MétaCan
Menu
Back to cohort
Record W2170926317 · doi:10.1109/ted.2005.843876

Effect of Doped Substrate on GaAs–AlGaAs Interfacial Workfunction IR Detector Response Through Cavity Effect

2005· article· en· W2170926317 on OpenAlexaff
S. G. Matsik, M. B. M. Rinzan, D. G. Esaev, A. G. U. Perera, G. vonWinckel, A. Stintz, Sanjay Krishna, H.C. Liu, M. Byloos, T. Oogarah, G. I. Sproule, K. Liu, M. Buchanan

Bibliographic record

VenueIEEE Transactions on Electron Devices · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSemiconductor Quantum Structures and Devices
Canadian institutionsInstitute for Microstructural Sciences
Fundersnot available
KeywordsResponsivitySubstrate (aquarium)DopingMaterials scienceOptoelectronicsHeterojunctionResonance (particle physics)DetectorQuantum efficiencyAnalytical Chemistry (journal)OpticsPhotodetectorChemistryPhysicsAtomic physics

Abstract

fetched live from OpenAlex

In this paper, results are reported showing response enhancement in GaAs-AlGaAs IR detectors using a doped substrate to increase reflection, enhancing the resonant cavity effect. Responsivity for heterojunction interfacial workfunction detectors grown on semi-insulating (SI) and doped substrates are compared. For a device grown on an SI substrate, a 9-/spl mu/m resonance peak had a response of 1.5 mA/W while a similar device on an n-doped substrate showed 12 mA/W. Also, the difference between response under forward and reverse bias (3 versus 12 mA/W) for the sample grown on the doped substrate, as well as calculated results confirm that the increased response is due to the resonant enhancement. An optimized design for a 15-/spl mu/m peak (24 /spl mu/m 0 response threshold) detector grown on a doped substrate could expect a peak response of 4 A/W with a 50% quantum efficiency and D/sup */ /spl sim/ 2 /spl times/ 10/sup 10/ Jones at the background limited temperature of 50 K.

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 score0.292
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.275
Teacher spread0.266 · 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

Citations0
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueIEEE Transactions on Electron DevicesSame topicSemiconductor Quantum Structures and DevicesFrench-language works237,207