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Record W2028775956 · doi:10.1021/ie0505763

Photocatalytic Process for CO<sub>2</sub> Emission Reduction from Industrial Flue Gas Streams

2006· article· en· W2028775956 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

VenueIndustrial & Engineering Chemistry Research · 2006
Typearticle
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsUniversity of Regina
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhotocatalysisFlue gasCarbon dioxideEnvironmental scienceGreenhouse gasMethaneSolar energyProcess (computing)Process engineeringWaste managementMaterials scienceChemistryComputer scienceCatalysisEngineering

Abstract

fetched live from OpenAlex

At present, carbon dioxide (CO 2 ) is the largest contributor among greenhouse gases. This article addresses the potential application of photocatalysis to the reduction of CO 2 emissions from industrial flue gas streams. Not only does this process remove CO 2, but it can also convert CO 2 into other chemical commodities such as methane, methanol, and ethanol. In addition, the photocatalytic process can consume less energy than conventional methods by harnessing solar energy. Given these advantages, photocatalysis is an attractive alternative for CO 2 capture. This article reviews the principle of photocatalysis; existing literature related to photocatalytic CO 2 reduction; and the effects of important parameters on process performance, including light wavelength and intensity, type of reductant, metal-modified surface, temperature, and pressure. Finally, we discuss various system configurations for UV and solar photocatalytic reactors. The advances in photocatalysis technology indicate a promising application potential for significant reductions of CO 2 emissions and a positive impact on climate change effects.

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)0.001
metaresearch head score (Gemma)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.065
GPT teacher head0.343
Teacher spread0.278 · 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