Ultrafast photocarrier dynamics in Fe-implanted InGaAs polycrystalline photoconductive materials
Bibliographic record
Abstract
Abstract We investigate the ultrafast photoconductivity and charge-carrier transport in thermally annealed Fe-implanted InGaAs/InP films using time-resolved terahertz spectroscopy. The samples were fabricated from crystalline InGaAs films amorphized with Fe ions implantation. The rapid thermal annealing of the InGaAs layer induces solid recrystallization through the formation of polycrystalline grains whose sizes are shown to increase with increasing annealing temperature within the 300–700 °C range. Based on the influence of the laser fluence, the temporal profile of the time-resolved photoconductivity was reproduced using a system of rate equations that describe the photocarrier dynamics in terms of a capture/recombination mechanism. For annealing temperatures below 500 °C, the capture time is found to be less than 1 ps while the recombination time from the charged states did not exceed 5 ps. However, for higher annealing temperatures, the capture and the recombination times show a continuous increase, reaching 7.1 ps and 1 ns respectively, for the film annealed at 700 °C. Frequency-dependent photoconductivity curves are analyzed via a modified Drude–Smith model that considers a diffusive restoring current and the confining particles’ sizes. Our results demonstrate that the localization parameter of the photocarrier transport model is correlated to the polycrystalline grain size. We also show that a relatively high effective mobility of about 2570 cm 2 V −1 s −1 is preserved in all these Fe-implanted InGaAs films.
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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".