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Record W2522034864 · doi:10.1149/2.0081701jes

Cycling Behavior of NCM523/Graphite Lithium-Ion Cells in the 3–4.4 V Range: Diagnostic Studies of Full Cells and Harvested Electrodes

2016· article· en· W2522034864 on OpenAlexfundno aff
James A. Gilbert, Javier Bareño, T. Spila, Stephen E. Trask, Dean J. Miller, Bryant J. Polzin, Andrew N. Jansen, Daniel P. Abraham

Bibliographic record

VenueJournal of The Electrochemical Society · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsnot available
FundersOak Ridge National LaboratoryArgonne National LaboratoryBasic Energy SciencesUniversity of Illinois at Urbana-ChampaignDalhousie UniversityDivision of Materials ResearchU.S. Department of Energy
KeywordsElectrodeElectrolyteDielectric spectroscopyHalf-cellLithium (medication)X-ray photoelectron spectroscopyMaterials scienceElectrochemistryAnalytical Chemistry (journal)InterphaseReversible hydrogen electrodeWorking electrodeChemistryChemical engineeringChromatography

Abstract

fetched live from OpenAlex

Energy density of full cells containing layered-oxide positive electrodes can be increased by raising the upper cutoff voltage above the current 4.2 V limit. In this article we examine aging behavior of cells, containing LiNi<sub>0.5</sub>Co<sub>0.2</sub>Mn<sub>0.3</sub>O<sub>2</sub> (NCM523)-based positive and graphite-based negative electrodes, which underwent up to ~400 cycles in the 3-4.4 V range. Electrochemistry results from electrodes harvested from the cycled cells were obtained to identify causes of cell performance loss; these results were complemented with data from X-ray photoelectron spectroscopy (XPS) and secondary ion mass spectroscopy (SIMS) measurements. Our experiments indicate that the full cell capacity fade increases linearly with cycle number and results from irreversible lithium loss in the negative electrode solid electrolyte interphase (SEI) layer. The accompanying electrode potential shift reduces utilization of active material in both electrodes and causes the positive electrode to cycle at higher states-of-charge. Here, full cell impedance rise on aging arises primarily at the positive electrode and results mainly from changes at the electrode-electrolyte interface; the small growth in negative electrode impedance reflects changes in the SEI layer. Our results indicate that cell performance loss could be mitigated by modifying the electrode-electrolyte interfaces through use of appropriate electrode coatings and/or electrolyte additives.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.320

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.011
GPT teacher head0.251
Teacher spread0.240 · 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 teacher head, 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".

Quick stats

Citations174
Published2016
Admission routes1
Has abstractyes

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