Minority carrier diffusion lengths and mobilities in low-doped n-InGaAs\n for focal plane array applications
Bibliographic record
Abstract
The hole diffusion length in n-InGaAs is extracted for two samples of\ndifferent doping concentrations using a set of long and thin diffused junction\ndiodes separated by various distances on the order of the diffusion length. The\nmethodology is described, including the ensuing analysis which yields diffusion\nlengths between 70 - 85 um at room temperature for doping concentrations in the\nrange of 5 - 9 x 10^15 cm-3. The analysis also provides insight into the\nminority carrier mobility which is a parameter not commonly reported in the\nliterature. Hole mobilities on the order of 500 - 750 cm2/Vs are reported for\nthe aforementioned doping range, which are comparable albeit longer than the\nmajority hole mobility for the same doping magnitude in p-InGaAs. A radiative\nrecombination coefficient of (0.5-0.2)x10^-10 cm^-3s^-1 is also extracted from\nthe ensuing analysis for an InGaAs thickness of 2.7 um. Preliminary evidence is\nalso given for both heavy and light hole diffusion. The dark current of\nInP/InGaAs p-i-n photodetectors with 25 and 15 um pitches are then calibrated\nto device simulations and correlated to the extracted diffusion lengths and\ndoping concentrations. An effective Shockley-Read-Hall lifetime of between\n90-200 us provides the best fit to the dark current of these structures.\n
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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".