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Record W3184608535 · doi:10.1021/acsenergylett.1c01215

Ni/Mn and Al Dual Concentration-Gradients To Mitigate Voltage Decay and Capacity Fading of Li-Rich Layered Cathodes

2021· article· en· W3184608535 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueACS Energy Letters · 2021
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsCathodeFadingElectrochemistryMaterials scienceX-ray photoelectron spectroscopyRedoxChemical engineeringConcentration gradientVoltageIonAnalytical Chemistry (journal)ElectrodeChemistryMetallurgyElectrical engineeringPhysical chemistryEnvironmental chemistry

Abstract

fetched live from OpenAlex

Li-rich layered oxides (LLOs) suffer from severe voltage decay and capacity fading which have hindered their practical application for years. Herein, Co-free LLO microspheres with Ni/Mn and Al dual concentration-gradients are constructed to mitigate the above obstacles. One concentration-gradient is an electrochemical active gradient (Ni/Mn), and the other is an electrochemical inert gradient (Al). XPS and soft and hard XAS after different cycles prove that the combination of dual concentration-gradients effectively mitigates interfacial reactions, structural evolution, and the generation of lower-valence Mn3+/Mn4+ or Mn2+/Mn3+ redox couples during cycling. As a result, the voltage fading rate of LLO cathode with dual concentration-gradients after 100 cycles is as small as 0.97 mV/cycle at 100 mA g–1. Furthermore, its capacity retention ratio is also as large as 84.1% after 400 cycles at 300 mA g–1. The combination of dual concentration-gradients in this work provides a way to develop advanced LLO cathodes for practical application in the near future.

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.

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)0.000
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 score0.008
Threshold uncertainty score0.682

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.012
GPT teacher head0.218
Teacher spread0.206 · 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