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Photocatalysis

2000· other· en· W4243449078 on OpenAlex
Nick Serpone

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

VenueKirk-Othmer Encyclopedia of Chemical Technology · 2000
Typeother
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsConcordia University
Fundersnot available
KeywordsPhotocatalysisTitanium dioxideCatalysisUltravioletUltraviolet lightPhotochemistryChemistryAqueous solutionSubstrate (aquarium)SemiconductorCarbon dioxideEnvironmental chemistryChemical engineeringMaterials scienceOrganic chemistryOptoelectronicsEcology

Abstract

fetched live from OpenAlex

Abstract When photons are implicated in a catalytic reaction, the system becomes a photocatalytic one. The catalyst may accelerate the photoreaction by interaction either with a substrate in its ground or an excited state, and/or with the primary photoproduct. Although not yet commercially viable, photocatalytic processes may provide an alternative to the traditional routes to water purification, destroying bacterial substances, and dissolved organics in waste streams. The process can be homogeneous, employing an oxidant and ultraviolet light, or heterogeneous, utilizing air, semiconductor particles (the photocatalyst), and ultraviolet radiation. These various pathways are discussed. The mechanistic details of using semiconductor particles as light harvesters is reviewed, as are the mechanisms by which the photooxidation occurs. Examples of aqueous dissolved organic compounds photooxidized to carbon dioxide and water in the presence of titanium dioxide, air, and near‐ultraviolet radiation are given.

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), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.233
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.005
GPT teacher head0.245
Teacher spread0.240 · 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