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Record W4394688480

Development of submillimeter multijunction cells for concentrator photovoltaics (micro-CPV) and assessment of their robustness

2020· preprint· fr· W4394688480 on OpenAlexaff
Pierre Albert

Bibliographic record

Venuetheses.fr (ABES) · 2020
Typepreprint
Languagefr
FieldEngineering
Topicsolar cell performance optimization
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPhotovoltaicsConcentratorRobustness (evolution)Materials scienceOptoelectronicsPhotovoltaic systemEngineering physicsAerospace engineeringOpticsPhysicsElectrical engineeringEngineeringChemistry
DOInot available

Abstract

fetched live from OpenAlex

Les dispositifs photovoltaïques, dominés par les panneaux en silicium, ont su évoluer pour proposer aujourd’hui des coûts d’électricité concurrentiels aux sources fossiles. Parmi les technologies émergentes, le photovoltaïque à concentration (CPV pour Concentrator Photovoltaics) repose sur l’utilisation de systèmes optiques (miroirs ou lentilles) qui concentrent la lumière sur des cellules de faibles dimensions (< cm2) mais très efficaces (> 40%). Malgré les performances élevées des modules CPV, cette technologie n’a pas su s’imposer en raison d’un coût élevé découlant de limitations technologiques (gestion thermique, pertes résistives…). Le micro-CPV promet de répondre à ces limitations en se basant sur l’utilisation de microcellules (< mm2). Cependant, des défis restent à relever : les procédés de fabrication et d’assemblage des microcellules doivent être adaptés, en s’inspirant de la microélectronique notamment, pour permettre de fortes efficacités et un coût restreint. Aussi, la fiabilité de ce nouveau type de dispositifs n’est pas connue. Ce mémoire de thèse a l’ambition de traiter de ces sujets, en se focalisant particulièrement sur les procédés de fabrication critiques.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.036
GPT teacher head0.254
Teacher spread0.218 · 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 teacher head, not a consensus.

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

Citations0
Published2020
Admission routes1
Has abstractyes

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