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Record W3213725232 · doi:10.1002/adfm.202108692

Unleash the Capacity Potential of LiFePO<sub>4</sub> through Rocking‐Chair Coordination Chemistry

2021· article· en· W3213725232 on OpenAlexaff
Zhong Ma, Zhijun Zuo, Lin Li, Yuning Li

Bibliographic record

VenueAdvanced Functional Materials · 2021
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsUniversity of Waterloo
FundersShanghai Jiao Tong UniversityNational Natural Science Foundation of China
KeywordsCathodeMaterials scienceAdsorptionDiffusionIonAtom (system on chip)ElectrodeLithium (medication)ZincChemical engineeringNanotechnologyPhysical chemistryThermodynamicsChemistryMetallurgyPhysicsOrganic chemistryComputer science

Abstract

fetched live from OpenAlex

Abstract There is still a considerable gap between the actual and theoretical capacities of the commercial cathode material LiFePO 4 (LFP) for lithium‐ion batteries (LIBs). Here, a new strategy to release the full capacity of LFP through the rocking‐chair coordination chemistry is reported. Specifically, the zinc acetate‐diethanolamine complex (Zn(OAc) 2 ·DEA) is used as a functional binder for the LFP cathode, where the N atom of DEA can coordinate with Zn 2+ , Fe 2+ , or Fe 3+ . The bond strength sequence is Fe 3+ –N &gt; Zn 2+ –N &gt; Fe 2+ –N, which makes the N atom swing between Fe 3+ on the surface of FePO 4 in the charged state and Zn 2+ of Zn(OAc) 2 in the discharged state. Density functional theory simulations reveal that the adsorption of DEA reduces the surface bandgap and the energy barriers of Li + diffusion along the [010] direction of LFP, which promotes electronic conduction and Li + diffusion, respectively. The Zn(OAc) 2 ·DEA‐based LFP electrode achieves a high capacity of 169 mAh g −1 at 0.2C, which approaches the theoretical value of 170 mAh g −1 . The electrode also has excellent cycling performance, showing a low capacity decay rate of 0.03% per cycle over 1500 cycles at 5C.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score0.956

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)0.0010.000

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 head0.012
GPT teacher head0.204
Teacher spread0.193 · 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

Citations24
Published2021
Admission routes1
Has abstractyes

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