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Record W2011862192 · doi:10.1016/j.egypro.2014.08.081

Dynamic Photoluminescence Lifetime Imaging for Injection-dependent Lifetime Measurements

2014· article· en· W2011862192 on OpenAlexfundno aff
Sandra Herlufsen, Karsten Bothe, Rolf Brendel, Jan Schmidt

Bibliographic record

VenueEnergy Procedia · 2014
Typearticle
Languageen
FieldEngineering
TopicSilicon and Solar Cell Technologies
Canadian institutionsnot available
FundersInstitute of Gender and Health
KeywordsPhotoluminescenceCarrier lifetimeMaterials scienceRange (aeronautics)Dynamic rangeExcitationCharge-carrier densityOptoelectronicsSiliconOpticsPhysicsElectrical engineeringDopingComposite materialEngineering

Abstract

fetched live from OpenAlex

We investigate the impact of an injection-dependent carrier lifetime in crystalline silicon on dynamic photoluminescence lifetime imaging (dynamic PLI). Although the dynamic lifetime approach is a technique that evaluates the time-dependence of a quantity proportional to the excess carrier density, it is only weakly influenced by the injection-level dependence of the lifetime. The reason for the little impact is the fact that the evaluation of dynamic PLI measurements does not only involve the decay of the carrier density, as it is common for photoconductance decay measurements, but also the increase of the carrier density directly after switching on the excitation source. In this contribution, we present injection-dependent lifetime measurements that are acquired with the camera-based dynamic PLI technique. We find that the deviation of the actual steady-state carrier lifetime from the lifetime obtained with dynamic PLI is less than 20 % for a wide range of measurement conditions.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.008
GPT teacher head0.205
Teacher spread0.197 · 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

Citations6
Published2014
Admission routes1
Has abstractyes

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