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Record W2013803034 · doi:10.1021/ie050981u

Electrohydraulic Discharge and Nonthermal Plasma for Water Treatment

2005· article· en· W2013803034 on OpenAlexaff
Bruce R. Locke, Masayuki Sato, P. Šunka, Michael R. Hoffmann, J.S. Chang

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2005
Typearticle
Languageen
FieldEngineering
TopicElectrohydrodynamics and Fluid Dynamics
Canadian institutionsMcMaster University
Fundersnot available
KeywordsElectric dischargeElectrical currentWastewaterEnvironmental sciencePlasmaWater treatmentCurrent (fluid)Sewage treatmentAqueous solutionProcess engineeringNonthermal plasmaEnvironmental chemistryMaterials scienceChemistryEnvironmental engineeringElectrodeOrganic chemistryElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

The application of strong electric fields in water and organic liquids has been studied for several years, because of its importance in electrical transmission processes and its practical applications in biology, chemistry, and electrochemistry. More recently, liquid-phase electrical discharge reactors have been investigated, and are being developed, for many environmental applications, including drinking water and wastewater treatment, as well as, potentially, for environmentally benign chemical processes. This paper reviews the current status of research on the application of high-voltage electrical discharges for promoting chemical reactions in the aqueous phase, with particular emphasis on applications to water cleaning.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.272
Teacher spread0.241 · 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
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

Citations1,174
Published2005
Admission routes1
Has abstractyes

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