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Enregistrement W2807451574 · doi:10.1149/ma2018-01/20/1290

Long-Term Evaluation of Modified Activated Carbon Electrodes for Capacitive Deionization

2018· article· en· W2807451574 sur OpenAlexaff
Adrián Serrano Mora, David P. Wilkinson, Madjid Mohseni

Notice bibliographique

RevueECS Meeting Abstracts · 2018
Typearticle
Langueen
DomaineEngineering
ThématiqueMembrane-based Ion Separation Techniques
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésCapacitive deionizationDesalinationActivated carbonPoint of zero chargeMaterials scienceAdsorptionElectrochemistryElectrodeReverse osmosisChemical engineeringCarbon fibersChemistryMembraneComposite material

Résumé

récupéré en direct d'OpenAlex

Capacitive deionization (CDI) is an emerging electrochemical technology for the desalination of brackish waters (1000 – 15 000 mg L -1 TDS). It offers higher water recoveries and it is less energy intensive than reverse osmosis and thermal distillation, the dominant desalination technologies. CDI relies on the electroadsorption of ions on the electrical double layers formed at the electrode surfaces when a potential is applied. As a consequence, a diluted, purified stream of water is produced. Once the surface is saturated, the potential is removed or reversed, and ions are released back into the solution. This process is performed cyclically, and ideally, it could be carried out indefinitely. However, there are secondary reactions that prevent this from being a reality, and the desalination performance will decay over time. In particular, carbon oxidation modifies the electrode surface over time, thus negatively affecting the electrochemical properties such as resistivity, potential of zero charge (PZC), and surface area [1]–[4]. In addition, the oxygen reduction reaction (ORR) consumes charge that otherwise would have been used to adsorb ions. Despite recent significant advances in materials and cell configurations for CDI, the long-term stability of most materials developed has not been studied. As a consequence, there are a number of materials and design approaches reported in literature with enhanced initial salt adsorption capacities but lack any long-term evaluation of the CDI performance. In this research, the utilization of activated carbon based electrodes for long-term capacitive deionization is explored. Specifically, the effect of electrode additives on the improvement of the cycling stability is investigated. The function of these additional materials is to promote oxygen reduction in order to reduce the availability of oxygen that can be incorporated (i.e., by oxidation) onto the electrode surface, and therefore increase the long-term performance [5]–[7]. It is presumed that, if these secondary reactions can be controlled, the process of oxidation will be delayed to some extent, therefore extending the life of the electrodes and offering acceptable desalination for a longer period of time. Non-precious additives which are able to promote the ORR are incorporated into a baseline electrode at different loadings, and their electrochemical properties including their ORR potential are monitored during prolonged cycling in a representative TDS solutions, i.e., as NaCl. Moreover, the disruption of the porous network by these additives is assessed by scanning electron microscopy (SEM) and other characterization techniques. Results from this study will provide insight into the feasibility of using activated carbons for long-term capacitive deionization. Furthermore, the inclusion of additives could offer a relatively simple and cheap solution to the challenge of carbon oxidation, and result in a more robust and efficient desalination technology. References [1] I. Cohen, E. Avraham, Y. Bouhadana, A. Soffer, and D. Aurbach, “Long term stability of capacitive de-ionization processes for water desalination: The challenge of positive electrodes corrosion,” Electrochim. Acta , vol. 106, pp. 91–100, Sep. 2013. [2] F. Duan, X. Du, Y. Li, H. Cao, and Y. Zhang, “Desalination stability of capacitive deionization using ordered mesoporous carbon: Effect of oxygen-containing surface groups and pore properties,” Desalination , vol. 376, pp. 17–24, 2015. [3] E. Avraham, M. Noked, Y. Bouhadana, A. Soffer, and D. Aurbach, “Limitations of charge efficiency in capacitive deionization processes III: The behavior of surface oxidized activated carbon electrodes,” Electrochim. Acta , vol. 56, no. 1, pp. 441–447, 2010. [4] Y. Bouhadana, M. Ben-Tzion, A. Soffer, and D. Aurbach, “A control system for operating and investigating reactors: The demonstration of parasitic reactions in the water desalination by capacitive de-ionization,” Desalination , vol. 268, no. 1, pp. 253–261, 2011. [5] P. Srimuk, M. Zeiger, N. Jäckel, A. Tolosa, B. Krüner, S. Fleischmann, I. Grobelsek, M. Aslan, B. Shvartsev, M. E. Suss, and V. Presser, “Enhanced performance stability of carbon/titania hybrid electrodes during capacitive deionization of oxygen saturated saline water,” Electrochim. Acta , vol. 224, pp. 314–328, Jan. 2017. [6] A. G. El-Deen, N. A. M. Barakat, K. A. Khalil, M. Motlak, and H. Yong Kim, “Graphene/SnO2 nanocomposite as an effective electrode material for saline water desalination using capacitive deionization,” Ceram. Int. , vol. 40, no. 9 PART B, pp. 14627–14634, Nov. 2014. [7] A. G. El-Deen, N. A. M. Barakat, and H. Y. Kim, “Graphene wrapped MnO2-nanostructures as effective and stable electrode materials for capacitive deionization desalination technology,” Desalination , vol. 344, pp. 289–298, Jul. 2014. Figure 1

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)0,001
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 enseignants0,024
Score d'incertitude au seuil0,645

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
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 Opus0,036
Tête enseignante GPT0,297
Écart entre enseignants0,261 · 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

Citations0
Publié2018
Routes d'admission1
Résumé présentoui

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