Ultra‐Thin Strain‐Relieving Si<sub>1−x</sub>Ge<sub>x</sub> Layers Enabling III‐V Epitaxy on Si
Bibliographic record
Abstract
Abstract The explosion of artificial intelligence, the possible end of Moore's law, dawn of quantum computing, and the continued exponential growth of data communications traffic have brought new urgency to the need for laser integration on the diversified Si platform. While diode lasers on group III‐V platforms have long‐powered internet data communications and other optoelectronic technologies, direct integration with Si remains problematic. A paradigm‐shifting solution requires exploring new and unconventional materials and integration approaches. In this work, it is shown that a sub‐10‐nm ultra‐thin Si 1−x Ge x buffer layer fabricated by an oxidative solid‐phase epitaxy process can facilitate extraordinarily efficient strain relaxation. The Si 1−x Ge x layer is formed by ion implanting Ge into Si(111) and selectively oxidizing Si atoms in the resulting ion‐damaged layer, precipitating a fully strain‐relaxed Ge‐rich layer between the Si substrate and surface oxide. The efficient strain relaxation results from the high oxidation temperature, producing a periodic network of dislocations at the substrate interface, coinciding with modulations of the Ge content in the Si 1−x Ge x layer and indicating the presence of defect‐mediated diffusion of Si through the layer. The epitaxial growth of high‐quality GaAs is demonstrated on this ultra‐thin Si 1−x Ge x layer, demonstrating a promising new pathway for integrating III‐V lasers directly on the Si platform.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".