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Record W4395115855 · doi:10.1021/acs.jpclett.4c00760

Reinterpreting the Intercalation-Conversion Mechanism of FeP Anodes in Lithium/Sodium-Ion Batteries from Evolution of the Magnetic Phase

2024· article· en· W4395115855 on OpenAlexaff
Hengjun Liu, Feihu Zou, Shuxuan Liao, Yuanyuan Pan, Zhiqiang Zhao, Fangchao Gu, Xixiang Xu, Xiancheng Sang, Yuanyuan Han, Zeyuan Bu, Lihao Qin, Yukui Wang, Guihuan Chen, Mingyue Ruan, Qinghao Li, Han Hu, Qiang Li

Bibliographic record

VenueThe Journal of Physical Chemistry Letters · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsUniversity of Waterloo
FundersNatural Science Foundation of Shandong ProvinceNational Natural Science Foundation of China
KeywordsAnodeIntercalation (chemistry)Lithium (medication)ElectrochemistryMaterials scienceBattery (electricity)GrapheneOxideSodiumChemical engineeringIonReaction mechanismInorganic chemistryChemistryElectrodeNanotechnologyCatalysisOrganic chemistryThermodynamicsMetallurgyPhysical chemistry

Abstract

fetched live from OpenAlex

Batteries with intercalation-conversion-type electrodes tend to achieve high-capacity storage, but the complicated reaction process often suffers from confusing electrochemical mechanisms. Here, we reinterpreted the essential issue about the potential of the conversion reaction and whether there is an intercalation reaction in a lithium/sodium-ion battery (LIB/SIB) with the FeP anode based on the evolution of the magnetic phase. Especially, the ever-present intercalation process in a large voltage range followed by the conversion reaction with extremely low potential was confirmed in FeP LIB, while it is mainly the conversion reaction for the sodium storage mechanism in FeP SIB. The insufficient conversion reaction profoundly limits the actual capacity to the expectedly respectable value. Accordingly, a graphene oxide modification strategy was proposed to increase the reversible capacity of FeP LIB/SIB by 99% and 132%, respectively. The results facilitate the development of anode materials with a high capacity and low operating potential.

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 head0.005
GPT teacher head0.221
Teacher spread0.216 · 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

Citations12
Published2024
Admission routes1
Has abstractyes

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