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Record W4285794527 · doi:10.1002/batt.202200257

Designing Low‐Concentration Propylene Carbonate‐based Electrolyte by Manipulating Lithium<sup>+</sup>‐Solvation Structure for Graphite Anode

2022· article· en· W4285794527 on OpenAlexaff
Dichang Guan, Guorong Hu, Zhongdong Peng, Zhanggen Gan, Xu‐Dong Zhang, Ke Du

Bibliographic record

VenueBatteries & Supercaps · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsMinistry of Education and Child Care
FundersNational Natural Science Foundation of China
KeywordsSolvationPropylene carbonateElectrolyteGraphiteLithium (medication)AnodeElectrochemistryChemistryDecompositionIntercalation (chemistry)Ethylene carbonateInorganic chemistrySolventMaterials sciencePhysical chemistryOrganic chemistryElectrode

Abstract

fetched live from OpenAlex

Abstract We systematically study the correlation between Li + ‐solvation structure, interfacial stability, and electrochemical behavior in the system of graphite anode with low‐concentration (0.5 M) propylene carbonate (PC)‐based electrolyte (LCPE). 1,1,2,2‐tetrafluoroethyl‐2,2,3,3‐tetrafluoropropylether (TTE) [or 1,1,2,2‐tetrafluoroethyl‐2,2,2‐trifluoroethyl ether (HFE)] is used to manipulate the solvation structures of Li + in the LCPEs. Varying Li + ‐solvation structures are realized by changing the volume ratios of PC to TTE (or HFE) in the LCPEs. With the increase of TTE (or HFE) dosages, the relative contents of LiF and Li x PO y F z in SEI derived from increase, while the decomposition products of PC reduce. With enough TTE (or HFE) in the LCPE, the Li||graphite cell exhibits reversible (de)lithiation without PC co‐intercalation and continuous electrolyte decomposition due to the shield of a compact SEI rich in LiF and Li x PO y F z . Our work proves it is practicable to achieve LiF‐riched SEIs on graphite anodes and realize reversible (de)lithiation in LCPEs by regulating the Li + ‐solvation structures with inert cosolvents.

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 categoriesMeta-epidemiology (narrow)
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 score0.065
Threshold uncertainty score1.000

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 communication0.0000.001
Open science0.0000.000
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 head0.009
GPT teacher head0.212
Teacher spread0.203 · 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.

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

Citations7
Published2022
Admission routes1
Has abstractyes

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