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Enregistrement W3024247149 · doi:10.1149/ma2020-01211269mtgabs

Electrocoagulation with Polarity Reversal for Treatment of Produced Water

2020· article· en· W3024247149 sur OpenAlexaff
Behzad Fuladpanjeh‐Hojaghan, Markus Ingelsson, Mohamed M. Elsutohy, Milana Trifkovic, Edward P.L. Roberts

Notice bibliographique

RevueECS Meeting Abstracts · 2020
Typearticle
Langueen
DomaineEnvironmental Science
ThématiqueWater Quality Monitoring and Analysis
Établissements canadiensUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésElectrocoagulationPassivationElectrodeMaterials scienceDissolutionCathodePolarity reversalWater treatmentAnodeChemical engineeringChlorideFerricChemistryMetallurgyEnvironmental engineeringComposite material

Résumé

récupéré en direct d'OpenAlex

Electrocoagulation (EC) is a cost-effective and reliable technology to treat water and wastewater and has the ability to remove many types of contaminants. Studies have shown that EC operated with aluminum or iron electrodes exhibits higher treatment efficiencies than traditional chemical coagulation with aluminum sulfate or ferric chloride salts [1], [2]. EC involves the in-situ generation of metal hydroxide coagulant by the electrochemical dissolution of sacrificial metal anodes using a direct current, combined with generation of hydroxide ions at the cathode. However, material precipitation on the electrodes associated with long term operation is a major problem hindering the scale up of EC [3]. The growth of electrode surface layers increases passivation, which reduces the treatment efficiency and increases operating costs [4]. Polarity reversal during electrocoagulation, i.e. intermittently changing the direction of the current, is a method that can remove passivation layers on the electrodes formed during direct current operation [5]. The main goal of this study was to investigate the effect of polarity reversal on the reaction and electrode fouling mechanisms as well as the performance of electrocoagulation for the treatment of SAGD produced water. Total organic carbon and silicon removal efficiencies were measured to evaluate treatment performance. Laser scanning confocal microscopy was used to monitor the pH distribution close to electrodes as well as the formation of solid products in an electrocoagulation cell. Customized polycarbonate bench scale reactors were used to study the relationship between coagulant production, polarity reversal frequency, solution composition, and flowrate. The cycle time of the polarity reversals was varied from 5 to 600 s, and the Reynolds numbers was varied between 30 to 200. The Faradaic efficiencies for the coagulant dissolution at different operating conditions were determined by digesting the solid products followed by elemental analysis. The evolution of pH during polarity reversal revealed that at higher frequencies or higher flow rates, the thickness of the interfacial pH boundary layer was lower. The quantification of pH was used to study the effect of pH on passivation layer stability. It was found that at higher frequencies, Faradaic efficiencies were lower for EC with iron electrodes, whereas increased efficiencies were observed for aluminum electrodes due to increased susceptibility to non-Faradaic corrosion. EC using aluminum electrodes (Al-EC), employing polarity reversal at all frequencies led to a reduction in cell voltage and therefore a reduction in the required energy for treatment. References [1] M. Eyvaz, M. Kirlaroglu, T. S. Aktas, and E. Yuksel, “The effects of alternating current electrocoagulation on dye removal from aqueous solutions,” Chem. Eng. J. , vol. 153, no. 1–3, pp. 16–22, 2009. [2] P. K. Holt, G. W. Barton, M. Wark, and C. A. Mitchell, “A quantitative comparison between chemical dosing and electrocoagulation,” Colloids Surfaces A Physicochem. Eng. Asp. , vol. 211, no. 2–3, pp. 233–248, 2002. [3] S. Garcia-Segura, M. M. S. G. Eiband, J. V. de Melo, and C. A. Martínez-Huitle, “Electrocoagulation and advanced electrocoagulation processes: A general review about the fundamentals, emerging applications and its association with other technologies,” Journal of Electroanalytical Chemistry , vol. 801. pp. 267–299, 2017. [4] C. M. van Genuchten, S. R. S. Bandaru, E. Surorova, S. E. Amrose, A. J. Gadgil, and J. Peña, “Formation of macroscopic surface layers on Fe(0) electrocoagulation electrodes during an extended field trial of arsenic treatment,” Chemosphere , vol. 153, pp. 270–279, 2016. [5] M. Eyvaz, “Treatment of brewery wastewater with electrocoagulation: Improving the process performance by using alternating pulse current,” Int. J. Electrochem. Sci. , vol. 11, no. 6, pp. 4988–5008, 2016.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,032
Score d'incertitude au seuil0,226

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,031
Tête enseignante GPT0,249
Écart entre enseignants0,218 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2020
Routes d'admission1
Résumé présentoui

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