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Enregistrement W2512863837 · doi:10.1149/ma2016-02/3/316

Sulfur Atoms Bridging Few-Layered MoS<sub>2</sub> with S-Doped Graphene Enables Highly Robust Anode for Lithium-Ion Batteries

2016· article· en· W2512863837 sur OpenAlexaff
Xiaolei Wang, Ge Li, Min Ho Seo, Zhongwei Chen

Notice bibliographique

RevueECS Meeting Abstracts · 2016
Typearticle
Langueen
DomaineMaterials Science
ThématiqueMXene and MAX Phase Materials
Établissements canadiensUniversity of Waterloo
Organismes subventionnairesnon disponible
Mots-clésAnodeMaterials scienceFaraday efficiencyGrapheneLithium (medication)Transition metalGraphiteNanotechnologyElectrodeChemical engineeringComposite materialChemistry

Résumé

récupéré en direct d'OpenAlex

Tremendous research interest from both academy and industry has been dedicated to the rechargeable lithium-ion batteries (LIBs) in the last decades for the upcoming era of portable electronics, electric vehicles (EVs) and hybrid electric vehicles (HEVs). As one of the favorite power sources, most commercial LIBs utilize natural or synthetic graphite as the anode material due to its low cost, high Coulombic efficiency, and flat and low average potential of 0.2 V ( vs. Li/Li + ), as well as long cycle life. However, its specific capacity of 372 mA h g -1 results in a device energy density of ~150 W h kg -1 , which is much lower than that of internal-combustion engines and cannot meet the EVs requirements. Therefore, there is an urgent need to develop novel anode materials with high theoretical capacities to replace graphite in next generation high energy LIBs. So far, various materials have been extensively studies for LIBs anodes, including alloys (e.g. Si and Sn) and transition metal oxides (e.g. Li 4 Ti 5 O 12 and SnO 2 ). Although most of these materials possess a significant larger specific capacity, they suffer from either poor cycling life due to volume change associated with Li-ion insertion/extraction or sluggish electrode kinetics stemmed from slow ion diffusivity or intrinsic poor electron conductivity. Compared to metal oxide materials, some transition metal sulfides possess high specific capacity and unique structures, and have been considered as promising candidates for high-performance anode materials. Among various candidates, a typical member of transition metal sulfide-molybdenum disulfide (MoS 2 ) possesses a similar layered structure to graphite but a much larger interlayer spacing of 6.15 Å ( vs. 3.35 Å of graphene) by stacking together through van der Waals interactions, which facilitates lithium-ion intercalation without a significant volume expansion. However, MoS 2 still suffers from fast structural deterioration during lithiation/de-lithiation process and poor electrical/ionic conductivity, resulting in unsatisfactory cycling performance and rate capability in LIBs application. Therefore, the development of novel highly stable MoS 2 -based materials with fast kinetics remains challenging, owing to the lack of a ration design from molecular level. Moreover, it is also critical to correlate the performance with materials structure, and to understand the chemistry behind before its future practical applications. Herein, we demonstrate a facile solvothermal synthesis of nanocomposites consisting few-layered MoS 2 and covalently sulfur-doped graphene (MoS 2 /SG) with excellent electrochemical performance. We focus on not only the development of MoS 2 -based electrode materials but also the materials design based on both structure and chemistry considerations. The sulfur atoms covalently bonded to graphene sheets and effectively bridging two-dimensional (2D) few-layered MoS 2 and graphene enable high robustness of the composite materials. Moreover, the intimate contact of MoS 2 and highly conductive graphene provides efficient electron transfer pathways, while the high surface of assembled 2D structured materials allows fast access to active materials. Such a unique composite architecture derived from the “bridging effect” ensures the electrode with an exceptional cycling stability and superior rate capability, which is also interpreted by the density functional theory (DFT) calculations. A capacity retention of 92.3% can be achieved after 2000 cycles at a current density of 10 A g -1 ; even at a high current density of 20 A g -1 , the electrode still possesses a specific capacity of 766 mA h g -1 . This composite material with excellent electrochemical properties synthesized via a facile solvo-thermal approach holds great promise in the practical application of high-performance LIBs. 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)0,002
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
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 seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
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 Opus0,020
Tête enseignante GPT0,228
Écart entre enseignants0,207 · 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.

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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