<i>In situ</i> x-ray diffraction study of metal induced crystallization of amorphous germanium
Bibliographic record
Abstract
Metal induced crystallization (MIC) is a technique that lowers the crystallization temperature of amorphous semiconductors. The process has mainly been used to influence the crystallization of amorphous silicon (a-Si) and multiple studies on this subject have already been performed. The research of the MIC of amorphous Ge (a-Ge) has been mostly limited to the use of a Ni or Al film. This paper focuses on the characterization of the crystallization behavior of a-Ge films in the presence of 20 transition metals (Ti, Zr, Hf, V, Nb, Ta, Cr, Mo, W, Mn, Re, Fe, Ru, Co, Rh, Ir, Ni, Pd, Pt, Cu, Ag, Au, and Al). The kinetics of the crystallization process are also systematically studied for the seven metals that lower the initial crystallization temperature the most. In addition, the influence of the thickness of the metal film was determined for the case of a Au and Al film. A comparison of the influence of the various metals on a-Ge and a-Si is made and the similarities and differences are discussed using existing models for the MIC process.
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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".