict the onset of blast lag in the channels and intersections, and thus explain these differences. Finally, methods to eliminate the differences are discussed.
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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 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 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".