Bibliographic record
Abstract
<p>The general objective of this thesis is to introduce ultrafast "Laser Induced Reverse Transfer" (LIRT) as a technique for material transfer in micro-fabrication. LIRT is performed using femtosecond laser radiation of wavelength 515 nm with gold coated silicon wafers under ambient conditions. The material transfer process is explained by the dynamics of a laser ablated plasma plume. The influence of processing parameters such as laser pulse energy, pulse width and scan speed on the width of transferred material is also investigated. The width of the deposition increases with the increase in pulse energy while it decreases with scan speed. Also, the width increases with laser pulse width ranging from femtosecond to picosecond range. In general the transferred material size is determined by the amount of material present in the plasma plume which depends on the energy deposited in the bulk material by laser irradiation. In the femtosecond pulse width range, the increase in pulse energy at constant pulse width transfers more energy in a short time with minimal heating effect to the surrounding material. Hence, the efficiency of material removal increases. This in turn enhances the feature size. On the other hand, as the laser pulse width increases from femtoseconds to picoseconds, the interaction time of laser radiation with material increases. This leads to an increase in the amount of material removed, thereby increasing the transferred material size. However, thermal damage to the surrounding material increases. An increase in scan speed at constant pulse energy decreases the laser interaction time, which results in a decrease in amount of material in the plasma plume. This in tum decreases the width of the deposited material. In general, femtosecond laser induced reverse material transfer is an efficient technique for microfabrication and can be used for device manufacturing.</p>
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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".