Vibrational Properties and Raman Peak Shift Relationships in Si1−xGex Epilayers Grown on Annealed Double Porous Silicon
Bibliographic record
Abstract
Previous investigations into SiGe alloys using Raman spectroscopy have generated significant uncertainties regarding the relationships between shifts in Raman peak frequencies and stress.Furthermore, these studies did not establish precise correlations when examining alloys on porous substrates.These substrates have emerged as promising candidates in the highly competitive field of adaptable substrates for epitaxial growth of heterogeneous systems (such as III-V, SiGe, etc.) on Silicon (Si).Among these porous materials, double porous silicon (DPSi) has recently garnered attention, featuring a low porosity upper layer atop a buried high porosity layer.However, during a heat treatment, the upper low-porosity layer transforms into a quasi-monocrystalline Si layer, making it suitable for high-quality epitaxial growth.In this work, we present the first investigation of the vibrational properties of the Si1-xGex membranes grown on top of annealed DPSi, using Raman spectroscopy.We systematically propose new relationships linking the Raman peak shift to Ge concentration and strain, using a set of experimental equations derived from the peak positions of the Si-Si, Si-Ge, and Ge-Ge modes.
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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".