Preferential crystal growth of germanium by solid phase crystallization
Bibliographic record
Abstract
We have investigated the preparation of crystalline germanium films by the solid phase crystallization (SPC) of amorphous germanium (a-Ge) precursor on single crystalline silicon substrates. The a-Ge precursor easily incorporates the impurities from the surface exposed to the air, and the impurities affect the crystallinity after the SPC. In the a-Ge precursor prepared by Knudsen-cell evaporation, the preferential crystalline growth following the Si substrates is disturbed by the high density of impurities and the random crystalline structures are formed. The a-Ge precursors prepared by electron beam evaporation have high impurity concentrations only near the surface because the impurity diffusion is slow because of the relatively high density. The preferential growth is successfully obtained in a-Ge precursor prepared on n-type Si substrates, although the random crystallization is slightly observed on p-type Si substrates. By sufficiently reducing the impurity concentrations by avoiding the air exposure, the preferential growth can be promoted on p-type Si substrates. The impurity incorporation because of the air exposure is sufficiently reduced for the preferential growth by covering a-Ge with a-Si blocking layers. This method is effective for future practical applications of SPC Ge films.
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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".