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Record W4389239346 · doi:10.1002/smtd.202301084

Operando X‐Ray Diffraction Boosting Understanding of Graphite Phase Evolution in Lithium‐Ion Batteries

2023· article· en· W4389239346 on OpenAlexfundno aff
Jinkun Wang, Yun Gao, Jianhong Liu, Hongying Liao, Li Wang, Xiangming He

Bibliographic record

VenueSmall Methods · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsnot available
FundersTsinghua National Laboratory for Information Science and TechnologyMinistry of Science and Technology of the People's Republic of ChinaCanada Excellence Research Chairs, Government of CanadaNational Natural Science Foundation of China
KeywordsMaterials scienceDiffractometerElectrodeAnodeLithium (medication)GraphiteDiffractionLithium-ion batteryBattery (electricity)Phase (matter)IonAnalytical Chemistry (journal)Chemical engineeringComposite materialChemistryThermodynamicsScanning electron microscopeChromatographyPhysicsPhysical chemistry

Abstract

fetched live from OpenAlex

diffusion kinetics. The phase evolution and intrinsic properties of an electrode material under different C-rates can be investigated by applying operando X-ray diffraction (XRD). In this study, a transmission X-ray diffractometer is used in operando monitoring the behaviors of NCM811/Graphite pouch cells during charging/discharging at low rate (0.1C) and high rate (2.5C), especially the structure changes, phase evolution, and relaxation of graphite anode. The variations in XRD patterns, as well as and the inconsistency between the state of charge (SOC) of full cells and the SOC of electrodes, are explained based on genetic algorithm and shrinking annuli model. Furthermore, from the perspectives of monitoring and identification of electrode state, structural design of materials and electrodes, and optimization of charging/discharging protocols, practical suggestions for understanding the state and improving the performance of electrodes are proposed.

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 score0.002

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.088
GPT teacher head0.368
Teacher spread0.281 · 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".

Quick stats

Citations5
Published2023
Admission routes1
Has abstractyes

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