Light-Blocking Optical Alignment Rulers for Guiding Layer-by-Layer Integration
Bibliographic record
Abstract
Vertical integration of device layers is a prevailing strategy to boost the performance of microchips and optical devices while maintaining a small form factor. In this paper, we introduce light blocking optical alignment rulers (LBOARs) for layer-by-layer alignment of thin films, which can be potentially applied in manufacturing three-dimensional integrated circuits. LBOAR measures the blocking of the light transmitted through two vertically stacked subwavelength aperture arrays (gratings), which are fabricated onto the separate device layers to be aligned. Here, detailed numerical studies and proof-of-concept experiments on LBOAR are presented. The simulation results reveal two different mechanisms governing the light transmission through a pair of rulers: light blocking and induced extraordinary optical transmission (EOT). In the light-blocking regime, the intensity change is very sensitive to the horizontal shift between two rulers. In contrast, EOT-based alignment is significantly disturbed by the vertical separation of the nearly contacting rulers. Therefore, LBOAR can be more advantageous than EOT-based alignment for certain applications that require only horizontal alignment between two layers of devices. To validate the light-blocking concepts, in our experiments, two-layer stacked LBOARs were fabricated using laser lithography, physical vapor deposition, and dry etching. Optical transmission measurements show that in the nearly perfect alignment condition the transmitted intensity in the light-blocking regime drops significantly providing an alignment accuracy better than 200 nm.
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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".