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Record W3207130879 · doi:10.1038/s41467-021-24404-1

In situ observation of thermal-driven degradation and safety concerns of lithiated graphite anode

2021· article· en· W3207130879 on OpenAlexfundno aff
Xiang Liu, Liang Yin, Dongsheng Ren, Li Wang, Yang Ren, Wenqian Xu, Saul H. Lapidus, Hewu Wang, Xiangming He, Zonghai Chen, Gui‐Liang Xu, Minggao Ouyang, Khalil Amine

Bibliographic record

VenueNature Communications · 2021
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsnot available
FundersVehicle Technologies OfficeDepartment of Science and Technology for Social DevelopmentOffice of ScienceArgonne National LaboratoryBasic Energy SciencesMinistry of Science and Technology of the People's Republic of ChinaCanada Excellence Research Chairs, Government of CanadaU.S. Department of Energy
KeywordsAnodeGraphiteMaterials scienceElectrolyteLithium (medication)Chemical engineeringDegradation (telecommunications)Flammable liquidElectrodeComposite materialChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Graphite, a robust host for reversible lithium storage, enabled the first commercially viable lithium-ion batteries. However, the thermal degradation pathway and the safety hazards of lithiated graphite remain elusive. Here, solid-electrolyte interphase (SEI) decomposition, lithium leaching, and gas release of the lithiated graphite anode during heating were examined by in situ synchrotron X-ray techniques and in situ mass spectroscopy. The source of flammable gas such as H 2 was identified and quantitively analyzed. Also, the existence of highly reactive residual lithium on the graphite surface was identified at high temperatures. Our results emphasized the critical role of the SEI in anode thermal stability and uncovered the potential safety hazards of the flammable gases and leached lithium. The anode thermal degradation mechanism revealed in the present work will stimulate more efforts in the rational design of anodes to enable safe energy storage.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.530
Threshold uncertainty score0.282

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 head0.028
GPT teacher head0.290
Teacher spread0.262 · 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

Citations247
Published2021
Admission routes1
Has abstractyes

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