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Enregistrement W2512182327 · doi:10.1149/ma2016-02/3/320

Variation of Coulombic Efficiency Versus Upper Cutoff Potential of Li-Ion Cells with Different Electrolyte Solvents

2016· article· en· W2512182327 sur OpenAlexaff
Jian Xia, Stephen Glazier, J. R. Dahn

Notice bibliographique

RevueECS Meeting Abstracts · 2016
Typearticle
Langueen
DomaineEngineering
ThématiqueAdvancements in Battery Materials
Établissements canadiensDalhousie University
Organismes subventionnairesnon disponible
Mots-clésElectrolyteEthylene carbonateDiethyl carbonateFaraday efficiencyDimethyl carbonateEthylene oxideChemistryElectrodeMaterials scienceAnalytical Chemistry (journal)Chemical engineeringChromatographyOrganic chemistryMethanol

Résumé

récupéré en direct d'OpenAlex

Introduction One of the easiest ways to increase the energy density of Li-ion cells is to increase the operating voltage range. However, the instability of state-of-the-art electrolyte towards high voltage is a great challenge [1, 2]. Electrolyte oxidation reactions can cause gas generation and impedance growth, result in swelling, capacity loss and cell failure. Accurate measurements of the coulombic efficiency (CE) of Li-ion cells are valuable to characterize these parasitic reaction rates occurring between the electrodes and the electrolyte. In this presentation, the impact of the various solvent blends on CE, charge endpoint capacity slippage, cell impedance and gas evolution during ultra high precision coulometry (UHPC) cycling tests were measured at 4.2, 4.4 and 4.5 V. Careful analysis of CE was made to determine the effect of different electrolyte solvents separately on the positive electrode and negative electrode as the upper cut-off voltage increases. Symmetric cells were made to distinguish the effect of the electrolyte solvents on the impedance at the positive or negative electrode. Experimental The pouch cells employed in this study were LaPO4-coated Li[Ni0.4Mn0.4Co0.2]O2 (NMC442)/graphite cells with a capacity of 180 mAh balanced for 4.7 V operation. Three electrolyte systems including 2 wt.% PES + 1 wt.% DTD + 1 wt.% TTSPi (PES 211) in 1M LiPF6 ethylene carbonate (EC):ethyl methyl carbonate (EMC) 3:7, 2 wt.% PES in 1M LiPF6 fluoroethylene carbonate (FEC) and bis(2,2,2-trifluoroethyl) carbonate (TFEC) 1:1 and 2 wt.%VC + 2 wt.% TAP in 1M LiPF6 sulfolane (SL):EMC 3:7 were chosen for this study. The cells then underwent a formation protocol during which they were opened and re-vacuum sealed at 3.5 V and 4.5 V to remove any gas generated during the first charge. After formation, cells were moved to Ultra High Precision Charger (UHPC) and cycled 15 times using “barn-charge” protocols [3]. After UHPC cycling, these cells were opened in the glovebox where symmetric cells were made. The detailed procedure for making symmetric cells has been described by Petibon et al.[4]. Some cells were studied using battery isothermal calorimetry as outlined by Downie et al. [5] Results and discussion Figure 1a shows the fractional charge endpoint capacity slippage per hour and the fractional capacity fade per hour plotted versus upper cutoff potential for cells containing EC:EMC, FEC:TFEC as well as SL:EMC electrolytes. Figure 1a allows one to determine which parasitic reactions, electrolyte oxidation at the positive electrode or Li consumption in the SEI at the negative electrode, play the dominant role in reducing the coulombic efficiency (CE) or increasing 1-CE when the upper cutoff potential increases [3]. Figure 1a shows that the fractional slippage per hour (positive electrode) increases dramatically when the upper cut-off potential increases from 4.2 V to 4.5 V, while, by contrast, the fractional fade per cycle (negative electrode) does not change dramatically with potential. Figure 1a shows the FEC:TFEC electrolyte has smaller slippage but higher capacity fade rate compared to SL:EMC or EC:EMC electrolyte at high voltages. This means the FEC:TFEC electrolyte partially fixes the positive side (small fractional slippage per hour) but has problems at the negative electrode side (larger fractional fade per hour). Figures 1b, 1c and 1d show the area-specific Nyquist plots of negative and positive electrode symmetric cells as well as full coin cells constructed from electrodes after UHPC cycling tests. Figures 1b to 1d show that cells containing FEC:TFEC electrolyte have much smaller positive impedance but higher negative electrode impedance, compared to cells containing SL:EMC and EC:EMC electrolytes after UHPC cycling. Figures 1b to 1d further prove that the benefit of using FEC:TFEC electrolyte is mainly on the positive side by hindering the electrolyte oxidation at the positive electrode/electrolyte interface. Microcalorimetry results which support this interpretation will also be shown. References L. Ma, J. Xia and J. R. Dahn, J. Electrochem. Soc., 161, A2250 (2014). K.J. Nelson, J. Xia and J.R. Dahn, J. Electrochem. Soc., 161, A1884 (2014). J. Xia, M. Nie, L. Ma and J. R. Dahn, J. Power Sources, 306, (2016) 233. R. Petibon, C. P. Aiken, N. N. Sinha, J. C. Burns, H. Ye, C. M. VanElzen, G. Jain, S. Trussler, and J. R. Dahn J. Electrochem. Soc., 160, A117 (2013). L.E. Downie and J. R. Dahn, J. Electrochem. Soc. 161, A1782 (2014). Figure captions Figure 1 a) Fractional charge endpoint capacity per hour and fractional fade per hour plotted versus the upper cutoff potential for the NMC442/graphite pouch cells with different electrolytes. The area-specific Nyquist plot of b) negative electrode symmetric cells, c) positive electrode symmetric cells and d) full coin cells made from the NMC442 pouch cells after the UHPC cycling to 4.5 V. 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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut 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 enseignants0,003
Score d'incertitude au seuil0,009

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0010,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

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 Opus0,007
Tête enseignante GPT0,213
Écart entre enseignants0,206 · 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 source (Gemma direct ou Codex distillé), 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
Publié2016
Routes d'admission1
Résumé présentoui

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