Examining Sulfur Nucleation and Growth on Carbon Nanomaterials from Aqueous, Elemental Sulfur Sols for Lithium−Sulfur Batteries
Notice bibliographique
Résumé
With decades of engineering, lithium-ion batteries are beginning to reach their fundamental energy density limits. As such, next generation chemistries that can store significantly more energy are essential for electrification of vehicles, improved portable electronics, and increased adoption of renewable energy sources. Lithium-sulfur batteries have attracted significant research attention due to their theoretical full cell capacity (1167 mAh/g) and gravimetric energy density (2500 Wh/kg) which are both an order of magnitude higher than conventional lithium-ion batteries. Furthermore, lithium-sulfur batteries employ elemental sulfur as the cathode material, which is both widely abundant and inexpensive, and also a common waste product of the petroleum industry, making the projected cost of lithium-sulfur cells per kWh much lower than conventional lithium-ion cells that rely on costly lithium transition metal oxide-based cathodes. However, a number of challenges plague the lithium-sulfur chemistry, one of the most critical being that elemental sulfur and its final discharge product, Li2S, are insulating in nature, requiring sulfur to be intimately mixed with a conductive, lightweight carbon material in order to facilitate electron transport. Because sulfur is typically redistributed throughout the cathode during cycling due to dissolution of intermediate polysulfide species in the electrolyte, the uniform coating of sulfur onto carbon materials has not garnered significant research attention. However, uniform distribution of the sulfur within the cathode is critical for several reasons. Large, insulating sulfur particles are not electrochemically converted during cycling, limiting cell capacity, and as sulfur undergoes an 80% volume change during cycling, non-uniform sulfur distribution can result in mechanical failure of the cathode. Moreover, as the field moves toward all-solid-state batteries, in which sulfur redistribution does not occur, the initial sulfur distribution within the cathode is critical for high performance cells. Nanoscale mixing of sulfur and carbon additives is typically achieved via melt imbibition, a lengthy, high-temperature process in which sulfur is melted and then used to coat solid carbon powders. This process typically employs carbon nanomaterials as aggregated solid powders, thereby limiting the accessible surface area that can be coated by sulfur. To access the exceptional surface area of carbon nanomaterials such as graphene (~2630 m2/g), the sulfur coating process needs to occur while the carbon nanomaterials are dispersed in solvent. While this has been demonstrated previously, it is typically done with highly toxic solvents such as CS2 due to sulfur’s limited solubility, or by using more costly and inefficient sulfur precursors, known as hydrophilic sulfur sols, to form elemental sulfur in situ. We demonstrate, for the first time, the use of aqueous, hydrophobic sulfur sols to coat carbon nanomaterials in solution at room temperature. Hydrophobic sulfur sols are sub-micron, metastable sulfur particles which are formed via the rapid dilution of an organic solution of sulfur into large quantities of water. We demonstrate that due to the metastable nature of these hydrophobic sulfur sols in the aqueous system, sulfur dissolves out of the sols and can uniformly coat the surface of dispersed carbon nanomaterials such as reduced graphene oxide (rGO) via a heterogeneous nucleation and growth process. This process is simple, scalable, employs inexpensive elemental sulfur directly, and can be performed at room temperature with an aqueous system, making it an attractive method to prepare sulfur cathodes. We study how the sulfur deposition process is affected by the introduction of a surfactant into the aqueous phase and the use of different organic solvents to prepare the sol, and further demonstrate that heterogeneous sulfur nucleation occurs preferentially with rGO, while a competing, undesirable homogeneous nucleation pathway that forms large insulating sulfur crystals is observed for Ketjen black and graphene oxide. We demonstrate that via this approach, high loading (3-4 mgsulfur/cm2) rGO/sulfur cathodes can be prepared that achieve capacities of 1300 mAh/g (~4.8 mAh/cm2) at 0.1C, and capacities 7-fold higher than cells prepared via traditional melt imbibition approaches at higher C rates of 0.8C and 1C. Moreover, we demonstrate that these cells can be prepared without additional conductive additives or binder and can achieve projected energy densities of ~468 Wh/kg at 0.1C when considering all inactive components and no lithium degradation, indicating the promise of this simple, novel approach for high energy density sulfur cathodes.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
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 ».