Terahertz Spectroscopy: Studying Carrier Dynamics in Semiconductor Nanostructures
Bibliographic record
Abstract
Understanding the ultrafast dynamics of photoexcited carriers in semiconductor nanostructures and their dependence on sample morphology is crucial for their incorporation into photonic devices. Time-resolved terahertz (THz) spectroscopy (TRTS) is an all-optical, contact-free technique that directly measures the transient mobile carrier dynamics and terahertz conductivity in materials over picosecond time scales, and is uniquely suited as a probe of conductivity in nanomaterials. Using low temperature MBE-grown silicon films as an example, we show how TRTS can be used to probe microscopic photoconductivity as well as obtain crucial insights into sample morphology. The thin silicon films consist of a mixture of amorphous and crystalline phases, and their relative content changes drastically with growth temperature. Photoexcited carrier dynamics in these films are determined by film crystallinity: 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. The complex THz conductivity spectra obtained from the TRTS measurements show that the long range conductivity is significantly higher in films grown at higher temperatures that contain a larger fraction of crystalline material with larger crystal grain sizes.
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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 | 0.001 | 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".