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Record W4255420813 · doi:10.1515/iupac.71.0001

Terminology, Relative Photonic Efficiencies and Quantum Yields in Heterogeneous Photocatalysis. Part I: Suggested ProtocolA draft version of this paper was published previously in part in [J. Photochem. Photobiol. A: Chem., J. Adv. Oxid. Technol.; IAPS Newsletter and EPA Newsletter] to solicit comments and critiques from the scientific and engineering community. Moreover, during the preparation the draft proposal was submitted to a number of distinguished photochemists and photocatalycists to obtain their views.

2016· dataset· en· W4255420813 on OpenAlexaff
Nick Serpone, Angela Trovato Salinaro

Bibliographic record

VenueIUPAC Standards Online · 2016
Typedataset
Languageen
FieldChemical Engineering
TopicCatalysis and Oxidation Reactions
Canadian institutionsConcordia University
Fundersnot available
KeywordsPhotocatalysisQuantumQuantum yieldPhotonTerminologyProcess (computing)Simple (philosophy)Yield (engineering)Computer sciencePhotonicsChemistryPhysicsQuantum mechanicsCatalysisEpistemologyThermodynamicsPhilosophyOrganic chemistryFluorescence

Abstract

fetched live from OpenAlex

The term photocatalysis is one amongst several in a quagmire of labels used to describe a photon-driven catalytic process; a simple description of photocatalysis is proposed herein. Other labels such as quantum yield and/or quantum efficiency used in solid/liquid and solid/gas heterogeneous photocatalytic systems to express process efficiencies have come to refer (incorrectly) to the ratio of the rate of a given event to the rate of incident photons impinging on the reactor walls and typically for broadband radiation. There is no accord on the expression for process efficiency. At times quantum yield is defined; often, it is ill-defined and more frequently how it was assessed is not described. This has led to much confusion in the literature, not only because of its different meaning from homogeneous photochemistry, but also because the description of photon efficiency precludes comparison of results from different laboratories owing to variations in light sources, reactor geometries, and overall experimental conditions. The previously reported quantum yields are in fact apparent quantum yields, i.e. lower limits of the true quantum yields. We address this issue and argue that any reference to quantum yields or quantum efficiencies in a heterogeneous medium is inadvisable until the number of photonsabsorbed by the light harvester (the photocatalyst) is known. A practical and simple alternative is proposed for general use and in particular for processes employing complex reactor geometries: the concept ofrelative photonic ef ficiency (ξr) is useful to compare process efficiencies using a given photocatalyst material and a given standard test molecule. A quantum yield can subsequently be calculated since Ф = ξr Фphenol, where Фphenol denotes the quantum yield for the photocatalyzed oxidative transformation of phenol used as the standard secondary actinometer and Degussa P-25 TiO2 as the standard photocatalyst. For heterogeneous suspensions (only), an additional method to determine quantum yields Ф is also proposed.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.007
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.008
Science and technology studies0.0030.003
Scholarly communication0.0040.005
Open science0.0050.002
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0280.018

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 head0.009
GPT teacher head0.317
Teacher spread0.308 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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