Temperature dependent structural, electronic and optical properties of the Si(100) surface from first principles
Bibliographic record
Abstract
The results presented here were obtained using the local density approximation (LDA) to density functional theory (DFT), within the pseudo-potentials scheme. We present the results of the numerical simulations for the Si bulk and Si(100) surface; ab-initio molecular dynamics (AIMD) using the Car-Parrinello Molecular Dynamics formalism (CPMD) and Born-Oppenheimer Molecular Dynamics (BOMD), related vibrational states (surface phonons) by calculating the vibrational density of states (VDOS) using a harmonic and anharmonic approach, and the optical response of the Si bulk and Si(100) surface calculating the temperature dependent reflectance anisotropy (RA). The surface reconstruction and temperature stimulated dimer flip impacts the surface reconstruction dynamics, the surface band gap and the optical response. For the calculated optical response and phonon spectra real temperature dependent atomic motion has been incorporated into the numerical formalism explicitly. This allows us to calculate the above materials??? properties, and reach an agreement with experiment, at different temperatures.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".