Highly tensile-strained Ge/InAlAs nanocomposites
Bibliographic record
Abstract
Abstract Self-assembled nanocomposites have been extensively investigated due to the novel properties that can emerge when multiple material phases are combined. Growth of epitaxial nanocomposites using lattice-mismatched constituents also enables strain-engineering, which can be used to further enhance material properties. Here, we report self-assembled growth of highly tensile-strained Ge/In 0.52 Al 0.48 As (InAlAs) nanocomposites by using spontaneous phase separation. Transmission electron microscopy shows a high density of single-crystalline germanium nanostructures coherently embedded in InAlAs without extended defects, and Raman spectroscopy reveals a 3.8% biaxial tensile strain in the germanium nanostructures. We also show that the strain in the germanium nanostructures can be tuned to 5.3% by altering the lattice constant of the matrix material, illustrating the versatility of epitaxial nanocomposites for strain engineering. Photoluminescence and electroluminescence results are then discussed to illustrate the potential for realizing devices based on this nanocomposite material.
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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".