Niobium and Aluminum Josephson Junctions Fabricated with a Damascene CMP Process
Bibliographic record
Abstract
We report on the fabrication of Josephson junction and superconducting bridges using a damascene CMP process applied for a first time to superconductors. The demonstrated industrial reliability of damascene CMP processes on large scale semiconductor circuits is a major incentive for our research that should allow large numbers of nanometric Josephson junctions to be fabricated in both Nb and Al, the two main material employed in superconducting quantum computing (qubit) and RSFQ electronics fabrication.We carried out a Chemical-Mechanical Polishing (CMP) process on Nb and Al films deposited on a SiO2 layer patterned with trenches of 100 to 300 nm of nominal depth. The process formed long bridges, 1 to 4 μm wide. The susceptibility and resistive transitions showed that CMP has no observable influence on superconductivity.We have also developed a hybrid technique that uses Al/Al2O3/Al shadow evaporation in the trenches before the damascene CMP process. This allows for high quality “in-situ” junction oxidation with the size reduction benefit provided by the damascene CMP process. We easily reach junctions sizes near 0.5 μm2 which are difficult to fabricate by other methods.We describe these techniques and report on measurements on large bridges and junctions and on the fabrication and measurements of Al and Nb nanobridges.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".