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Record W4403208477 · doi:10.1038/s41524-024-01409-0

Light-harvesting properties of photocatalyst supports—no photon left behind

2024· article· en· W4403208477 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

Venuenpj Computational Materials · 2024
Typearticle
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsUniversity of Toronto
FundersMitacsEidgenössische Technische Hochschule ZürichCMC MicrosystemsFord Motor Company
KeywordsPhotocatalysisPhotonMaterials scienceBusinessOptoelectronicsChemistryOpticsPhysics

Abstract

fetched live from OpenAlex

Abstract In this work, we set out to elucidate the light-harvesting properties of various random and ordered photocatalyst supports (PSs) with different macropore sizes. To accomplish this, we propose two studies of increasing relevance, enabled by computed tomography (CT) reconstructions and ray-tracing COMSOL Multiphysics simulations: (a) a 360-degree light release study approximating a PS situated within a compound parabolic concentrator (CPC) or cylindrical LED reactor with open ends; and (b) the same system as before but with closed ends. The ordered geometry is of interest, as it can be 3D printed at scale with a tailored morphology and porosity, and it can potentially be refined using machine learning models to optimize its light-harvesting properties. As will be shown, the local volumetric light absorption (LVLA) data suggests that an ordered PS with a more open pore interior and a smaller pore exterior would begin to approach the more isophotonic light-harvesting properties of random PSs.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.266
Teacher spread0.248 · 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