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Record W1850161749 · doi:10.1139/er-2014-0009

Review of the factors relevant to the design and operation of an electrocoagulation system for wastewater treatment

2014· article· en· W1850161749 on OpenAlexaffvenue
Sin Yin Lee, Graham A. Gagnon

Bibliographic record

VenueEnvironmental Reviews · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicAdvanced oxidation water treatment
Canadian institutionsDalhousie University
Fundersnot available
KeywordsElectrocoagulationAlkalinityWastewaterAnodeEnvironmental scienceWater treatmentWaste managementSewage treatmentProcess engineeringChemical oxygen demandCoagulationPulp and paper industryChemistryBiochemical engineeringEnvironmental engineeringElectrodeEngineering

Abstract

fetched live from OpenAlex

Electrocoagulation (EC) is a water treatment technology that has been proven effective at the bench scale for the removal of a wide variety of contaminants from water and wastewater. It is an electrochemical process that involves using a sacrificial anode to generate cations for coagulation. It also evolves hydrogen gas at the cathode, which some researchers have suggested can be used for natural flotation. EC has a number of advantages over conventional chemical coagulation (CC). For instance, solid metal electrodes tend to be easier to move and store than corrosive chemical salts. Furthermore, EC tends to increase solution pH, rather than consume alkalinity like chemical coagulants. However, unlike with CC, there are no standardized procedures for jar testing with EC, or for designing EC systems. Much of the current EC literature focuses on the treatment of a specific water or wastewater using custom EC systems. In an attempt to provide guidance for EC cell design, this paper reviews some of the current literature in four parts: electrodes, electrolyte, power source, and operational parameters.

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 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: Empirical
Teacher disagreement score0.326
Threshold uncertainty score0.267

Codex and Gemma teacher scores by category

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

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 head0.021
GPT teacher head0.253
Teacher spread0.231 · 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.

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

Citations55
Published2014
Admission routes2
Has abstractyes

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