Characterization of pulsed ultraviolet laser micromachining operation for rapid prototyping of microfluidic devices
Bibliographic record
Abstract
Advancements in lab-on-a-chip technologies have led to the rapid development and widespread use of miniaturized, portable analytical chemistry equipment and biosensing devices. These biosensing devices have enabled the application of modern analytical methods to numerous industries including forensics, agrifood technology, and point-of-care medical diagnostics. The development of such devices is largely made possible by continuous advancements in microfluidic fabrication techniques. In this area, laser ablation processes have shown promise as a replacement to more complex lithographic fabrication methods. Such processes are prone to causing microfractures and thermal stresses in the microfluidic substrate, potentially causing leaking and delamination when the devices are in use. In this work, an Oxford Lasers A-355 Micromachining System is used to fabricate microfluidic devices with high resolution features in low-cost glass substrates (borosilicate glass and soda lime glass). The fabricated microfluidic devices are enclosed using a low-temperature glass-to-glass bonding technique. For each substrate the laser cut depth is reported as a function of pulse frequency and peak operating power. This characterization fills important gaps in literature and enables researchers to customize the laser ablation process to fit the unique requirements of their microfluidic devices. The optimized ablation procedure is presented and shown to produce a watertight seal when bonded to a secondary enclosure substrate. Nominal actuation of the device is demonstrated with a red dye sample.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".