A Finite Element Model for Predicting the Collapse of Short and Large Two-Line Patterns During Drying Process in Photolithography
Bibliographic record
Abstract
Photolithography is one of the main mass nano-production processes. Smaller devices are always aimed to save material and energy. Manufacturing small devices by photolithography is a challenge, due to the risk of collapse of patterns during the drying of rinse liquid. One of the main pattern shapes is the two-line parallel. In our previous study, an analytical model was developed for predicting the collapse of large (L/d, LAR>20; see Fig. 1) two-line parallel patterns [1]. This model assumes the rinse interface shape is cylindrical. Knowledge of the rinse interface shape is needed to define the forces contribute to collapse, i.e. Laplace pressure and surface tension force at the three-phase line. In the current study, a Finite Element (FE) model is developed to predict the collapse of short (LAR<20) and large (LAR>20) two-line parallel patterns. Rinse liquid shape and its curvature are found using Surface Evolver (an interactive program for the study of surfaces shaped by surface tension, gravitational and other energies). Another finite element method (i.e. ANSYS 11.0) is used to find the pattern deformation. It was found that the pattern deformation decreases by decreasing the LAR value. It is important as for the cases that due to the design specifications, selection of the pattern material and rinse liquid is restricted, by changing the LAR value one may resolve the collapse problem.
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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".