Ultrafast carrier dynamics and the role of grain boundaries in polycrystalline silicon thin films grown by molecular beam epitaxy
Bibliographic record
Abstract
Abstract We have used time-resolved terahertz spectroscopy to study microscopic photoconductivity and ultrafast photoexcited carrier dynamics in thin, pure, non-hydrogenated silicon films grown by molecular beam epitaxy on quartz substrates at temperatures ranging from 335 °C to 572 °C. By controlling the growth temperature, thin silicon films ranging from completely amorphous to polycrystalline with minimal amorphous phase can be achieved. Film morphology, in turn, determines its photoconductive properties: in the amorphous phase, carriers are trapped in bandtail states on sub-picosecond time scales, while the carriers excited in crystalline grains remain free for tens of picoseconds. We also find that in polycrystalline silicon the photoexcited carrier mobility is carrier-density-dependent, with higher carrier densities mitigating the effects of grain boundaries on inter-grain transport. In a film grown at the highest temperature of 572 °C, the morphology changes along the growth direction from polycrystalline with needles of single crystals in the bulk of the film to small crystallites interspersed with amorphous silicon at the top of the film. Depth profiling using different excitation wavelengths shows corresponding differences in the photoconductivity: the photoexcited carrier lifetime and mobility are higher in the first 100–150 nm from the substrate, suggesting that thinner, low-temperature grown polycrystalline silicon films are preferable for photovoltaic applications.
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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 | 0.001 |
| 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".