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Record W4379232010 · doi:10.1016/j.joule.2023.05.006

Low-cost photoreactors for highly photon/energy-efficient solar-driven synthesis

2023· article· en· W4379232010 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

VenueJoule · 2023
Typearticle
Languageen
FieldEnergy
TopicTiO2 Photocatalysis and Solar Cells
Canadian institutionsUniversity of Toronto
FundersHelmholtz AssociationKarlsruhe Institute of Technology
KeywordsPhotocatalysisSolar energyProcess engineeringScale (ratio)Environmental scienceRaw materialEfficient energy useEnvironmental economicsNanotechnologyEngineeringComputer scienceMaterials scienceElectrical engineeringChemistryPhysics

Abstract

fetched live from OpenAlex

Solar-driven photocatalytic processes are an emerging field that inspires hopes and dreams of a sustainable future on planet Earth. Using carbon dioxide and water as feedstocks, photocatalytic processes could deliver the energy and carbon feedstock for the future world economy. However, until today, low achieved photocatalytic efficiencies and high costs of photoreaction technology are hurdles for photocatalytic processes at scale. Within this contribution, a low-cost, milli-to-micro structured, and panel-like photoreactor concept, which is suitable for small-scale decentral and large-scale solar farm applications, is introduced. The key feature is a high achieved photocatalytic efficiency at a low design complexity and system cost. The optical modeling and analysis reveal achievable limits and prevalent loss mechanisms cumulating in a concise design guideline for the proposed photoreactors. The guideline comprehensibly establishes a connection between design parameters and performance metrics at a universal level, thereby providing a basis for adaptation and further development in the field of solar-driven photosynthesis.

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 categoriesMeta-epidemiology (narrow), Insufficient 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 score0.299
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)0.0000.001

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 head0.019
GPT teacher head0.242
Teacher spread0.224 · 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