Hafnium dioxide (HfO<sub>2</sub>) as micro-crucible liner on GeOI for rapid melt growth (RMG) structure
Bibliographic record
Abstract
This paper presented an evaluation of hafnium dioxide (HfO2) used as insulator and micro-crucible in the modification of rapid melt growth (RMG) structure. A 20 nm HfO2 have been deposited on silicon (Si) and silicon on insulator (SOI) substrates using Atomic Layer Deposition (ALD). Samples encapsulated with HfO2 in the RMG structure shows free from cracks and delamination even heated at higher annealing temperature (1049oC) that observed by Scanning Electron microscopy (SEM), Transmission Electron Microscopy (TEM) and Focus Ion Beam (FIB). The quality of Germanium (Ge) thin-film is characterised using micro-Raman Spectroscopy. Results show that samples with HfO2 micro-crucible liner on Si substrate gives the Ge-Ge peak position lies at ~299 cm-1, indicating that the 20 nm HfO2 layer gives slightly tensile strain with a small shift in peak position compared to the bulk reference value of 300.2 cm-1. The Raman peak position for samples on SOI substrate increased approximately 0.3 cm-1 to 299.3 cm-1 indicating lower stress. The Raman peak of this sample had an increased Full width at half maximum (FWHM) of ~3.9 cm-1 which is believed to be mainly due to the presence of HfO2 and scattering of Raman laser.
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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".