GeSi intermixing in Ge nanostructures on Si(111): An XAFS versus STM study
Bibliographic record
Abstract
We report a detailed investigation of interdiffusion processes that occur during the growth of germanium nanostructures on the (111)-oriented surface of silicon. In particular, X-ray Absorption Fine Structure (XAFS) measurements performed ex situ show that a ${\mathrm{Ge}}_{1\ensuremath{-}x}{\mathrm{Si}}_{x}$ alloy forms during deposition, with average composition $x$ varying between 0.25 and 0.50, depending on substrate temperature and total coverage. By fitting the Si nearest-neighbor numbers around Ge as a function of the deposited thickness with a simple model, the effective vertical composition profile in the growth direction has been estimated. The latter has been described with a static effective diffusion length of $(10.0\ifmmode\pm\else\textpm\fi{}1.5)\phantom{\rule{0.3em}{0ex}}\mathrm{nm}$ at $530\phantom{\rule{0.2em}{0ex}}\ifmmode^\circ\else\textdegree\fi{}\mathrm{C}$ and $(5\ifmmode\pm\else\textpm\fi{}1)\phantom{\rule{0.3em}{0ex}}\mathrm{nm}$ at $450\phantom{\rule{0.2em}{0ex}}\ifmmode^\circ\else\textdegree\fi{}\mathrm{C}$, which is interpreted as the dominance of surface transport processes in the intermixing dynamics. The analysis of the data on Ge-Ge bond length indicates a decrease of the Ge-Ge atomic distances with increasing Ge fraction, confirming previous theoretical predictions for strained epilayers. The XAFS results are compared to morphological information obtained by scanning tunneling microscopy investigations carried out in situ, yielding a satisfactory description for the epitaxy of this system.
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 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) | 0.002 | 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".