Comparison of two different Ti/Al/Ti/Au ohmic metallization schemes for AlGaN/GaN
Bibliographic record
Abstract
Two different ohmic metallization schemes for AlGaN/GaN heterostructure field-effect transistor structures are investigated. Each consists of Ti/Al/Ti/Au layers, with the Ti contacting the AlGaN surface, and they differ only in the relative thicknesses of Ti and Al. The “Cornell” metallization consists of 20/100/45/55 nm thicknesses, respectively, while the “NRC” metallization consists of 30/80/120/55 nm thicknesses for the layers. Thus, the Cornell scheme is much richer in Al. The two schemes were compared on the same AlGaN/GaN growth wafer which, because of nonuniformity, provides a variety of contact resistances in the final annealed devices. The Cornell scheme formed good quality ohmic contacts at short anneal times, but clearly contained excess, unalloyed Al, as it showed visible, gas-evolving corrosion in a cleaning solution consisting of 1:1 HCl:H2O. The surface morphology was rough and the edge acuity was relatively poor. Auger depth profiling showed a single, almost uniformly mixed layer. The NRC scheme required a longer anneal time, and the contact resistance remained high for larger grained AlGaN/GaN material. It was stable in the HCl:H2O cleaning solution, and exhibited good edge acuity and a smooth surface morphology. Auger electron depth profiling of the NRC scheme showed two layers present in the annealed metal. The Auger results are consistent with transmission electron microscope results presented elsewhere. The results suggest that the Cornell scheme would be the choice for materials that are more difficult to contact.
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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 | 0.001 |
| 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".