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Record W7105694092 · doi:10.5281/zenodo.17604353

Evaluation of the Peroxone Process in a Multiphase Flow Reactor for Enhanced Micropollutant Removal

2025· article· W7105694092 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typearticle
Language
FieldEnvironmental Science
TopicAdvanced oxidation water treatment
Canadian institutionsWestern University
Fundersnot available
KeywordsOzoneHydrogen peroxideProcess (computing)Water treatmentMass transferAdvanced oxidation processHydroxyl radicalFlow (mathematics)

Abstract

fetched live from OpenAlex

This study investigates the peroxone process—a combination of hydrogen peroxide (H₂O₂) andozone (O₃)—in a flow chemistry-based reactor, MITO3X®. The objective was to evaluate theefficiency of hydroxyl radical (·OH) production under various operational parameters, includingpump frequency, water flow rate, and ozone mass concentration. Experiments revealed that 89%of injected ozone dissolved into the water stream, enabling effective reaction with hydrogenperoxide. Residual concentrations of ozone and hydrogen peroxide were measured to determinethe reacted quantities of each reagent. Results highlight the synergistic interaction between O₃ andH₂O₂, demonstrating significant potential for advanced oxidation processes in wastewatertreatment applications.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.507
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.033
GPT teacher head0.295
Teacher spread0.262 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

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