Bibliographic record
Abstract
In the abrasive jet micro-machining (AJM) process, a jet of small particles is directed through an erosion resistant mask opening so that micro-sized features (i.e., micro-channels, holes, etc.) can be machined for the fabrication of micro-devices such as micro-fluidic and micro-electro-mechanical-systems (MEMS). Polymeric materials and elastomers have found applications in a wide variety of micro-devices. This thesis investigates the AJM of such materials, addressing the major challenges that must be overcome in order for the process to gain wider acceptance in industry. The thesis first presents a novel cryogenically assisted abrasive jet micro-machining (CAJM) technique that enables the micro-machining of elastomers such as polydimethylsiloxane (PDMS) that cannot be machined at room temperature. It was found that the erosion rate during CAJM is greatly increased, and the degree of particle embedment greatly decreased, compared to room temperature experiments. A finite element (FE) analysis was used to investigate the relationships between erosion, the heat transfer of the cooling jet and the resulting target temperature during the CAJM of channels in PDMS. The analysis illustrated the asymmetric nature of the cooling with much more cooling occurring towards the trailing edge of the jet. It was found that the predicted shape of the evolving machined surface profiles was improved significantly when a FE model was used to account for thermal distortion occurring during the CAJM process. An unwanted consequence of the AJM of polymeric materials was found to be particle embedding. Criteria leading to the embedding of spherical and angular particles in such materials were identified and modelled using rigid plastic analyses. It was found that the likelihood of embedding was proportional to the static coefficient of friction between the particle and the target for angular particles, and the depth of penetration for spherical particles. Scanning electron microscopy with EDX was used to measure the area coverage of embedded Al2O3 particles in polymers and elastomers, in order to evaluate various cleaning methods that were developed. It was found that glass bead blasting at 45˚ followed by the freezing technique was the best method to remove embedded particles, leading to 100% removal in some cases.
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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 | 0.000 |
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 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".