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Record W4283707847 · doi:10.3390/nanoenergyadv2030010

Alternative Uses of Luminescent Solar Concentrators

2022· article· en· W4283707847 on OpenAlexafffund
Daniele Benetti, Federico Rosei

Bibliographic record

VenueNanoenergy Advances · 2022
Typearticle
Languageen
FieldChemistry
TopicPhotochemistry and Electron Transfer Studies
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsPhotovoltaic systemOptoelectronicsSolar cableEngineering physicsWindow (computing)Solar cellMaterials sciencePlanarPhotovoltaic thermal hybrid solar collectorProcess engineeringSolar mirrorElectrical engineeringEngineeringComputer science

Abstract

fetched live from OpenAlex

Over the last decade, the field of luminescent solar concentrators (LSC) has experienced significant growth, as noted by the increasing number of studies. However, so far, most of the devices developed have only been employed in a simple planar configuration coupled with silicon photovoltaic solar cells. This type of device is essentially a solar window whose main objective is to produce electrical power. However, due to the intrinsic nature of LSC, that is, the ability to absorb, downshift and concentrate the solar radiation that impinges on it, this photonic device can be used in alternative ways. In particular, in this review, we will explore several non-conventional applications in which LSCs are used successfully, including as solar bioreactors for algae development, photo reactors for organic synthesis, and as greenhouses.

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)0.000
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: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.233
Teacher spread0.225 · 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

Citations22
Published2022
Admission routes2
Has abstractyes

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