MétaCan
Menu
Back to cohort
Record W4416299697 · doi:10.1002/cey2.70106

Comparing the Indoor and Solar Performance of Light‐Concentrating Waveguide‐Encoded Lattice Slim Films

2025· article· en· W4416299697 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCarbon Energy · 2025
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsMcMaster University
FundersIsaac Newton TrustMitacsEuropean CommissionEngineering and Physical Sciences Research CouncilMcMaster University
KeywordsPhotovoltaic systemPhotovoltaicsLattice (music)Light intensitySolar energy

Abstract

fetched live from OpenAlex

ABSTRACT Although multicrystalline Si photovoltaics have been extensively studied and applied in the collection of solar energy, the same systems suffer significant efficiency losses in indoor settings, where ambient light conditions are considerably smaller in intensity and possess greater components of non‐normal incidence. Yet, indoor light‐driven, stand‐alone devices can offer sustainable advances in next‐generation technologies such as the Internet of Things. Here, we present a non‐invasive solution to aid in photovoltaic indoor light collection—radially distributed waveguide‐encoded lattice (RDWEL) slim films (thickness 1.5 mm). Embedded with a monotonical radial array of cylindrical waveguides (±20°), the RDWEL demonstrates seamless light collection (FoV (fields of view) = 74.5°) and imparts enhancements in J SC (short circuit current density) of 44% and 14% for indoor and outdoor lighting conditions, respectively, when coupled to a photovoltaic device and compared to an unstructured but otherwise identical slim film coating.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.699
Threshold uncertainty score0.296

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 head0.008
GPT teacher head0.195
Teacher spread0.188 · 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