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Record W4229852006 · doi:10.1149/ma2018-02/6/430

Positive – Positive Symmetric Cell Study on the Compatibility of Different Electrolyte Additives with Li[Ni<sub>0.6</sub>Mn<sub>0.2</sub>Co<sub>0.2</sub>]O<sub>2</sub>

2018· article· en· W4229852006 on OpenAlexaff
Yulong Liu, J. R. Dahn

Bibliographic record

VenueECS Meeting Abstracts · 2018
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsDalhousie University
Fundersnot available
KeywordsElectrolyteElectrodeCompatibility (geochemistry)Half-cellMaterials scienceIonAnalytical Chemistry (journal)ChemistryInorganic chemistryWorking electrodeComposite materialPhysical chemistryChromatography

Abstract

fetched live from OpenAlex

Electrode/electrolyte compatibility plays a critical role to increase the energy density and longevity of lithium-ion cells. A sound understanding of the interactions between electrode and electrolyte allows us to design better electrolyte formulation with more suitable additives. Nevertheless, the study of electrode/electrolyte interaction is difficult to carry out in a full lithium-ion cell due to the interactions between positive and negative electrodes, such as the migration of oxidation products and dissolved transition metal to the negative electrode1, and the effect of different negative electrodes on the surface layer composition of positive electrode2. In recent years, there has been quite a few experimental techniques developed aiming to solve this problem3,4. Among them, symmetric cells are excellent test vehicles where performance is exclusively determined by the compatibility of the electrode of interest with the electrolyte of choice. In this study, the compatibility of two electrolyte additives, vinylene carbonate (VC) and prop-1-ene-1,3-sultone (PES), with uncoated polycrystalline Li[Ni0.6Mn0.2Co0.2]O2 were studied using positive-positive symmetric cells with electrodes hand-made from powder. Each symmetric cell was constructed with one fresh electrode and one delithiated electrode prepared using a coin-cell half cell. These symmetric cells were then cycled at 40oC with 10 cycles of C/10 followed by 1 cycle of C/30 repeatedly between ±0.9 V, ±0.8 V, ±0.7 V, ±0.6 V, ±0.5 V, which correspond to half cell voltages of 4.39 V, 4.35 V, 4.29 V, 4.22 V and 4.15 V vs. Li/Li+, respectively. It was found that for all symmetric cells cycled with the chosen voltage cut-offs, the cells containing VC showed better capacity retention compared to those with PES. This is surprising because in full Li-ion cells operated above 4.3 V, the opposite was found to be true by Lin Ma et al. 5 The symmetric cell building method in this work can also be used to study electrode/electrolyte compatibility when machine-made electrodes are not readily available to researchers. References A. J. Smith, J. C. Burns, D. Xiong, and J. R. Dahn, J. Electrochem. Soc., 158, A1136 (2011) E. Björklund, D. Brandell, M. Hahlin, K. Edström, and R. Younesi, J. Electrochem. Soc., 164, A3054–A3059 (2017) D. J. Xiong et al., J. Electrochem. Soc., 164, A340–A347 (2017) C. Shen et al., J. Electrochem. Soc., 164, A3349–A3356 (2017) Lin Ma et al, J. Electrochem. Soc. 161, A2250-A2254, (2014). 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.227
Teacher spread0.217 · 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
Published2018
Admission routes1
Has abstractyes

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