Residual Stress, Defects, and Electrical Properties of Epitaxial Copper Growth on GaAs
Bibliographic record
Abstract
The residual stress in Cu films epitaxially grown on GaAs(001) single crystalline substrates has been compared to polycrystalline Cu growth on (111) textured Au substrates, both grown via the same galvanostatic electrodeposition process. Optimized epitaxial nucleation and growth was obtained with a substrate pre-etch in dilute ammonium-hydroxide followed by electrodeposition in a pure Cu sulfate aqueous electrolyte at elevated temperatures. The resulting films are single crystalline, and strain relaxed, as measured by X-ray and electron diffraction. The (001) surfaces developed square pyramidal facets that increase in average size with increasing current density. In situ wafer curvature measurements found that the films followed the commonly observed change from compressive to tensile and finally to compressive stress that quickly relaxed once growth was interrupted. In contrast, polycrystalline films developed a smaller and constant tensile stress that relaxed more slowly. Given the similar growth rates of the two systems, differences in residual stress are related to differences in the density and nature of the coalescence boundaries and associated surface adatom processes. The resulting electrical properties of diodes show an interfacial capacitance that is consistent with interdiffusion and the reaction layer detected by electron microscopy.
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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".