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Enregistrement W2936291552 · doi:10.1149/ma2019-03/2/207

Temperature Dependent Electrochemical Impedance Spectroscopy Studies of Lithium Ion Batteries

2019· article· en· W2936291552 sur OpenAlexaff
A. S. Keefe, J. R. Dahn

Notice bibliographique

RevueECS Meeting Abstracts · 2019
Typearticle
Langueen
DomaineEngineering
ThématiqueAdvanced Battery Technologies Research
Établissements canadiensDalhousie University
Organismes subventionnairesnon disponible
Mots-clésElectrolyteDielectric spectroscopyElectrodeLithium (medication)Materials scienceIonic conductivityElectrochemistryConductivityAnalytical Chemistry (journal)ChemistryChemical engineeringChromatography

Résumé

récupéré en direct d'OpenAlex

Impedance in lithium ion cells grows over the lifetime of the cell and can be a large contributing factor to cell failure. This study attempts to understand impedance growth by looking at the factors that contribute to cell impedance. Separating these factors and understanding the origins of impedance in cells provides insight into how and why cells fail and could lead to improvements in cell cycling and lifetime. The positive and negative electrode solid electrolyte interphase (SEI) layer, contact resistances, degradation of electrical conductivity in electrodes, and loss of ionic conductivity in electrolyte are all contributing factors to overall cell impedance. However, separating these factors can be difficult in impedance spectroscopy measurements. In this study, Li[Ni0.5Mn0.3Co0.2]O2/artificial graphite pouch cells were used with 1.2M LiPF6 in EC:DMC 3:7 (w:w) electrolyte containing 2 wt% vinylene carbonate (VC), 1 wt% lithium difluorophosphate (LiPF2O2 – called LFO here), or no additive as a control electrolyte. Cells were formed to 4.2 V or 4.4 V and were either left at top of charge or discharged to 3.8 V before disassembly. See Table 1 for a full list of electrolytes and voltages of the cells used in this study. Following pouch cell formation, symmetric cells were made from two positive electrodes or two negative electrodes harvested from the full lithium ion cell to study each electrode separately. Full coin cells were also made with one positive and one negative electrode. Electrochemical impedance spectroscopy (EIS) was performed at a range of temperatures to facilitate the separation of impedance factors. Measurements were taken at -10°C, 0°C, 10°C, 20°C, 30°C, and 40°C. Spectra were measured at 10°C at the beginning, middle, and end of the experiments to ensure repeatability. Figure 1 is an example of measurements taken from one disassembled pouch cell. Note that only -10°C, 10°C, 30°C, and 40°C are shown in this figure for simplicity. The left column in Figure 1 shows the Nyquist plots for negative symmetric cells at the various temperatures. The middle and right columns show the positive symmetric cells and the full cells respectively. The middle, positive symmetric cell column contains two spectra, one for a cell made with aluminum hardware and the other with steel hardware, labelled (A) and (S) respectively. Data from one symmetric cell is shown per type of symmetric cell, however several cells of each type were made from each pouch cell to ensure repeatability of the data. The low frequency (right side) semicircular feature in these Nyquist plots may be attributed to charge transfer resistance between the electrolyte and the electrodes. The charge transfer resistance used here lumps together ion desolvation, ion transfer through the SEI and combination with an electron at the inner SEI surface. The high frequency (left side) semicircular feature may be attributed to contact resistance. The steel and aluminum hardware positive symmetric cell data have very similarly sized low frequency features – representing charge transfer resistance, which should not change at all with hardware. However, the high frequency feature varies substantially between the two symmetric cells, indicating that this feature is in fact due to contact resistance. In general, for all spectra, charge transfer resistance increases dramatically in magnitude with decreasing temperature, while the contact resistance remains almost constant. Therefore, Figure 1 strongly suggests that researchers interested in studying charge transfer resistance with minimal confusion should make their measurements at low temperature. The full cells have three features, which represent a combination of charge transfer and contact resistances from the negative and positive electrodes in combination. This data shows that the majority of cell impedance growth as temperature decreases originates from the positive electrode SEI. Equivalent electric circuit models have been used to model the impedance behavior of the symmetric cells. Circuit models include resistance factors representing charge transfer resistance, contact resistance, and solution resistance, as well as imperfect capacitances (constant phase elements) representing electrochemical double layers. Impedance spectra have been fitted using these simple circuit models. Using this technique, charge transfer resistances, contact resistances, solution resistances, and double layer capacitance values can be obtained for positive and negative electrodes/SEI layers separately as a function of temperature. Activation energies for the charge transfer between SEI and electrolyte have been extracted from charge transfer resistance measurements as they follow an Arrhenius temperature dependence. Capacitance values associated with double layers at the SEI/electrolyte interface were also be obtained through these measurements and these will be discussed. 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)0,000
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 enseignants0,002
Score d'incertitude au seuil0,006

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0000,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,001

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 Opus0,012
Tête enseignante GPT0,276
Écart entre enseignants0,264 · 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

Citations1
Publié2019
Routes d'admission1
Résumé présentoui

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