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Record W4301778756 · doi:10.48550/arxiv.1707.08023

Minority carrier diffusion lengths and mobilities in low-doped n-InGaAs\n for focal plane array applications

2017· preprint· en· W4301778756 on OpenAlexaff
Alexandre W. Walker, M. W. Denhoff

Bibliographic record

VenuearXiv (Cornell University) · 2017
Typepreprint
Languageen
FieldEngineering
TopicAdvanced Semiconductor Detectors and Materials
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsDopingDiffusionMaterials scienceDiodeOptoelectronicsElectron mobilityDark currentPhotodetectorOpticsPhysics

Abstract

fetched live from OpenAlex

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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.250
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.037
GPT teacher head0.195
Teacher spread0.159 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2017
Admission routes1
Has abstractyes

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