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Record W2791162972 · doi:10.1111/php.12913

A Green Method to Determine VUV (185 nm) Fluence Rate Based on Hydrogen Peroxide Production in Aqueous Solution

2018· article· en· W2791162972 on OpenAlexaff
Laxiang Yang, Mengkai Li, Wentao Li, James R. Bolton, Zhimin Qiang

Bibliographic record

VenuePhotochemistry and Photobiology · 2018
Typearticle
Languageen
FieldEnergy
TopicTiO2 Photocatalysis and Solar Cells
Canadian institutionsUniversity of Alberta
FundersMinistry of Science and Technology of the People's Republic of ChinaNational Natural Science Foundation of China
KeywordsActinometerChemistryHydrogen peroxideAqueous solutionFluenceQuantum yieldProduction rateUltravioletAnalytical Chemistry (journal)IrradiationPhotochemistryKineticsOxygenMaterials scienceFluorescenceOpticsOptoelectronicsChromatographyPhysical chemistryPlasmaOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

Abstract A mini‐fluidic vacuum ultraviolet/ultraviolet (VUV/UV) photoreaction system (MVPS) was developed in our previous study. Based on the MVPS, a green method to determine VUV fluence rate has been developed using the production rate of H2O2 when water is exposed to 185 nm VUV. The H2O2 production followed pseudo‐zero‐order reaction kinetics well over the first 10 min of VUV/UV exposure. This new method was well calibrated with a standard cis‐cyclooctene cis–trans photoisomerization actinometer as recommended by the International Union of Pure and Applied Chemistry. The apparent quantum yield for H2O2 production by 185 nm VUV irradiation of water was determined to be 0.024 ± 0.002. As the solution pH increased from 5.0 to 8.0, the H2O2 production rate decreased from 0.83 to 0.40 μm min–1. Dissolved oxygen had a negligible influence on the H2O2 production. This study proposes a novel VUV fluence rate determination method with advantages of nontoxicity, low detection limits, low costs and convenience, and it can be used as a good alternative to traditional actinometers.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.017
GPT teacher head0.267
Teacher spread0.250 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations37
Published2018
Admission routes1
Has abstractyes

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