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Record W2610887560 · doi:10.1149/ma2017-01/5/370

A Sulfide Solid Electrolyte Surface Layer Formed Via Electrolyte Additives Enables Stable Plating of Li Metal

2017· article· en· W2610887560 on OpenAlexaff
Quanquan Pang, Linda F. Nazar

Bibliographic record

VenueECS Meeting Abstracts · 2017
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsElectrolyteSulfideChemical engineeringMaterials scienceSeparator (oil production)Fast ion conductorPlating (geology)Ionic conductivityInorganic chemistryChemistryElectrodeMetallurgy

Abstract

fetched live from OpenAlex

Li metal batteries promise the next-generation rechargeable batteries for electric vehicles applications due to the highest specific capacity (3840 mA h g-1) and lowest reduction potential (−3.04 V vs. S.H.E.) of Li among all alkali and alkaline earth metals. However, a non-uniform solid electrolyte interphase (SEI) layer formed via parasite reactions of Li with the electrolytes leads to locally site-specific Li deposition, i.e., dendritic plating.1 Dynamic breaking and forming of this layer, in turn, leads to the accumulative loss of Li, build-up of the SEI and consumption of the electrolyte causing cell failure. Upon prolonged cycling, penetration of dendrites through the separator causes hazardous cell short-circuits. Modified electrolytes including concentrated electrolytes,2 LiF additive3 and artificial SEI layer4 have shown promise in suppressing dendrites. In this presentation, we will demonstrate an in-vivo formed sulfide-based ionic conductive layer — realized by using a low concentration complexed electrolyte additive — that not only generates a kinetically favorable interface, but also reduces the corrosive reactions of the electrolyte with Li. Upon Li plating, the high ionic conductivity of the solid electrolyte layer allows the Li+flux to be evenly distributed over the conductive surface. Furthermore, even at extremely high current densities when incipient dendritic Li start to form, the reservoir additives in the electrolyte facilitate local formation of the conductive layer. Upon resting at OCV, the Li|Li symmetric cell in the presence of the electrolyte additive shows much lower interfacial charge transfer resistance than a cell with a “blank” electrolyte (20 vs. 320 Ω cm-2). Furthermore, the impedance is stable over 2 days of rest, in contrast with significantly increasing impedance exhibited by the blank cell. Greatly improved long-term cycling of the symmetric cells is observed. The cell with additive exhibits extremely stable voltage evolution over 400 hours, whereas the blank electrolyte cell experiences voltage fluctuation followed by short-circuit after 270 hours (Figure 1a). Notably, stable cycling of Li|Li symmetric cells over 2500 hours at 1 mA cm-2 with 1 mA h cm-2 capacity was achieved using 100 mM additive (Figure 1b), and a significant decrease in polymerized solvent is observed compared to a cell with no additive. In a full Li metal cell using Li4Ti5O12 as the positive electrode, the cell with the electrolyte additive exhibits very stable capacity retention (88%) over 400 cycles. Reference 1. Y. S. Cohen, Y. Cohen, D. Aurbach, J. Phys. Chem. B, 2000, 104, 12282-12291. 2. J. Qian, W. A. Henderson, W. Xu, P. Bhattacharya, M. Engelhard, O. Borodin, J.-G. Zhang, Nat. Commun., 2015, 6, 6362. 3. Y. Lu, Z. Tu, L. A. Archer, Nat. Mater., 2014, 13, 961–969. 4. G. Zheng, S. W. Lee, Z. Liang, H.-W. Lee, K. Yan, H. Yao, H. Wang, W. Li, S. Chu, Y. Cui, Nat. Nanotech., 2014, 9, 618–623. Figure 1

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.241
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2017
Admission routes1
Has abstractyes

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