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Record W2766815547 · doi:10.4071/isom-2017-poster5_154

Dark Current Leakage in Optoelectronic Hermetic Packages

2017· article· en· W2766815547 on OpenAlexaff
Clara Dionet, Goran Perosevic, Jeff Javier, Sammie Fernandez, Taylor Hurdle, Maziar Moradi, Andrew O. Neely, Kevin Ma, Marwan Albarghouti

Bibliographic record

VenueIMAPSource Proceedings · 2017
Typearticle
Languageen
FieldEngineering
TopicElectrostatic Discharge in Electronics
Canadian institutionsSemtech (Canada)
Fundersnot available
KeywordsPhotodetectorDark currentOptoelectronicsMaterials scienceLeakage (economics)FabricationMedicine

Abstract

fetched live from OpenAlex

Abstract In this work, the root cause of the increase in dark current occurring over time at high temperature in hermetic packages, such as those used in optoelectronic devices, was investigated. It was observed that hermetic Receiver Optical Subassembly (ROSA) devices show continuously increasing dark current when stressed and monitored at 85°C over an extended period of time, reaching, in some cases, values greater than 500nA. However, this increase in leakage current was recoverable once the package seal is broken, and this behavior was found to be very repeatable. Photodetectors from two different suppliers were tested and found to have dark current which is dependent on the fabrication process, as the photodetector (PD) from supplier 1 (PD1) showed three times higher leakage than the photodetector from supplier 2 (PD2). The main difference between the two photodetectors is that the polyimide layer in PD1 in significantly greater than in PD2. It was also observed that 48 hour pre-seal baking at 120°C keeps the dark current constant at much lower levels, but does not stop it completely from rising over time.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.008
GPT teacher head0.248
Teacher spread0.241 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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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