Lift-off with solvent for negative resist using low energy electron beam exposure
Bibliographic record
Abstract
Lift-off and direct etch are the two most popular pattern transfer methods for electron beam lithography. For some applications negative resist would offer significantly less exposure time than positive one. Unfortunately, lift-off using negative resist is very challenging because the resist profile is typically positively tapered due to electron forward scattering, and upon exposure, negative resist is cross-linked and thus insoluble in solvents. Here, the authors will show that low energy exposure can circumvent both issues simultaneously, and the authors achieved liftoff of Cr with polystyrene resist using a solvent xylene. Moreover, low energy exposure offers proportionally higher resist sensitivity. Lastly, since low energy electrons are mostly stopped inside the resist layer, radiation damage to the sublayer is greatly reduced. Thus, the current method may be employed to fabricate metal nanostructures on top of an organic conducting layer.
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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 | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".