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Record W1994970085 · doi:10.1063/1.4821120

Contactless measurement of electrical parameters and estimation of current-voltage characteristics of Si solar cells using the illumination intensity dependence of lock-in carrierography (photoluminescence) images

2013· article· en· W1994970085 on OpenAlex
Junyan Liu, Alexander Melnikov, Andreas Mandelis

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Applied Physics · 2013
Typearticle
Languageen
FieldEngineering
TopicSilicon and Solar Cell Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials sciencePhotoluminescenceOptoelectronicsVoltageSolar cellSiliconIntensity (physics)Current densityElectrical contactsRadiative transferSpontaneous emissionLaserLight intensityOpticsPhysics

Abstract

fetched live from OpenAlex

A combined theoretical and experimental approach is reported using spectrally windowed lock-in carrierography imaging (lock-in photoluminescence) under variable illumination intensity to provide quantitative contactless measurements of key electrical parameters (photogenerated current density, Jg, open circuit voltage, VOC, and maximum power voltage, Vm) of multicrystalline silicon (m-Si) solar cells in very good agreement with standard electrical measurements. The method is based on a recently developed photocarrier radiative recombination current flux relation which links the optical and electrical characteristics of solar cells. In addition, this approach is shown to yield non-contact all-optical estimates of the solar-cell current-voltage characteristics with the conventional variable load resistance replaced by variable laser intensity.

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.

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 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 score0.086
Threshold uncertainty score0.321

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 head0.018
GPT teacher head0.222
Teacher spread0.204 · 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