(Invited) Investigations into the Chemical Role of Additives in Li-Ion Cells
Notice bibliographique
Résumé
INTRODUCTION For over a decade, the most common electrolyte solution in commercially available lithium-ion cells has remained LiPF6 dissolved in some blend of organic carbonate solvents.1 Rather than change the salt or the solvent, many industrial production lines have adopted the use of electrolyte additives to improve cycling performance, extend calendar lifetime, decrease detrimental gas formation and improve lithium-ion cell safety. The practical advantage of this move to electrolyte additives is that performance improvements can be achieved with minimal changes to existing supply chains for electrolyte salts and solvents. However, the optimization of lithium-ion cells for various applications (automotive, grid storage, etc.) would be greatly enhanced by a more detailed understanding of the cell chemistry. In particular, it is desirable to characterize the chemical and electrochemical reactions that occur during solid-electrolyte interphase (SEI) formation for the various additives in use. This presentation will demonstrate how our group has used computational and experimental methods, together, to study SEI formation for two additives, prop-1-ene-1,3-sultone (PES)2 and pyridine boron trifluoride (PBF).3 EXPERIMENTAL Density functional theory (DFT) calculations were performed with the Gaussian 09 (G09.D01) software package using the B3LYP and M06-2X hybrid functionals. The IEFPCM-UFF solvation model and its parameterization will be discussed.4 Several experimental methods will be discussed, including coulometry, in situ volumetric measurements using the Measuring Archimedes’ Gas Evolution (MAGE) instrument, gas-chromatography coupled with mass spectrometry (GC-MS) and thermal conductivity detection (GC-TCD), X-ray photoelectron spectroscopy (XPS), and isothermal microcalorimetry. Experimental details have been described previously.5–9 RESULTS AND DISCUSSION During the initial formation cycle (i.e., the first charge step), PES forms a passive SEI at the negative electrode surface via a two-electron electrochemical reduction, which produces Li2PES (Figure 1). The decomposition of this compound and its various reactions with the solvent (EC and EMC) and with other PES molecules will be discussed. These reactions are spontaneous and result in the formation of Li2SO3 and organic sulfate species (RSO3Li) at the anode. This is a good match to the S2ppeaks observed in the XPS spectrum of the anode after formation. The predicted gas-phase products, including several hydrocarbons at the anode, are also consistent with those observed by GC-MS. PBF similarly forms a passive SEI at the graphite surface by electrochemical reduction. The reduced species, LiPBF, forms a bipyridine boron trifluoride adduct, which is accompanied by the reduction of the solvent component, ethylene carbonate (EC). This reaction produces lithium ethyl carbonate, a soluble lithium semicarbonate. This reaction pathway does not produce an appreciable amount of any gas-phase species, as demonstrated by MAGE, GC-MS, and GC-TCD results. The predicted PBF-derived dimer is consistent with the C1s and N1s peaks observed in the XPS spectrum of the anode surface after formation. In summary, carefully developed theoretical methods coupled with experimental data reveal several spontaneous pathways for the reductive decomposition of two additives, PES and PBF. It is hoped that these results will prove useful for developing new and improved electrolyte additives. Moreover, these results provide new insight into the role of the solvent molecules during SEI formation that may have significance for research into new solvents and solvent blends. REFERENCES 1. K. Xu, Chem. Rev., 114, 11503–11618 (2014). 2. B. Li, M. Xu, T. Li, W. Li, and S. Hu, Electrochem. Commun., 17, 92–95 (2012). 3. M. Nie, J. Xia, and J. R. Dahn, J. Electrochem. Soc., 162, A1186–A1195 (2015). 4. D. S. Hall, J. Self, and J. R. Dahn, J. Phys. Chem. C, 119, 22322–22330 (2015). 5. C. P. Aiken et al., J. Electrochem. Soc., 161, A1548–A1554 (2014). 6. V. L. Chevrier et al., J. Electrochem. Soc., 161, A783–A791 (2014). 7. L. Madec et al., J. Phys. Chem. C, 118, 29608–29622 (2014). 8. R. Petibon, L. M. Rotermund, and J. R. Dahn, J. Power Sources, 287, 184–195 (2015). 9. J. Self, D. S. Hall, L. Madec, and J. R. Dahn, J. Power Sources, 298, 369–378 (2015). Figure 1
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,041 | 0,022 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».