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Record W4416143822 · doi:10.1063/5.0289481

Quasi-open circuit response times of single- and multi-junction InGaAs photonic power converters

2025· article· en· W4416143822 on OpenAlexafffund
Osbel Almora, Alexandre W. Walker, D P Wilson, Carmine Pellegrino, Meghan N. Beattie, Lluı́s F. Marsal, David Lackner, Henning Helmers, Karin Hinzer

Bibliographic record

VenueJournal of Applied Physics · 2025
Typearticle
Languageen
FieldEngineering
Topicsolar cell performance optimization
Canadian institutionsUniversity of OttawaNational Research Council Canada
FundersAgencia Estatal de InvestigaciónMinisterio de Ciencia e InnovaciónBundesministerium für Bildung und ForschungGovernment of CanadaGeneralitat de CatalunyaEuropean CommissionCMC Microsystems
KeywordsConvertersPhotonicsPower (physics)Electromagnetic interferenceElectrical impedanceLaserSemiconductor laser theorySemiconductor deviceLaser power scaling

Abstract

fetched live from OpenAlex

Photonic power converters provide an emerging alternative to traditional metallic cabling due to their immunity to electromagnetic interference and for minimizing fire hazards as well as their ability to wirelessly power loads. In this work, we study the electrical response as a function of laser power in single and multi-junction In0.53Ga0,47As-based structures using current–voltage and impedance spectroscopy techniques. The resistance, capacitance, and quasi-open-circuit response times are discussed. Estimated values for single- and ten-junction devices were 314 and 911 ns, respectively, measured under 1520 nm laser radiation with an irradiance of 88 mW cm−2. A methodology with analytical modeling is proposed for comparing single- and multi-junction devices based on the average sub-cell performance. Our analysis provides useful information for the optimization of multi-junction photonic power converters in applications where the device response time is relevant such as simultaneous power and data transfer applications.

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)0.002
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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 science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.222
Teacher spread0.209 · 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
Published2025
Admission routes2
Has abstractyes

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