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Record W4411774407 · doi:10.1002/aenm.202502363

Molecular Interlocking Multidimensional Modulations of Cathode‐Electrolyte Interface for Constructing High Energy Density Quasi‐Solid‐State Batteries

2025· article· en· W4411774407 on OpenAlexfundno aff
Xinyou He, Haozhe Qin, Junxiang Liu, Jiaqi Wang, Zhiming Xiao, Lei Ming, Tongchao Liu, Khalil Amine, Xing Ou

Bibliographic record

VenueAdvanced Energy Materials · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsnot available
FundersArgonne National LaboratoryMajor Scientific and Technological Special Project of Guizhou ProvinceOffice of ScienceUniversity of ChicagoOffice of Energy Efficiency and Renewable EnergyCanada Excellence Research Chairs, Government of CanadaU.S. Department of Energy
KeywordsMaterials scienceInterlockingElectrolyteCathodeEnergy densityQuasi-solidEnergy (signal processing)Interface (matter)Chemical physicsNanotechnologyChemical engineeringEngineering physicsElectrodePhysical chemistryComposite materialMechanical engineering

Abstract

fetched live from OpenAlex

Abstract Gel polymers are regarded as a promising candidate electrolyte for lithium‐metal quasi‐solid‐state batteries, primarily due to their high ionic conductivity and solid‐liquid synergistic properties. However, challenges such as interfacial side reactions, limitations in Li + transport caused by interfacial issues, and leaching of transition metals from the cathode have yet to be effectively solved. Herein, a novel gel electrolyte modulation strategy based on electrostatic filler assembly is proposed to address the issues of ineffective capacity utilization and inadequate cycling stability of high‐energy‐density cathode materials in solid‐state lithium‐ion batteries. It constructs a 3D interpenetrating charge‐bridge network that effectively tackles the phase‐separation challenge between fillers and electrolytes at the molecular level. Meanwhile, the molecular interlocking structure effectively inhibits the electrolyte erosion. More critically, it optimizes and stabilizes the cathode‐electrolyte interface film, which facilitates the conduction of Li⁺‐ions through a size‐sieving mechanism. Consequently, this strategy enables effective adaptation across diverse high‐energy‐density cathode materials with satisfactory capacity performance (170.4 mAh g −1 at 4.5 V/1 C for LiNi 0.6 Co 0.2 Mn 0.2 O 2 and 194.0 mAh g −1 at 4.3 V/1 C for LiNi 0.9 Co 0.08 Mn 0.02 O 2 ). This investigation offers a straightforward and effective reference for addressing the critical challenges of ionic transport and interface stabilization in the design of gel electrolytes.

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 score0.424
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.006
GPT teacher head0.250
Teacher spread0.244 · 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

Citations3
Published2025
Admission routes1
Has abstractyes

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