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PERFORMANCE ANALYSIS OF NANOSCALE-GAP THERMOPHOTOVOLTAIC ENERGY CONVERSION DEVICES

2011· article· en· W2298630029 on OpenAlex

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

Venuenot available
Typearticle
Languageen
FieldEngineering
Topicsolar cell performance optimization
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsThermophotovoltaicMaterials scienceOptoelectronicsRadiator (engine cooling)Thermal radiationGallium antimonideHeat transferWide-bandgap semiconductorBand gapOpticsCommon emitterMechanics

Abstract

fetched live from OpenAlex

The performance characteristics of nanoscale-gap thermophotovoltaic (nano-TPV) power generators are investigated via a coupled near-field thermal radiation, charge and heat transport formulation. A nano-TPV device consisting of a tungsten radiator, maintained at 2000 K, and cells made of indium gallium antimonide is considered; the thermal management system is modeled assuming a convective boundary with a fluid temperature fixed at 293 K. Results reveal that in order to maintain the cell at room temperature, a heat transfer coefficient as high as 105 Wm−2K−1 is required for nanometer-size vacuum gaps. In future studies, near-field radiation spectral conditions leading to optimal performance characteristics of the device will be investigated.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.590
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.015
GPT teacher head0.180
Teacher spread0.165 · 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

Quick stats

Citations2
Published2011
Admission routes1
Has abstractyes

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