MétaCan
Menu
Back to cohort
Record W2018242409 · doi:10.1021/es803253c

Catalytic Ozonation of Selected Pharmaceuticals over Mesoporous Alumina-Supported Manganese Oxide

2009· article· en· W2018242409 on OpenAlexfundno aff
Li Yang, Chun Hu, Yulun Nie, Jiuhui Qu

Bibliographic record

VenueEnvironmental Science & Technology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsnot available
FundersPublic Health Agency of Canada
KeywordsChemistryCatalysisFourier transform infrared spectroscopyAqueous solutionMesoporous materialInorganic chemistryAttenuated total reflectionMesoporous silicaNuclear chemistryManganeseReactivity (psychology)OzoneInfrared spectroscopyChemical engineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Catalytic ozonation of five pharmaceutical compounds (PhACs)-phenazone, ibuprofen, diphenhydramine, phenytoin, and diclofenac sodium in alumina-supported manganese oxide (MnOx) suspension was carried out with a semicontinuous laboratory reactor. MnOx supported by mesoporous alumina (MnOx/MA) was highly effective in mineralizing the PhACs in aqueous solution. Fourier transform infrared (FTIR) spectroscopy and in situ attenuated total reflection FTIR (ATR-FTIR) spectroscopy were used to examine the interaction of ozone with different catalysts undervarious conditions. The crucial active sites, surface oxide species at 1380 cm(-1), were formed by the interaction of ozone with Lewis acid sites on the alumina surface. New surface hydroxyl groups at 2915 and 2845 cm(-1) were produced by the interaction of the catalyst and ozone in aqueous suspension and became active sites in the presence of MnOx. The introduction of MnOx enhanced the formation and activation of surface hydroxyl groups, causing higher catalytic reactivity. On the basis of these findings, a reaction mechanism is proposed for the catalytic ozonation of PhACs in MnOx/MA suspension.

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 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), Science and technology studies, 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
Bibliometrics0.0000.002
Science and technology studies0.0000.004
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.011
GPT teacher head0.280
Teacher spread0.270 · 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 teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations229
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueEnvironmental Science & TechnologySame topicPharmaceutical and Antibiotic Environmental ImpactsFrench-language works237,207