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Enregistrement W3214399117 · doi:10.1149/ma2021-024497mtgabs

Degradation of the All-Vanadium Redox Flow Battery in the Presence of Metal Impurities

2021· article· en· W3214399117 sur OpenAlexaff
Maedeh Pahlevaninezhad, Majid Pahlevani, Edward P.L. Roberts

Notice bibliographique

RevueECS Meeting Abstracts · 2021
Typearticle
Langueen
DomaineChemical Engineering
ThématiqueCatalysis and Oxidation Reactions
Établissements canadiensQueen's UniversityUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésVanadiumRedoxDegradation (telecommunications)Flow batteryImpurityMetalInorganic chemistryBattery (electricity)Materials scienceChemistryChemical engineeringMetallurgyElectrodeElectrolyteThermodynamicsComputer scienceOrganic chemistryPhysical chemistry

Résumé

récupéré en direct d'OpenAlex

Vanadium redox flow batteries (VRFBs) are a promising technology to advance grid scale energy storage and renewable energy generation integration. However, the cost of the electrolyte is a major challenge for implementation of VRFBs [1, 2]. Electrolyte quality and purity have a significant impact on the cell performance and cost. The presence of impurities even at low concentrations in the vanadium electrolyte solution can cause the instability of the electrolyte and influence cell performance, energy density, operating temperature range, electrochemical kinetics, and production/operation costs [3-6]. However, there is no universal standard for the electrolyte specifications in the market, and a high purity electrolyte is favored by researchers and technology developers to avoid potential detrimental impacts of impurities on the system performance. There is thus a need for improved understanding of the impact of electrolyte impurities on the degradation of VRFBs is vital for commercialization of VRFBs [7]. This study aims to evaluate the effect of iron, aluminum, and manganese ions (Mn 2+ , Fe 2+ and Al 3+ ) on the VRFB performance and the degradation of materials used in the VRFB cell. The battery performance was evaluated using a ‘zero-gap’ flow cell with an electrode area of 5 cm 2 . An electrolytic solution containing 1.6 M VOSO 4 solution in 3 M H 2 SO 4 was circulated through the cell. Thermally treated carbon papers were used as the cathode and anode electrodes. For charge-discharge experiments, constant current density (in the range 10 to 80 mA cm −2 ) was applied with 1.65 and 0.8 V as upper and lower voltage limits. The effects of each impurity were studied at 0.1 M concentrations through charge-discharge experiments. Material characterization analysis (SEM-EDS, XRD, Raman spectroscopy, and UV-Vis) were conducted before and after cycling to provide a better understanding of the effects of the impurities on the electrode, membrane, and electrolyte degradation. Based on the results obtained from these experiments, the effects of each impurities in the electrolyte can be ascertained providing an important reference for electrolyte manufacturing and regeneration. Figure 1 compares the morphologies of the carbon paper electrodes used in the positive and negative sides of the VRFB, before and after 200 cycles of operation, captured by SEM (Figure 1a, 1b). Carbon papers have a smooth fiber surface with small flakes scattered on the surface. The surface of the fresh carbon paper was smooth as shown in Fig. 1a. In the absence of impurities, the electrode morphology appears to be almost unchanged by after 200 cycles, although the surface of the carbon fibers may be slightly rougher. However, a different structure was observed are cycling with an electrolyte containing Al 3+ impurity ions. A solid phase has blocked the electrode pores and precipitated on the active surface area of the electrode. This precipitate adhered to the carbon paper electrode surface and changed the surface structure, hindering interfacial contact between the electrolyte and electrode [8] resulting in performance degradation of VRFB. The observations of electrode morphology changes are consistent with voltammetric analysis and the observed degradation of battery performance. References: [1] A. Parasuraman, T.M. Lim, Ch, Menictas, M. Skyllas-Kazacos, A review of electrolyte additives and impurities in vanadium redox flow batteries, Electrochimica Acta, Vol.101, pp.27-40, 2013. [2] Cao, L., Skyllas-Kazacos, M., Menictas, Ch., Noack, J., A review of electrolyte additives and impurities in vanadium redox flow batteries, Journal of Energy Chemistry, Vol.27, pp.1269-1291, 2018. [3] A.K. Singh., N. Yasri., K. Karan, E.P. L. Roberts, Electrocatalytic Activity of Functionalized Carbon Paper Electrodes and Their Correlation to the Fermi Level Derived from Raman Spectra, ACS Appl. Energy Mater. 2019, 2, 2324−2336. [4] John, J. St., Imergy uses recycled vanadium to cut materials costs for flow batteries, Greentech media, 2014. [5] A.K. Singh, M. Pahlevaninezhad, N. Yasri, E. Roberts, Degradation of Carbon Electrodes in the All-Vanadium Redox Flow Battery, ChemSusChem. (2021),14- 1-13. [6] J.H. Park, J.J. Park, H.J Lee, B.S. Min, J.H. Yang, Influence of Metal Impurities or Additives in the Electrolyte of a Vanadium Redox Flow Battery, Journal of The Electrochemical Society 165(7), page A1263-A1268, 2018. [7] Ding, M., Liu, T., Zhang, Y., Cai, Z., Yang, Y., Yuan, Y., Effect of Fe (III) on the positive electrolyte for vanadium redox flow battery, R. SOC. open sci. 6: 181309, 2019. [8] M. Ding, T. Liu, Y. Zhang, Stability and Electrochemical Performance Analysis of an Electrolyte with Na+Impurity for a Vanadium Redox Flow Battery in Energy Storage Applications, Energy and Fuels. 34 (2020) 6430–6438. 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)0,000
score de la tête « metaresearch » (Gemma)0,001
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 enseignants0,114
Score d'incertitude au seuil0,180

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
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 Opus0,016
Tête enseignante GPT0,235
Écart entre enseignants0,219 · 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
Publié2021
Routes d'admission1
Résumé présentoui

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